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首页> 外文期刊>Engineering Applications of Artificial Intelligence >Multi-pose human head detection and tracking boosted by efficient human head validation using ellipse detection
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Multi-pose human head detection and tracking boosted by efficient human head validation using ellipse detection

机译：使用椭圆检测进行有效的人头验证可增强多姿势人头检测和跟踪

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摘要

In this paper, a novel system is developed to detect and track multiple heads in multi-pose status by efficient human head validation using ellipse detection. A particle filter is employed for each tracked head. The appearance model of head is updated based on fusion of color histogram and oriented gradient one. Regardless of its pose, a head is modeled as an ellipse, and we propose an objective function to fit the proposed elliptical equation. A robust supervised distance function learning framework has been developed to recover some missed detections and suppress some false detections, using an Expectation Maximization algorithm. Comparative study with state-of-the-arts has indicated the superiority and good performance of the proposed method.
机译：在本文中，开发了一种新颖的系统，可以通过使用椭圆检测的有效人头验证来检测和跟踪处于多姿势状态的多个头。每个跟踪头都采用了粒子过滤器。基于颜色直方图和定向梯度1的融合来更新头部的外观模型。无论其姿势如何，都将头部建模为椭圆，并且我们提出了一个目标函数来拟合所提出的椭圆方程。已经开发出了鲁棒的有监督距离函数学习框架，可以使用期望最大化算法来恢复一些漏检并抑制一些误检。与最新技术的比较研究表明，该方法具有优越性和良好的性能。

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