Vision-based multi-person tracking by using MCMC-PF and RRF in office environments
Vision-based multi-person tracking by using MCMC-PF and RRF in office environments
复制标题
在办公环境中使用 MCMC-PF 和 RRF 进行基于视觉的多人跟踪
DOI：
10.1109/iros.2004.1389424
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
E. Kondo
中科院分区：
文献类型：
--
作者：
Kanji Tanaka;E. Kondo
提出了一种基于视觉的方法，用于在杂乱的办公室环境中，利用单目视觉传感器获取的灰度图像序列对多个人进行跟踪。该方法是基于一种新的算法来获取的原始和强大的功能，目标的位置和大小的目标的深度。该方法通过记忆和利用目标状态的历史数据，有效地科普了固定目标和运动目标造成的长时间遮挡问题。我们采用基于MCMC的粒子滤波器（MCMCMC-PF）来实现这些领域的知识，包括目标之间的相互作用，以及径向到达滤波器（RRF）来提取噪声灰度图像中的对象。在实验中，该方法可以可靠地跟踪多个人，并从错误中恢复，即使它失去了目标的视线。
We propose a vision-based method for tracking multiple persons with gray-scale image sequence acquired by a monocular vision sensor in cluttered office environments. This method is based on a novel algorithm for acquiring depth of targets with primitive and robust features, position and size of targets. To cope with long-term occlusions caused by both fixed and moving objects, the method memorizes and utilizes history data of targets' state. We employ MCMC-based particle filter (MCMC-PF) to implement such domain knowledge including, interactions between targets, as well as radial reach filter (RRF) to extract objects in noisy gray-scale images. In experiments, the method could track multiple persons reliably, and recover from errors even when it loses sight of targets.
影响因子：
4.7
作者：
Nummiaro, K;Koller-Meier, E;Van Gool, L
通讯作者：
Van Gool, L