一种贝叶斯方法来跟踪人群

Changjun Wang, Guojun Dai
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引用次数: 0

摘要

我们提出了一种新颖的方法来跟踪静态摄像机观察到的人群。该方法基于统一的贝叶斯定理框架对场景背景和目标颜色分布进行建模。通过共享框架,构建一个实用的监控系统更加简单,成本更低。此外,与GMM框架相比,该框架具有对初始观测值不敏感和自适应选择模态数的能力。通过对人的颜色分布建模,该方法不仅可以跟踪单个目标,还可以跟踪场景中被其他人遮挡或与他人互动的目标。户外视频实验证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Bayesian approach to groups of people tracking
We proposed a novel approach to track groups of people observed by a static camera. The approach relies on a unified Bayes' theorem based framework to model both scene background and the color distribution of targets. By sharing the framework, it is more simple and low cost to construct a practical surveillance system. Additionally, the framework has the advantages of insensitiveness to initial observations and the capability of adaptive selection of modal number compared with GMM framework. By modeling the color distribution of people, the approach can keep tracking not only single person targets but also those occluded by or interacting with other people in the scene. The experiments using outdoor videos prove that the approach is effective.
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