Current techniques for generating animated scenes involve either videos (whose resolution is limited) or a single image (which requires a significant amount of user interaction). In this project, we describe a system that allows the user to quickly and easily produce a compelling-looking animation from a small collection of high resolution stills. Our system has two unique features. First, it applies an automatic partial temporal order recovery algorithm to the stills in order to approximate the original scene dynamics. The output sequence is subsequently extracted using a second-order Markov Chain model. Second, a region with large motion variation can be automatically decomposed into semiautonomous regions such that their temporal orderings are softly constrained. This is to ensure motion smoothness throughout the original region. The final animation is obtained by frame interpolation and feathering. Our system also provides a simple-to-use interface to help the user to fine-tune the motion of the animated scene. Using our system, an animated scene can be generated in minutes. We show results for a variety of scenes.

HIGH RESOLUTION ANIMATED SCENES FROM STILLS

Abstract
Current techniques for generating animated scenes involve either videos (whose resolution is limited) or a single image (which requires a significant amount of user interaction). In this project, we describe a system that allows the user to quickly and easily produce a compelling-looking animation from a small collection of high resolution stills. Our system has two unique features. First, it applies an automatic partial temporal order recovery algorithm to the stills in order to approximate the original scene dynamics. The output sequence is subsequently extracted using a second-order Markov Chain model. Second, a region with large motion variation can be automatically decomposed into semiautonomous regions such that their temporal orderings are softly constrained. This is to ensure motion smoothness throughout the original region. The final animation is obtained by frame interpolation and feathering. Our system also provides a simple-to-use interface to help the user to fine-tune the motion of the animated scene. Using our system, an animated scene can be generated in minutes. We show results for a variety of scenes.

Existing System:
 The existing system has garnered a lot of attention is video texture, which reuses frames to generate a seamless video of arbitrary length.
 Video textures work by figuring out frames in the original video that are temporally apart but visually close enough, so that jumping between such frames appears seamless.
 This work was extended to produce video sprites, which permit high-level control of moving objects in the synthesized video. Unlike videos, the ordering of our input stills may not be 1D. Thus, we can only use partial orders as reference dynamics.
Drawbacks:
Fully manual in traction.
Each and every process should be done by manually.
Ex. Flash player.
Proposed System:
 The proposed system is a scene animation system that can easily generate a video or video texture from a small collection of stills.
 Our system first builds a graph that links similar images. It then recovers partial temporal orders among the input images and uses a second-order Markov Chain model to generate an image sequence of the video or video texture. Our system is designed to allow the user to easily fine-tune the animation.
Merits:
¢ Reduce the user interaction
¢ Time complexity
¢ User can give only collections of jpeg images. Based on the images we will get movie file for 1 or more than 2 minutes.
¢ Simply conversion of Jpeg to Mpeg/AVI

Modules
The modules of the system are
¢ Preprocessing
¢ Building a Graph
¢ Motion creation
¢ Scene making
¢ Manual editing
Module Description

Preprocessing
Color Enhancement, Improve the image quality, Size corrections, and noise removal.
Algorithm: Morphological Filters, Automatic Color Enhancement technique [ACE]
Input:
Collections of related stills/ images.
Output:
Quality stills.

1. Color Enhancement - improve the Contrast & Brightness, Improve the quality based on the saturation Adjustment
In first module we first set same pixels for all images. Bcoz it will compare the images for find the difference b/w the same objects.
After that we will set the same brightness and contrast for all images. Bcoz based on the brightness and contrast the output will be show with same bright n contrast.
Morphology - Removing Noise
If we improve the quality of an image it will affect the original pixels. Some pixels may be affect that time noise will occur. Her we are using noise removal process.
2. Convolution and correlation - Smoothing, Sharpness

Building a Graph
¢ Image comparison.
¢ Algorithm: Floyd™s algorithm, Partial Temporal order recovery algorithm.
¢ Input: Unordered stills
¢ Output: Ordered, distance computed.
1. Edge Detection - Detect the object Edges
Using canny edge detection process we will detect the edges of the images. Here we will show layout of the objects.
2. Difference calculation “ Calculate the Difference b/w the two images based on the pixel difference.
3. Make a Graph “ Make a Graph based on difference

Motion Creation
¢ Based on distance low resolution optical flow is created between two adjacent images. Sampling the graph
¢ Algorithm: Statistical approach, Markov Chain Model.
¢ Fine tuning
¢ Input: Stills with no tuning
¢ Output: Fine tuned video texture.

Scene Making
¢ Video texture creations
¢ AVI File conversion based on time sequence
¢ Frame interpolation
¢ Algorithm :AVI format
¢ Input: Stills
¢ Output: Video or video texture.

Manual Editing
¢ Manual reorders
¢ Editing the image
¢ Motion smoothness
¢ Measuring motion irregularity.


Software Requirements

Operating system: Windows XP Professional/Vista
Front End : Microsoft Visual Studio .Net 2008
Coding Language : Visual C# .Net

Hardware Requirements

System : Pentium IV
Hard disk : 40 GB
RAM : 1 GB

I want system flow diagram for this topic...........

I need system flow diagram for this topics

Hi,
If you can provide me with source code for this project i will be happy to pay what you want. If you agree for this you can contact me on this ID
chandoo1nu[at]yahoo.co.in

Sorry, the project code is unavailable. The papers of the topic are available. It may be of some help to you.

High Resolution Animated Scenes from Stills
A single picture conveys a lot of information about the scene, but it rarely conveys the scene’s true dynamic nature. A video can do both but the resolution of the video is limited. A resolution of 720x480 at 30 fps is the capability of the standard camcorders. Modern digital cameras have a resolution of around 16 Megapixels producing extremely high resolution images. Video textures can be a method for producing arbitrarily long video sequences with the help of high resolution camcorders. compelling-looking animated scenes can be generated by the system developed by Chuang et al but it has some major drawbacks and also a lot of manual input is required.
In the proposed system , a small collection of high resolution stills that undersamples the original scene is input to the system. This system thus represents the the dynamic nature of the scene and also has high resolution. the animated scene generation process has to be done with considerable easiness and must be suited for real world application. a video or video texture can be generated in the system from 10 to 20 stills which are captured in the interval of 1 to 2 minutes. a graph that links similar images is first built by the system. Then partial temporal orders among the input images are developed and a a second-order Markov Chain model is sued to generate the final video sequence.

Get the research paper at:
http://research.microsoftpubs/78063/2007...Stills.pdf
http://freepatentsonliney2008/0001950.html
http://siliconindiaaiepic/project/high_resolution_animated_scenes_from_stills-pid=3653.html