Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation
International Journal of Computer Vision
Dynamic Texture Detection Based on Motion Analysis
International Journal of Computer Vision
Detecting regions of dynamic texture
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
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There are increasing demands for ultralow bit-rate video image transmission. We present a new formulation of moving object segmentation and motion estimation to quantify the potential gain in using object-oriented motion compensation in image sequence coding. Motivated by real-valued parameter estimation required in object-oriented motion-compensated video source coding, a framework motivated by Rissanen's (1983) minimum description length (MDL) principle is proposed to more tightly couple motion estimation and object segmentation algorithms to the overall objective of minimizing source bit rate. A new objective function is constructed, and a suboptimal procedure to segment and estimate moving objects in a scene is proposed. Each object is represented by chain-coded block boundaries, affine motion parameters, and motion-compensated prediction error. A number of experimental comparisons between block- and object-oriented coding schemes suggests a significant potential coding gain using object-oriented motion-compensated coding