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AUGMENTED REALITY
A B S T R A C T
Augmented reality adds information and meaning to a real object or place. Unlike virtual reality, augmented reality does not create a simulated reality. Instead, it takes a real object or space and uses technologies to add contextual data to deepen understanding of it. This paper surveys the field of Augmented Reality, in which 3-D virtual objects are integrated into a real environment in real time. It describes the medical, manufacturing, visualization, entertainment and military applications that have been explored. This paper describes the characteristics of Augmented Reality systems, including a brief discussion of the tradeoffs between optical and video blending approaches. Registration and sensing errors are two of the biggest problems in building effective Augmented Reality systems, so this paper summarizes current efforts to overcome these problems. Future directions and areas requiring further research are discussed. On the spectrum between virtual reality, which creates immersible, computer-generated environments, and the real world, augmented reality is closer to the real world. Augmented reality adds graphics, sounds, haptics and smell to the natural world as it exists. You can expect video games to drive the development of augmented reality, but this technology will have countless applications. Everyone from tourists to military troops will benefit from the ability to place computer-generated graphics in their field of vision.
Name : Suryendu sangam Samal
Regd. : 0601289094
A Seminar Report for the Final Review On AUGMENTED REALITY
No: 0601289086
7th Semester
I N T R O D U C T I O N
This paper describes the current state-of-the-art in Augmented Reality. It describes work performed at many different sites and explains the issues and problems encountered when building Augmented Reality systems. It summarizes the tradeoffs and approaches taken so far to overcome these problems and speculates on future directions that deserve exploration.Section 1 describes what Augmented Reality is and the motivations for developing this technology. Section 2 discusses the issues involved in building an Augmented Reality system. Currently, two of the biggest problems are in registration and sensing: the subjects of Sections 3 and 4. Section 5 describes the advantage of augmented reality over virtual environment systems . Five classes of potential applications that have been explored are described in Section 6. Finally, Section 7 describes some areas that require further work and research. Augmented reality will truly change the way we view the world. Picture yourself walking or driving down the street. With augmented-reality displays, which will eventually look much like a normal pair of glasses, informative graphics will appear in your field of view, and audio will coincide with whatever you see. These enhancements will be refreshed continually to reflect the movements of your head. In this article, we will take a look at this future technology, its components and how it will be used. Tourists that visit historical sites, such as a Civil War battlefield do not see these locations as they were in the past, due to changes over time. It is often difficult for a modern visitor to imagine what these sites really looked like in the past. A tourist equipped with an outdoors AR system could see a computer-generated version of Living History. Tourists and students walking around the grounds with such AR displays would gain a much better understanding of these historical sites and the important events that took place there. After the basic problems with AR are solved, the ultimate goal will be photorealism has been demonstrated in feature films, but accomplishing this in an interactive application will be much harder.
Augmented Reality :
Augmented Reality (AR) is a variation of Virtual Environments (VE), or Virtual Reality as it is more commonly called. VE technologies completely immerse a user inside a synthetic environment. While immersed, the user cannot see the real world around him. In contrast, AR allows the user to see the real world, with virtual objects superimposed upon or composited with the real world. Therefore, AR supplements reality, rather than completely replacing it. Ideally, it would appear to the user that the virtual and real objects coexisted in the same space, Figure shows an example of what this might look like. All these things are optional also ,i.e. they can be ignored if the user want some specific details rather than details for everything that comes in itâ„¢s way . AR can be thought of as the "middle ground" between VE (completely synthetic) and telepresence (completely real).This survey defines AR as systems that have the following three characteristics:
1) Combines real and virtual
2) Interactive in real time
3) Registered in 3-D
REALITY AUGMENTED REALITY VIRTUAL REALITY
2 DESIGN :
A see-through HMD is one device used to combine real and virtual. Standard closed-view HMDs do not allow any direct view of the real world. In contrast, a seethrough HMD lets the user see the real world, with virtual objects superimposed by optical or video technologies.
2.1 Optical see-through HMD :
Optical see-through HMDs work by placing optical combiners in front of the user's eyes. These combiners are partially transmissive, so that the user can look directly through them to see the real world. The combiners are also partially reflective, so that the user sees virtual images bounced off the combiners from head mounted monitors. This approach is similar in nature to Head-Up Displays (HUDs) commonly used in military aircraft, except that the combiners are attached to the head. The optical combiners usually reduce the amount of light that the user sees
from the real world. Since the combiners act like half-silvered mirrors, they only let in some of the light from the real world, so that they can reflect some of the light from the monitors into the user's eyes. Choosing the level of blending is a design problem. More sophisticated combiners might vary the level of contributions based upon the wavelength of light. For example, such a combiner might be set to reflect all light of a certain wavelength and none at any other wavelengths. This would be ideal with a monochrome monitor. Virtually all the light from the monitor would be reflected into the user's eyes, while almost all the light from the real world (except at the particular wavelength) would reach the user's eyes. However, most existing optical see-through HMDs do reduce the amount of light from the real world, so they act like a pair of sunglasses when the power is cut off.
2.2 Video see-through HMD :
Video see-through HMDs work by combining a closed-view HMD with one or two head-mounted video cameras. The video cameras provide the user's view of the real world. Video from these cameras is combined with the graphic images created by the scene generator, blending the real and virtual. The result is sent to the monitors in front of the user's eyes in the closed-view HMD. Figure shows a conceptual diagram of a video see-through HMD. Video composition can be done in more than one way. A simple way is to use chroma-keying, a technique used in many video special effects. The background of the computer graphic images is set to a specific color, say green, which none of the virtual objects use. Then the combining step replaces all green areas with the corresponding parts from the video of the real world. This has the effect of superimposing the virtual objects over the real world. A more sophisticated composition would use depth information. If the system had depth information at each pixel for the real world images, it could combine the real and virtual images by a 12 pixel-by-pixel depth comparison. This would allow real objects to cover virtual objects and vice-versa.
VIDEO SEE-THROUGH HMD CONCEPTUAL DIAGRAM
2.3 Monitor based AR :
AR systems can also be built using monitor-based configurations, instead of see-through HMDs. Figure shows how a monitor-based system might be built. In this case, one or two video cameras view the environment. The cameras may be static or mobile. In the mobile case, the cameras might move around by being attached to a robot, with their locations tracked. The video of the real world and the graphic images generated by a scene generator are combined, just as in the video see-through HMD case, and displayed in a monitor in front of the user. The user does not wear the display device.
MONITOR BASED AR CONCEPTUAL DIAGRAM
2.4 Trade offs between the two approaches :
The rest of this section compares the relative advantages and disadvantages of optical and video approaches, starting with optical. An optical approach has the following advantages over a video approach:
1) Simplicity:
Optical blending is simpler and cheaper than video blending. Optical approaches have only one "stream" of video to worry about: the graphic images. The real world is seen directly through the combiners, and that time delay is generally a few nanoseconds. Video blending, on the other hand, must deal with separate video streams for the real and virtual images. Both streams have inherent delays in the tens of milliseconds. Digitizing video images usually adds at least one frame time of delay to the video stream, where a frame time is how long it takes to completely update an image. A monitor that completely refreshes the screen at 60 Hz has a frame time of 16.67 ms. The two streams of real and virtual images must be properly synchronized or temporal distortion results. Also, optical see-through HMDs with narrow field-of-view combiners offer views of the real world that have little distortion. Video cameras almost always have some amount of distortion that must be compensated for, along with any distortion from the optics in front of the display devices. Since video requires cameras and combiners that optical approaches do not need, video will probably be more expensive and complicated to build than optical-based systems.
2) Resolution:
Video blending limits the resolution of what the user sees, both real and virtual, to the resolution of the display devices. With current displays, this resolution is far less than the resolving power of the fovea. Optical see-through also shows the graphic images at the resolution of the display device, but the user's view of the real world is not degraded. Thus, video reduces the resolution of the real world, while optical see-through does not.
3) Safety:
Video see-through HMDs are essentially modified closed-view HMDs. If the power is cut off, the user is effectively blind. This is a safety concern in some applications. In contrast, when power is removed from an optical seethrough HMD, the user still has a direct view of the real world. The HMD then becomes a pair of heavy sunglasses, but the user can still see.
4) No eye offset:
With video see-through, the user's view of the real world is provided by the video cameras. In essence, this puts his "eyes" where the video cameras are. In most configurations, the cameras are not located exactly where the user's eyes are, creating an offset between the cameras and the real eyes. The distance separating the cameras may also not be exactly the same as the user's interpupillary distance (IPD). This difference between camera locations and eye locations introduces displacements from what the user sees compared to what he expects to see. For example, if the cameras are above the user's eyes, he will see the world from a vantage point slightly taller than he is used to. Video see-through can avoid the eye offset problem through the use of mirrors to create another set of optical paths that mimic the paths directly into the user's eyes. Using those paths, the cameras will see what the user's eyes would normally see without the HMD. However, this adds complexity to the HMD design. Offset is generally not a difficult design problem for optical see-through displays. While the user's eye can rotate with respect to the position of the HMD, the resulting errors are tiny. Using the eye's center of rotation as the viewpoint in the computer graphics model should eliminate any need for eye tracking in an optical see-through HMD.
Video blending offers the following advantages over optical blending:
1) Flexibility in composition strategies:
A basic problem with optical seethrough is that the virtual objects do not completely obscure the real world objects, because the optical combiners allow light from both virtual and real sources. Building an optical see-through HMD that can selectively shut out the light from the real world is difficult. In a normal optical system, the objects are designed to be in focus at only one point in the optical path: the user's eye. Any filter that would selectively block out light must be placed in the optical path at a point where the image is in focus, which obviously cannot be the user's eye. Therefore, the optical system must have two places where the image is in focus: at the user's eye and the point of the hypothetical filter. This makes the optical design much more difficult and complex. No existing optical see-through HMD blocks incoming light in thisfashion. Thus, the virtual objects appear ghost-like and semi-transparent. This damages the illusion of reality because occlusion is one of the strongest depth cues. In contrast, video see-through is far more flexible about how it merges the real and virtual images. Since both the real and virtual are available in digital form, video seethrough compositors can, on a pixel-by-pixel basis, take the real, or the virtual, or some blend between the two to simulate transparency. Because of this flexibility, video see-through may ultimately produce more compelling environments than optical see-through approaches.
2) Wide field-of-view:
Distortions in optical systems are a function of the radial distance away from the optical axis. The further one looks away from the center of the view, the larger the distortions get. A digitized image taken through a distorted optical system can be undistorted by applying image processing techniques to unwrap the image, provided that the optical distortion is well characterized. This requires significant amounts of computation, but this constraint will be less important in the future as computers become faster. It is harder to build wide field-of-view displays with optical see-through techniques. Any distortions of the user's view of the real world must be corrected optically, rather than digitally, because the system has no digitized image of the real world to manipulate. Complex optics are expensive and add weight to the HMD. Wide field-of-view systems are an exception to the general trend of optical approaches being simpler and cheaper than video approaches.
3) Real and virtual view delays can be matched:
Video offers an approach for reducing or avoiding problems caused by temporal mismatches between the real and virtual images. Optical see-through HMDs offer an almost instantaneous view of the real world but a delayed view of the virtual. This temporal mismatch can cause problems. With video approaches, it is possible to delay the video of the real world to match the delay from the virtual image stream.
4) Additional registration strategies:
In optical see-through, the only information the system has about the user's head location comes from the head tracker. Video blending provides another source of information: the digitized image of the real scene. This digitized image means that video approaches can employ additional registration strategies unavailable to optical approaches.
Both optical and video technologies have their roles, and the choice of technology depends on the application requirements. Many of the mechanical assembly and repair prototypes use optical approaches, possibly because of the cost and safety issues. If successful, the equipment would have to be replicated in large numbers to equip workers on a factory floor. In contrast, most of the prototypes for medical applications use video approaches, probably for the flexibility in blending real and virtual and for the additional registration strategies offered.
3 Registration :
3.1 The registration problem
One of the most basic problems currently limiting Augmented Reality applications is the registration problem. The objects in the real and virtual worlds must be properly aligned with respect to each other, or the illusion that the two worlds coexist will be compromised. More seriously, many applications demand accurate registration. For example, recall the needle biopsy application. If the virtual object is not where the real tumor is, the surgeon will miss the tumor and the biopsy will fail. Without accurate registration, Augmented Reality will not be accepted in many applications. For example, a user wearing a closed-view HMD might hold up her real hand and see a virtual hand. This virtual hand should be displayed exactly where she would see her real hand, if she were not wearing an HMD. But if the virtual hand is wrong by five millimeters, she may not detect that unless actively looking for such errors. The same error is much more obvious in a see-through HMD, where the conflict is visual-visual. Furthermore, a phenomenon known as visual capture makes it even more difficult to detect such registration errors. Visual capture is the tendency of the brain to believe what it sees rather than what it feels, hears, etc. That is, visual information tends to override all other senses. When watching a television program, a viewer believes the sounds come from the mouths of the actors on the screen, even though they actually come from a speaker in the TV. Ventriloquism works because of visual capture. Similarly, a user might believe that her hand is where the virtual hand is drawn, rather than where her real hand actually is, because of visual capture. This effect increases the amount of registration error users can tolerate in Virtual Environment systems. If the errors are systematic, users might even be able to adapt to the new environment, given a long exposure time of several hours or days. Augmented Reality demands much more accurate registration than Virtual Environments. Imagine the same scenario of a user holding up her hand, but this time wearing a see-through HMD. Registration errors now result in visual-visual conflicts between the images of the virtual and real hands. Such conflicts are easy to detect because of the resolution of the human eye and the sensitivity of the human visual system to differences. Registration of real and virtual objects is not limited to AR. Special-effects artists seamlessly integrate computer-generated 3-D objects with live actors in film and video. The difference lies in the amount of control available. With film, a director can carefully plan each shot, and artists can spend hours per frame, adjusting each by hand if necessary, to achieve perfect registration. As an interactive medium, AR is far more difficult to work with. The AR system cannot control the motions of the HMD wearer. The user looks where she wants, and the system must respond within tens of milliseconds. Registration errors are difficult to adequately control because of the high accuracy requirements and the numerous sources of error. These sources of error can be divided into two types: static and dynamic. Static errors are the ones that cause registration errors even when the user's viewpoint and the objects in the environment remain completely still. Dynamic errors are the ones that have no effect until either the viewpoint or the objects begin moving. For current HMD-based systems, dynamic errors are by far the largest contributors to registration errors, but static errors cannot be ignored either. The next two sections discuss static and dynamic errors and what has been done to reduce them.
3.1.1 Static errors
The three main sources of static errors are:
3.1.1.1 Distortion in the optics:
Optical distortions exist in most camera and lens systems, both in the cameras that record the real environment and in the optics used for the display. Because distortions are usually a function of the radial distance away from the optical axis, wide field-of-view displays can be especially vulnerable to this error. Near the center of the field-of-view, images are relatively undistorted, but far away from the center, image distortion can be large. For example, straight lines may appear curved. In a see-through HMD with narrow field-of-view displays, the optical combiners add virtually no distortion, so the user's view of the real world is not warped. However, the optics used to focus and magnify the graphic images from the display monitors can introduce distortion. This mapping of distorted virtual images on top of an undistorted view of the real world causes static registration errors. The cameras and displays may also have nonlinear distortions that cause errors. Optical distortions are usually systematic errors, so they can be mapped and compensated. This mapping may not be trivial, but it is often possible. For example,
describes the distortion of one commonly-used set of HMD optics. The distortions might be compensated by additional optics. An alternate approach is to do the compensation digitally. This can be done by image warping techniques, both on the digitized video and the graphic images. Typically, this involves predistorting the images so that they will appear undistorted after being displayed. Digital compensation methods can be computationally expensive, often requiring special hardware to accomplish in real time.
3.1.1.2 Errors in the tracking system:
Errors in the reported outputs from the tracking and sensing systems are often the most serious type of static registration errors. These distortions are not easy to measure and eliminate, because that requires another "3-D ruler" that is more accurate than the tracker being tested. These errors are often non-systematic and difficult to fully characterize. Almost all commercially available tracking systems are not accurate enough to satisfy the requirements of AR systems.
3.1.1.3 Mechanical misalignments:
Mechanical misalignments are discrepancies between the model or specification of the hardware and the actual physical properties of the real system. For example, the combiners, optics, and monitors in an optical see-through HMD may not be at the expected distances or orientations with respect to each other. If the frame is not sufficiently rigid, the various component parts may
change their relative positions as the user moves around, causing errors. Mechanical misalignments can cause subtle changes in the position and orientation of the projected virtual images that are difficult to compensate. While some alignment errors can be calibrated, for many others it may be more effective to "build it right" initially.
3.1.2 Dynamic errors :
Dynamic errors occur because of system delays, or lags. The end-to-end system delay is defined as the time difference between the moment that the tracking system measures the position and orientation of the viewpoint to the moment when the generated images corresponding to that position and orientation appear in the displays. These delays exist because each component in an Augmented Reality system requires some time to do its job. The delays in the tracking subsystem, the communication delays, the time it takes the scene generator to draw the appropriate images in the frame buffers, and the scanout time from the frame buffer to the
displays all contribute to end-to-end lag. End-to-end delays of 100 ms are fairly typical on existing systems. Simpler systems can have less delay, but other systems have more. Delays of 250 ms or more can exist on slow, heavily loaded, or networked systems. End-to-end system delays cause registration errors only when motion occurs. Assume that the viewpoint and all objects remain still. Then the lag does not cause registration errors. No matter how long the delay is, the images generated are appropriate, since nothing has moved since the time the tracker measurement was taken. Compare this to the case with motion. For example, assume a user wears a see-through HMD and moves her head. The tracker measures the head at an initial time t. The images corresponding to time t will not appear until some future time t2, because of the end-to-end system delays. During this delay, the user's head remains in motion, so when the images computed at time t finally appear, the user sees them at a different location than the one they were computed for. Thus, the images are incorrect for the time they are actually viewed. To the user, the virtual objects appear to "swim around" and "lag behind" the real objects. This was graphically System delays seriously hurt the illusion that the real and virtual worlds coexist because they cause large registration errors. With a typical end-to-end lag of 100 ms and a moderate head rotation rate of 50 degrees per second, the angular dynamic error is 5 degrees. At a 68 cm arm length, this results in registration errors of almost 60 mm. System delay is the largest single source of registration error in existing AR systems, outweighing all others combined .
3.1.2.1 Reduce system lag:
The most direct approach is simply to reduce, or ideally eliminate, the system delays. If there are no delays, there are no dynamic errors. Unfortunately, modern scene generators are usually built for throughput, not minimal latency. It is sometimes possible to reconfigure the software to sacrifice throughput to minimize latency. For example, the SLATS system completes rendering a pair of interlaced NTSC images in one field time (16.67 ms) on Pixel-Planes. Being careful about synchronizing pipeline tasks can also reduce the end-to-end lag. System delays are not likely to completely disappear anytime soon. Some believe that the current course of technological development will automatically solve this problem. Unfortunately, it is difficult to reduce system delays to the point where they are no longer an issue. Recall that registration errors must be kept to a small fraction of a degree. At the moderate head rotation rate of 50 degrees per second, system lag must be 10 ms or less to keep angular errors below 0.5 degrees. Just scanning out a frame buffer to a display at 60 Hz requires 16.67 ms. It might be possible to build an HMD system with less than 10 ms of lag, but the drastic cut in throughput and the expense required to construct the system would make alternate solutions attractive. Minimizing system delay is important, but reducing delay to the point where it is no longer a source of registration error is not currently practical.
3.1.2.2 Match temporal streams:
In video-based AR systems, the video camera and digitization hardware impose inherent delays on the user's view of the real world. This is potentially a blessing when reducing dynamic errors, because it allows the temporal streams of the real and virtual images to be matched. Additional delay is added to the video from the real world to match the scene generator delays in generating the virtual images. This additional delay to the video stream will probably not remain constant, since the scene generator delay will vary with the complexity of the rendered scene. Therefore, the system must dynamically synchronize the two streams. Note that while this reduces conflicts between the real and virtual, now both the real and virtual objects are delayed in time.
3.1.2.3 Predict:
The last method is to predict the future viewpoint and object locations. If the future locations are known, the scene can be rendered with these future locations, rather than the measured locations. Then when the scene finally appears, the viewpoints and objects have moved to the predicted locations, and the graphic images are correct at the time they are viewed. For short system delays
(under ~80 ms), prediction has been shown to reduce dynamic errors by up to an order of magnitude. Accurate predictions require a system built for realtime measurements and computation. Using inertial sensors makes predictions more accurate by a factor of 2-3. Predictors have been developed for a few AR systems, but the majority were implemented and evaluated with VE systems. More work needs to be done on ways of comparing the theoretical performance of various predictors and in developing prediction models that better match actual head motion .
3.2 Current status :
The registration problem is far from solved. Many systems assume a static viewpoint, static objects, or even both. Even if the viewpoint or objects are allowed to move, they are often restricted in how far they can travel. Registration is shown under controlled circumstances, often with only a small number of real-world objects, or where the objects are already well-known to the system. For example, registration may only work on one object marked with fiducials, and not on any other objects in the scene. Much more work needs to be done to increase the domains in which registration is robust. Duplicating registration methods remains a nontrivial task, due to both the complexity of the methods and the additional hardware required. If simple yet effective solutions could be developed, that would speed the acceptance of AR systems.
4 Sensing :
Accurate registration and positioning of virtual objects in the real environment requires accurate tracking of the user's head and sensing the locations of other objects in the environment. The biggest single obstacle to building effective Augmented Reality systems is the requirement of accurate, long-range sensors and trackers that report the locations of the user and the surrounding objects in the environment. Commercial trackers are aimed at the needs of Virtual Environments and motion capture applications. Compared to those two applications, Augmented Reality has much stricter accuracy requirements and demands larger working volumes. No tracker currently provides high accuracy at long ranges in real time. More work needs to be done to develop sensors and trackers that can meet these stringent requirements. Specifically, AR demands more from trackers and sensors in three areas :
¢ Greater input variety and bandwidth
¢ Higher accuracy
¢ Longer range
4.1 Input variety and bandwidth :
VE systems are primarily built to handle output bandwidth: the images displayed, sounds generated, etc. The input bandwidth is tiny: the locations of the user's head and hands, the outputs from the buttons and other control devices, etc. AR systems, however, will need a greater variety of input sensors and much more input bandwidth. There are a greater variety of possible input sensors than output displays. Outputs are limited to the five human senses. Inputs can come
from anything a sensor can detect. It is speculated that Augmented Reality may be useful in any application that requires displaying information not directly available or detectable by human senses by making that information visible (or audible, touchable, etc.). Other future applications
might use sensors to extend the user's visual range into infrared or ultraviolet frequencies, and remote sensors would let users view objects hidden by walls or hills. Conceptually, anything not detectable by human senses but detectable by machines might be transduced into something that a user can sense in an AR system. Range data is a particular input that is vital for many AR applications. The AR system knows the distance to the virtual objects, because that model is built into the system. But the AR system may not know where all the real objects are in the
environment. The system might assume that the entire environment is measured at the beginning and remains static thereafter. However, some useful applications will require a dynamic environment, in which real objects move, so the objects must be tracked in real time. Thus, a significant modeling effort may be required and should be taken into consideration when building an AR application.
4.2 High accuracy :
The accuracy requirements for the trackers and sensors are driven by the accuracies needed for visual registration, as described in Section 3. For many approaches, the registration is only as accurate as the tracker. Therefore, the AR system needs trackers that are accurate to around a millimeter and a tiny fraction of a degree, across the entire working range of the tracker. Few trackers can meet this specification, and every technology has weaknesses. Some mechanical trackers are accurate enough, although they tether the user to a limited working volume. Magnetic trackers are vulnerable to distortion by metal in the environment, which exists in many desired AR application environments. Ultrasonic trackers suffer from noise and are difficult to make accurate at long ranges because of variations in the ambient temperature. Optical technologies have distortion and calibration problems. Inertial trackers drift with time. Of the
individual technologies, optical technologies show the most promise due to trends toward high-resolution digital cameras, real-time photogrammetric techniques, and structured light sources that result in more signal strength at long distances. Future tracking systems that can meet the stringent requirements of AR will probably be hybrid systems, such as a combination of inertial and optical technologies. Using multiple technologies opens the possibility of covering for each technology's weaknesses by combining their strengths. Attempts have been made to calibrate the distortions in commonly-used magnetic tracking systems. These have succeeded at removing much of the gross error from the tracker at long ranges, but not to the level required by AR systems. For example, mean errors at long ranges can be reduced from several inches to around one inch. The requirements for registering other sensor modes are not nearly as stringent. For example, the human auditory system is not very good at localizing deep bass sounds, which is why subwoofer placement is not critical in a home theater system.
4.3 Long range :
Few trackers are built for accuracy at long ranges, since most VE applications do not require long ranges. Motion capture applications track an actor's body parts to control a computer-animated character or for the analysis of an actor's movements. This is fine for position recovery, but not for orientation. Orientation recovery is based upon the computed positions. Even tiny errors in those positions can cause orientation errors of a few degrees, which is too large for AR systems. A scalable system is one that can be expanded to cover any desired range, simply by adding more modular components to the system. This is done by building a cellular tracking system, where only nearby sources and sensors are used to track a user. As the user walks around, the set of sources and sensors changes, thus achieving large working volumes while avoiding long distances between the current working set of sources and sensors. While scalable trackers can be effective, they are complex and by their very nature have many components,
making them relatively expensive to construct. The Global Positioning System (GPS) is used to track the locations of vehicles almost anywhere on the planet. It might be useful as one part of a long range tracker for AR systems. However, by itself it will not be sufficient. The best reported
accuracy is approximately one centimeter, assuming that many measurements are integrated (so that accuracy is not generated in real time), when GPS is run in differential mode. That is not sufficiently accurate to recover orientation from a set of positions on a user. Tracking an AR system outdoors in real time with the required accuracy has not been demonstrated and remains an open problem.
5 Comparison against virtual environments :
The overall requirements of AR can be summarized by comparing them against the requirements for Virtual Environments, for the three basic subsystems that they require.
5.1 Scene generator:
Rendering is not currently one of the major problems in AR. VE systems have much higher requirements for realistic images because they completely replace the real world with the virtual environment. In AR, the virtual images only supplement the real world. Therefore, fewer virtual objects need to be drawn, and they do not necessarily have to be realistically rendered in order to serve the purposes of the application. For example, in the annotation applications, text and 3-D wireframe drawings might suffice. Ideally, photorealistic graphic objects would be seamlessly merged with the real environment, but more basic problems have to be solved first.
5.2 Display device:
The display devices used in AR may have less stringent requirements than VE systems demand, again because AR does not replace the real world. For example, monochrome displays may be adequate for some AR applications, while virtually all VE systems today use full color. Optical see-through HMDs with a small field-of-view may be satisfactory because the user can still see the real world with his peripheral vision; the see-through HMD does not shut off the
user's normal field-of-view. Furthermore, the resolution of the monitor in an optical see-through HMD might be lower than what a user would tolerate in a VE application, since the optical see-through HMD does not reduce the resolution of the real environment.
5.3 Tracking and sensing:
While in the previous two cases AR had lower requirements than VE, that is not the case for tracking and sensing. In this area, the requirements for AR are much stricter than those for VE systems since it is done in real time.
6 MOTIVATION AND APPLICATIONS :
Why is combining real andvirtual objects in 3-D useful? Augmented Reality enhances a user's perception of and interaction with the real world. The virtual objects display information that the user cannot directly detect with his own senses. It can be otherwise termed as Intelligence Amplification. At least five classes of potential AR applications have been explored: medical visualization, maintenance and repair, annotation, entertainment and military aircraft navigation and targeting. The next section describes work that has been done in each area. While these do not cover every potential application area of this technology, they do cover the areas explored so far.
6.1 Medical
Doctors could use Augmented Reality as a visualization and training aid for surgery. It may be possible to collect 3-D datasets of a patient in real time, using noninvasive sensors like Magnetic Resonance Imaging (MRI), Computed Tomography scans (CT), or ultrasound imaging. These datasets could then be rendered and combined in real time with a view of the real patient. AR technology could provide an internal view without the need for larger incisions. AR might also be helpful for general medical visualization tasks in the surgical room. The information from the non-invasive sensors would be directly displayed on the patient, showing exactly where to perform the operation. AR might also be useful for training purposes. Virtual instructions could remind a novice surgeon of the required steps, without the need to look away from a patient to consult a manual.
6.2 Manufacturing and repair
Another category of Augmented Reality applications is the assembly, maintenance, and repair of complex machinery. Instructions might be easier to understand if they were available, not as manuals with text and pictures, but rather as 3-D drawings superimposed upon the actual equipment, showing step-by-step the tasks that need to be done and how to do them. These superimposed 3-D drawings can be animated, making the directions even more explicit.
6.3 Annotation and visualization
AR could be used to annotate objects and environments with public or private information. Applications using public information assume the availability of public databases to draw upon. For example, a hand-held display could provide information about the contents of library shelves as the user walks around the library A user can point at parts of an engine model and the AR system displays the name of the part that is being pointed at .AR might give architects "X-ray vision" inside a building, showing where the pipes, electric lines, and structural supports are inside the walls. Similarly, virtual lines and objects could aid navigation and scene understanding during poor visibility conditions, such as underwater or in fog.
6.4 Entertainment
In the entertainment field AR has still bigger achievements . The actors stand in front of a large blue screen, while a computer-controlled motion camera records the scene. Since the camera's location is tracked, and the actor's motions are scripted, it is possible to digitally composite the actor into a 3-D virtual background. The entertainment industry sees this as a way to reduce production costs: creating and storing sets virtually is potentially cheaper than constantly building new physical sets from scratch. It can be further enhanced by populating the environment with intelligent virtual creatures that respond to user actions .
6.5 Military aircraft
For many years, military aircraft and helicopters have used Head-Up Displays (HUDs) and Helmet-Mounted Sights (HMS) to superimpose vector graphics upon the pilot's view of the real world. Besides providing basic navigation and flight information, these graphics are sometimes registered with targets in the environment, providing a way to aim the aircraft's weapons. Future generations of combat aircraft will be developed with an HMD built into the pilot's helmet.
7. Future directions
This section identifies areas and approaches that require further research to produce improved AR systems.
7.1 Hybrid approaches:
Future tracking systems may be hybrids, because combining approaches can cover weaknesses. The same may be true for other problems in AR. For example, current registration strategies generally focus on a single strategy. Future systems may be more robust if several techniques are combined. An example is combining vision-based techniques with prediction. If the fiducials are not available, the system switches to open-loop prediction to reduce the registration errors, rather than breaking down completely. The predicted viewpoints in turn produce a more accurate initial location estimate for the vision-based techniques.
7.2 Real-time systems and time-critical computing:
Many VE systems are not truly run in real time. Instead, it is common to build the system, often on UNIX, and then see how fast it runs. This may be sufficient for some VE applications. Since everything is virtual, all the objects are automatically synchronized with each other. AR is a different story. Now the virtual and real must be synchronized, and the real world "runs" in real time. Therefore, effective AR systems must be built with real time performance in mind. Accurate timestamps must be available. Operating systems must not arbitrarily swap out the AR software process at any time, for arbitrary durations. Systems must be built to guarantee completion within specified time budgets, rather than just "running as quickly as possible." These are characteristics of flight simulators and a few VE systems. Constructing and debugging real-time systems is often painful and difficult, but the requirements for AR demand real-time performance.
7.3 Perceptual and psychophysical studies:
Augmented Reality is an area ripe for psychophysical studies. How much lag can a user detect? How much registration error is detectable when the head is moving? Besides questions on perception, psychological experiments that explore performance issues are also needed. How much does head-motion prediction improve user performance on a specific task? How much registration error is tolerable for a specific application before performance on that task degrades substantially? Is the allowable error larger while the user moves her head versus when she stands still? Furthermore, not much is known about potential optical illusions caused by errors or conflicts in the simultaneous display of real and virtual objects. Few experiments in this area have been performed. Jannick Rolland, Frank Biocca and their students conducted a study of the effect caused by eye displacements in video see-through HMDs. They found that users partially adapted to the eye displacement, but they also had negative aftereffects after removing the HMD.
7.4 Portability:
AR requires making the equipment self-contained and portable. Existing tracking technology is not capable of tracking a user outdoors at the required accuracy.
7.5 Multimodal displays:
Almost all work in AR has focused on the visual sense: virtual graphic objects and overlays. But augmentation might apply to all other senses as well. In particular, adding and removing 3-D sound is a capability that could be useful in some AR applications.
7.6 Social and political issues:
Technological issues are not the only ones that need to be considered when building a real application. There are also social and political dimensions when getting new technologies into the hands of real users. Sometimes, perception is what counts, even if the technological reality is different. For example, if workers perceive lasers to be a health risk, they may refuse to use a system with lasers in the display or in the trackers, even if those lasers are eye safe.
Ergonomics and ease of use are paramount considerations. Whether AR is truly a cost-effective solution in its proposed applications has yet to be determined. Another important factor is whether or not the technology is perceived as a threat to jobs, as a replacement for workers, especially with many corporations undergoing recent layoffs. AR may do well in this regard, because it is intended as a tool to make the user's job easier, rather than something that completely replaces the human worker. Although technology transfer is not normally a subject of academic papers, it is a real problem. Social and political concerns should not be ignored during attempts to move AR out of the research lab and into the hands of real users.
Conclusion
Augmented Reality is far behind Virtual Environments in maturity. No commercial vendor currently sells an HMD-based Augmented Reality system. Today AR systems are primarily found in academic and industrial research laboratories. The first deployed HMD-based AR systems will probably be in the application of aircraft manufacturing. Both Boeing and McDonnell Douglas are exploring this technology. The former uses optical approaches, while the latter is pursuing video approaches. Annotation and visualization applications in restricted, limited-range environments are deployable today. Applications in medical visualization will take longer. Prototype visualization aids have been used on an experimental basis, but the stringent registration requirements and ramifications of mistakes will postpone common usage for many years. AR will probably be used for medical training before it is commonly used in surgery. The next generation of combat aircraft will have Helmet-Mounted Sights with graphics registered to targets in the environment. Augmented Reality is a relatively new field, where most of the research efforts have occurred in the past ten years. One area where a breakthrough is required is tracking an HMD outdoors at the accuracy required by AR. If this is accomplished, several interesting applications will become possible. Two examples are: navigation maps and visualization of past and future environments. The first application is a navigation aid to people walking outdoors. An AR system makes navigation easier by performing the association step automatically. If the user's position and orientation are known, and the AR system has access to a digital map of the area, then the AR system can draw the map in 3-D directly upon the user's view. The second application is visualization of locations and events as they were in the past or as they will be after future changes are performed.
References
[1] Teleoperators and Virtual Environments , 355-385 A Survey of Augmented Reality Ronald T. Azuma Hughes Research Laboratories 3011 Malibu Canyon Road, MS RL96 Malibu, CA 90265 azuma[at]isl.hrl.hac.com
[2] Ronald Azuma HRL Laboratories, Yohan Baillot NRL Virtual Reality Lab/ITT Advanced Engineering, Reinhold Behringer Rockwell Scienti.c Steven Feiner Columbia University
[3] Simon Julier NRL Virtual Reality Lab/ITT Advanced Engineering, Blair MacIntyre Georgia Institute of Technology, Recent Advances in Augmented Reality
[4] James R Vallino Interactive Augmented Reality Submitted in partial Fulfillment of the Requirements for the Degree Doctor of philosophy.
http://se.rit.edu/~jrv/research/ar/introduction.html
CONTENTS
1. Introduction¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦...1
2. Design¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦...2
¢ Optical see-through HMD
¢ Video see-through HMD
¢ Monitor based AR
3. Registration problem¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦.8
¢ Static problem
¢ Dynamic problem
4. Sensing problem¦..¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦14
¢ Greater input variety and bandwidth
¢ Higher accuracy
¢ Long range
5. Advantage of Augmented Reality over Virtual Environment...¦¦.17
6. Applications¦.¦¦¦¦¦¦¦...¦¦¦¦¦¦¦¦¦¦¦¦...18
¢ Medical
¢ Maintenance and repair
¢ Visualization
¢ Entertainment
¢ Military
7. Future areas of work and research¦¦¦¦¦¦¦¦¦¦¦¦¦.19
