Publication

Fast Texture-Based Tracking and Delineation Using Texture Entropy

Pascal Fua
2004
Reports

Abstract

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.

Official source

https://infoscience.epfl.ch/entities/publication/58af5cec-d679-40b0-ba32-d38854c153a9

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Pascal Fua
2004
Reports

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/58af5cec-d679-40b0-ba32-d38854c153a9

About this result

Related concepts (32)

Image segmentation

In and computer vision, image segmentation is the process of partitioning a into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.

Active contour model

Active contour model, also called snakes, is a framework in computer vision introduced by Michael Kass, Andrew Witkin, and Demetri Terzopoulos for delineating an object outline from a possibly 2D . The snakes model is popular in computer vision, and snakes are widely used in applications like object tracking, shape recognition, , edge detection and stereo matching. A snake is an energy minimizing, deformable spline influenced by constraint and image forces that pull it towards object contours and internal forces that resist deformation.

Computer vision

Computer vision tasks include methods for , , and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images (the input to the retina in the human analog) into descriptions of the world that make sense to thought processes and can elicit appropriate action.

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Fast Texture-Based Tracking and Delineation Using Texture Entropy

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