Fast Texture-Based Tracking and Delineation Using Texture Entropy

We propose a fast texture-segmentation approach to the problem of 2-D and 3--D model-based contour tracking, which is suitable for real-time or interactive applications. Our approach relies on detecting texture boundaries in the direction normal to the contour boundaries and on using a Hidden Markov Model to link these boundary points in the other direction. The probabilities that appear in this computation closely relate to texture entropy and Kullback-Leibler Divergence, a property we use to compute and update dynamic texture models. We demonstrate results both in the context of interactive 2-D delineation and fast 3-D tracking.


    • EPFL-REPORT-52680

    Record created on 2005-07-13, modified on 2017-05-12

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