Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Visual Modeling with a Hand-Held Camera
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
Particle Video: Long-Range Motion Estimation using Point Trajectories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Object segmentation by long term analysis of point trajectories
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Efficient non-consecutive feature tracking for structure-from-motion
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Robust Bilayer Segmentation and Motion/Depth Estimation with a Handheld Camera
IEEE Transactions on Pattern Analysis and Machine Intelligence
SlimCuts: graphcuts for high resolution images using graph reduction
EMMCVPR'11 Proceedings of the 8th international conference on Energy minimization methods in computer vision and pattern recognition
Feature trajectory retrieval with application to accurate structure and motion recovery
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
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Visual effect creation as used in movie production often require structure and motion recovery and video segmentation. Both techniques are essential to integrate virtual objects between scene elements. In this paper, a new method for video segmentation is presented. It incorporates 3D scene information from the structure and motion recovery. By connecting and evaluating discontinued feature tracks, occlusion and reappearance information is obtained during sequential camera and scene estimation. The foreground is characterized as image regions which temporarily occlude the rigid scene structure. The scene structure is represented by reconstructed object points. Their projections onto the camera images provide the cues for regions classified as foreground or background. The knowledge of occluded parts of a connected feature track is used to feed the object segmentation which crops the foreground image regions automatically. Two applications are presented: the occlusion of integrated virtual objects and the blurred background effect. Several demonstrations on official and self-made data show very realistic results in augmented reality.