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 KullbackLeibler 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.

• Type: Conference
• Year: 2005
• Where: ICCV
• Authors: Ali Shahrokni, Tom Drummond, Pascal Fua
• Keywords: Computer Vision, Fast Texture-segmentation Approach, ICCV 2005, Model-based Contour Tracking, Texture Boundaries