The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
Cosegmentation of Image Pairs by Histogram Matching - Incorporating a Global Constraint into MRFs
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Fast Global Minimization of the Active Contour/Snake Model
Journal of Mathematical Imaging and Vision
Automatic 3D object segmentation in multiple views using volumetric graph-cuts
Image and Vision Computing
User-friendly interactive image segmentation through unified combinatorial user inputs
IEEE Transactions on Image Processing
CuteChat: a lightweight tele-immersive video chat system
MM '11 Proceedings of the 19th ACM international conference on Multimedia
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
From co-saliency to co-segmentation: An efficient and fully unsupervised energy minimization model
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Scale invariant cosegmentation for image groups
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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Despite the great progress on interactive image segmentation, image co-segmentation, 2D and 3D segmentation, there is still no workable solution to the problem: given a set of calibrated or un-calibrated multi-view images (say, more than 40 images), by interactively cutting 3~4 images, can the foreground object of the rest images be quickly cutout automatically and accurately? In this paper, we propose a non-trivial engineering solution to this problem. Our basic idea is to integrate 3D segmentation with 2D segmentation so as to combine their advantages. Our proposed system iteratively performs 2D and 3D segmentation, where the 3D segmentation results are used to initialize 2D segmentation and ensure the silhouette consistency among different views and the 2D segmentation results are used to provide more accurate cues for the 3D segmentation. The experimental results show that the proposed system is able to generate highly accurate segmentation results, even for some challenging real-world multi-view image sequences, with a small amount of user input.