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Visual motion analysis method for detecting arbitrary numbers of moving objects in image sequences

机译:用于检测图像序列中任意数量的运动物体的视觉运动分析方法

摘要

A visual motion analysis method that uses multiple layered global motion models to both detect and reliably track an arbitrary number of moving objects appearing in image sequences. Each global model includes a background layer and one or more foreground “polybones”, each foreground polybone including a parametric shape model, an appearance model, and a motion model describing an associated moving object. Each polybone includes an exclusive spatial support region and a probabilistic boundary region, and is assigned an explicit depth ordering. Multiple global models having different numbers of layers, depth orderings, motions, etc., corresponding to detected objects are generated, refined using, for example, an EM algorithm, and then ranked/compared. Initial guesses for the model parameters are drawn from a proposal distribution over the set of potential (likely) models. Bayesian model selection is used to compare/rank the different models, and models having relatively high posterior probability are retained for subsequent analysis.
机译:一种视觉运动分析方法,它使用多层全局运动模型来检测并可靠地跟踪出现在图像序列中的任意数量的运动对象。每个全局模型包括一个背景层和一个或多个前景“ polybones”,每个前景polybone包括参数形状模型,外观模型和描述相关运动对象的运动模型。每个多骨骨都包括一个排他的空间支持区域和一个概率边界区域,并分配有明确的深度顺序。生成具有与检测到的对象相对应的不同数量的层,深度顺序,运动等的多个全局模型,使用例如EM算法对其进行精炼,然后对其进行排名/比较。模型参数的初始猜测是从一组潜在(可能)模型的提议分布中得出的。贝叶斯模型选择用于比较/排序不同模型,并保留具有较高后验概率的模型以用于后续分析。

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