多个移动头部的实时立体跟踪

R. Luo, Yan Guo
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引用次数: 17

摘要

在具有遮挡的混乱场景中跟踪大量移动的人是计算机视觉中的一个重要问题。在本文中,我们提出了RealTrack,一个在现实世界应用中同时跟踪多个运动头部的实时系统。它利用深度信息来减轻阴影的影响,并通过深度排序消除遮挡的歧义。通过旋转不敏感的头肩轮廓模型和自适应跟踪算法的增强,我们的系统可以鲁棒地跟踪各种情况下的人,如交叉、聚集、散射和在不同于遮挡前运动方向的方向上重新出现。我们还采用了动态背景更新的方法,使我们的系统适合在缓慢的光照变化和物体进出等干扰下的长时间监控。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time stereo tracking of multiple moving heads
Tracking a number of persons moving in a cluttered scene with occlusions is an important issue in computer vision. In this paper we present RealTrack, a system for simultaneously tracking of multiple moving heads in real time for real world applications. It leverages on depth information to alleviate the influence of shadows and to disambiguate occlusions by depth ordering. Augmented by rotation insensitive head-shoulder contour models together with an adaptive tracking algorithm, our system can robustly track people in various conditions such as crossing, gathering, scattering, and re-appearing in a direction different from the moving direction before occlusion. We also employ dynamic background update method, which makes our system suitable for long time surveillance under slow lighting changes and disturbances such as objects going in and out of the scene.
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