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Automatic extraction of upper human body in single images

机译:在单个图像中自动提取上半身

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摘要

Extraction of the human body in single, unconstrained, monocular images is a very difficult task. Localization and extraction of the body region, however, provides important and useful knowledge that can facilitate many other tasks, such as gesture recognition, pose estimation and action recognition. In this paper we present a simple appearance-based methodology that combines face detection, skin detection, image segmentation and anthropometric constraints to efficiently estimate the position and regions of hands in images. It requires no training neither explicit estimation of the human pose. Experimental results in a difficult dataset illustrate the performance of the approach.
机译:在单一,不受约束的单眼图像中提取人体是一项非常困难的任务。但是,身体部位的定位和提取提供了重要且有用的知识,可以促进许多其他任务,例如手势识别,姿势估计和动作识别。在本文中,我们提出了一种基于外观的简单方法,该方法结合了面部检测,皮肤检测,图像分割和人体测量学约束,可以有效地估计图像中手的位置和区域。它不需要训练,也不需要对人体姿势的显式估计。在困难的数据集中的实验结果说明了该方法的性能。

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