单幅图像中上半身的自动提取

A. Tsitsoulis, N. Bourbakis
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引用次数: 0

摘要

在单一的、无约束的、单目图像中提取人体是一项非常困难的任务。然而,身体区域的定位和提取提供了重要和有用的知识,可以促进许多其他任务,如手势识别,姿态估计和动作识别。在本文中,我们提出了一种简单的基于外观的方法,该方法结合了人脸检测、皮肤检测、图像分割和人体测量约束,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明确估计。在复杂数据集上的实验结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic extraction of upper human body in single images
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.
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