基于主动运动的人体轮廓分割

I. Kakadiaris, Dimitris N. Metaxas, R. Bajcsy
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引用次数: 9

摘要

提出了一种综合的人体轮廓分割和形状估计方法。最初,我们假设人体由单个部分组成,并使用基于物理的形状和运动估计框架将可变形模型拟合到给定数据中。当演员达到不同的姿势时,轮廓上会出现新的突出物。我们使用一种由可变形模型的参数组合组成的新表示方案来模拟这些形状的变化。通过监测组成模型的形状和运动参数的演变,这种表示使我们能够识别逐渐可见的潜在人体部位。基于这些参数,确定了它们的关节位置。该算法在随后的帧中迭代应用,直到识别出所有的运动部件。我们在一系列实验中证明了这项技术,结果非常令人鼓舞。
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Active motion-based segmentation of human body outlines
We present an integrated approach towards the segmentation and shape estimation of human body outlines. Initially, we assume that the human body consists of a single part, and we fit a deformable model to the given data using our physics-based shape and motion estimation framework. As an actor attains different postures, new protrusions emerge on the outline. We model these changes in the shape using a new representation scheme consisting of a parametric composition of deformable models. This representation allows us to identify the underlying human parts that gradually become visible, by monitoring the evolution of shape and motion parameters of the composed models. Based on these parameters, their joint locations are identified. The algorithm is applied iteratively over subsequent frames until all moving parts are identified. We demonstrate the technique in a series of experiments with very encouraging results.<>
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