Computer graphics (2nd ed. in C): principles and practice
Computer graphics (2nd ed. in C): principles and practice
Intelligent scissors for image composition
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Digital Image Processing
ACM SIGGRAPH 2004 Papers
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2004 Papers
An Iterative Optimization Approach for Unified Image Segmentation and Matting
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
3D Object Transfer Between Non-Overlapping Videos
VR '06 Proceedings of the IEEE conference on Virtual Reality
A Closed Form Solution to Natural Image Matting
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
The Visual Computer: International Journal of Computer Graphics
An Iterative Bayesian Approach for Digital Matting
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
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Given two video sequences of different scenes, the problem of seamlessly transferring a 3D moving object from one sequence to the other is a complex task. In this paper, we present a method to extract the alpha matte of a moving 3D object from a source video, and then correctly augment the object into another target video. Our framework builds upon techniques in natural image and video matting, composition, and image-based rendering. Natural image matting is usually composed of: foreground and background color estimating and alpha estimating. Our proposed technique uses local and global color information to estimate the accurate alpha values and extends this approach to extract a moving object from a video sequence. From a video sequence consisting of a single moving object over a stationary background, we combine motion statistics, color and contrast cues to extract a foreground (moving) object efficiently with no interaction from the user. During the process of compositing the moving object (from source video) on the target video, our approach composes the object accurately and ensures that the implanted moving object does not collide with other objects (static or moving) already present. An intuitive user interface (UI) tool is designed and implemented to provide flexible control and facilitate 3D composition for the user.