Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object-Based Spatial Segmentation of Video Guided by Depth and Motion Information
WMVC '07 Proceedings of the IEEE Workshop on Motion and Video Computing
Multi-view video based multiple objects segmentation using graph cut and spatiotemporal projections
Journal of Visual Communication and Image Representation
Virtual view synthesis using multi-view video sequences
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Background Removal of Multiview Images by Learning Shape Priors
IEEE Transactions on Image Processing
Efficient Prediction Structures for Multiview Video Coding
IEEE Transactions on Circuits and Systems for Video Technology
Introduction to the Special Section on Multiview Video Coding
IEEE Transactions on Circuits and Systems for Video Technology
ViBe: A Universal Background Subtraction Algorithm for Video Sequences
IEEE Transactions on Image Processing
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A novel scheme for multi-view segmentation and tracking is proposed aiming to acquire perceptually consistent results for object-based coding. Firstly, a classic image segmentation technique is employed to perform initial segmentation to divide the whole image into spatially homogeneous regions. Secondly, the motion information is extracted based on frame differences and the disparity information is derived by employing a classic disparity estimation technique. Thirdly, a novel scheme is proposed to perform merging of the initial segmentation results based on both motion and disparity information to remove over-segmented regions and extract perceptually consistent semantic objects. Finally, a contour-based tracking algorithm is proposed to implement accurate and robust object tracking along both temporal and view directions. Experiments are conducted and the results demonstrate that the proposed scheme is effective and, compared with the existing technique, it can acquire more perceptually consistent results.