International Journal of Computer Vision
Interactive segmentation with Intelligent Scissors
Graphical Models and Image Processing
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
3D reconstruction using labeled image regions
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
An Efficient Solution to the Five-Point Relative Pose Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
iModel: interactive co-segmentation for object of interest 3d modeling
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part II
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In this paper we introduce a novel method for automatic propagation of foreground objects in image sequences. Our method is based on a combination of the mean-shift operator with the well known intelligent scissors technique. It is effective due to the fact that the images are captured with high overlap, resulting in highly redundant scene information. The algorithm requires an initial segmentation of one image of the sequence as an input. In each consecutive image the segmentation of the previous image is taken as an initialization and the propagation procedure proceeds along four major steps. Each step refines the segmentation of the foreground object and the algorithm converges until all images of the sequence are processed. We demonstrate the effectiveness of our approach on several datasets.