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Model-based human gait tracking, 3D reconstruction and recognition in uncalibrated monocular video

机译:未校准的单眼视频中基于模型的步态跟踪,3D重建和识别

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摘要

Automatic analysis of human motion includes initialisation, tracking, pose recovery and activity recognition. In this paper, a computing framework is developed to automatically analyse human motions through uncalibrated monocular video sequences. A model-based kinematics approach is proposed for human gait tracking. Based on the tracking results, 3D human poses and gait features are recovered and extracted. The recognition performance is evaluated by using different classifiers. The proposed method is advantageous in its capability of recognising human subjects walking non-parallel to the image plane.
机译:人体运动的自动分析包括初始化,跟踪,姿势恢复和活动识别。在本文中,开发了一种计算框架,用于通过未经校准的单眼视频序列自动分析人体运动。提出了一种基于模型的运动学方法用于人体步态跟踪。根据跟踪结果,恢复并提取3D人体姿势和步态特征。通过使用不同的分类器评估识别性能。所提出的方法在其识别不平行于图像平面行走的人类对象的能力方面是有利的。

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