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Measuring Image Flow By Tracking Edge-lines

James L. Crowley, Patrick Stelmaszyk, Christophe Discours

发表年份
2005
引用次数
77

摘要

This paper describes a technique for measuring the movement of edge-lines in a sequence of images by maintalning an image plane model. Edge-lines are expressed as a set of parameter vectors representing the center-point, orientation and length of a segment. Each parameter vector is composed of an estimate, a temporal derivative, and their covariance matrix. Line segment parameters in the flow model are updated using a Kalman filter. The eorrespondance of observed edge-lines segments to segments predicted from the flow model is determined by a linear complexity algorithm using distance normalized by covariance. The existence of segments in the flow model is controlled using a confidence factor. This technique is in everyday use as part of a larger system for building 3-D scene descriptions using a camera mounted on a robot arm. A near video-rate hardware implementation is currently under development

关键词

Computer visionKalman filterArtificial intelligenceComputer scienceCovarianceCovariance matrixOrientation (vector space)Line (geometry)Enhanced Data Rates for GSM EvolutionImage plane

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