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Object Oriented Video Segmentation Using Converged Mean Shift Algorithm

K. Mahesh, Dr. K. Kuppusamy, P. Pandi Selvi

Abstract


The survey describes an approach for object–oriented video segmentation based on motion coherence. Using a tracking process, 2-D motion patterns are identified with an ensemble clustering approach. Particles are clustered to obtain a pixel-wise segmentation in space and time domains. The mean-shift algorithm for segmentation used here has a problem since; it requires the use of fixed bandwidth, reducing the magnitude and variety of detected motion patterns. To overcome this problem we propose the use of infinity norm which ensures that each evaluated pixel could be inside the neighborhood, and it avoids unnecessary calculations. The use of infinity norm ensures that each evaluated pixel could be inside the neighborhood and this fact avoids unnecessary calculations.

Keywords


Ensemble Clustering, Motion Segmentation, Object-Based Video Segmentation, Point Tracking, Video Coding.

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