基于多帧松弛的轮廓跟踪

N. Sharp, E. Hancock
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引用次数: 1

摘要

本文提出了一种新的特征跟踪方法。它基于帧间松弛技术。该方法结合了框架内和框架间对可接受轮廓结构行为的约束。帧内信息由局部轮廓结构字典和一组方向特征检测算子响应的统计模型来表示。框架间成分表示新的建模成分;它被三维特征点的底层表面结构的隐式模型封装。该模型用一系列单峰概率密度表示,其参数为帧间距离。松弛方案中的初始概率有效地结合了描述位置统计不确定性的分布和多帧轮廓的特征特征;根据字典对这些概率进行细化,以产生一致的轮廓。
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Contour tracking by multi-frame relaxation
This paper describes a novel feature tracking method. It is based on an inter-frame relaxation technique. This method combines intra-frame and inter-frame constraints on the behaviour of acceptable contour structure. The intra-frame information is represented by both a dictionary of local contour structure and a statistical model of the response of a set of directional feature detection operators. The inter-frame ingredient represents the novel modelling component; it is encapsulated by an implicit model of the underlying surface structure of 3D feature points. The model is represented in terms of a series of unimodal probability densities whose single parameter is the inter-frame distance. The initial probabilities in our relaxation scheme effectively combine distributions describing the statistical uncertainties in the position and feature characteristics of multiframe contours; these probabilities are refined in the light of the dictionary to produce consistent contours.<>
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Detecting irregularities in cyclic motion Contour tracking by multi-frame relaxation A system for human motion matching between synthetic and real images based on a biomechanic graphical model Segmenting independently moving, noisy points Analyzing gait with spatiotemporal surfaces
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