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A PTZ camera based people-occupancy estimation system (PCBPOES)

机译:基于PTZ摄像机的人员占用估算系统(PCBPOES)

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A single PTZ Camera Based People-Occupancy Estimation System (PCBPOES) is proposed to estimate the number of people occupying a region of interest with acceptable accuracy. The PTZ camera aids this objective by efficiently monitoring a wide area by dividing it into zones, capturing high resolution zone images aided by the optical zoom for detecting human head patterns. A seminar room is used as a test location for evaluating this system. Cascade trained support vector machine models are used to detect head patterns in the images. Features such as HAAR, HOG were explored for modeling the head patterns. We adopt a zone-based detection and ensemble approach to combine the zone detection results. A temporal probabilistic selection approach improves the head detection accuracy. Experiments prove that the system has high detection accuracy achieving average precision scores of 0.92 and recall scores of 0.82. A bio-inspired retina model is adopted to detect heads in low illumination. The system is currently used to estimate people-occupancy in the test location.
机译:提出了一个基于PTZ摄像机的人员占用估算系统(PCBPOES),以可接受的精度估算占用感兴趣区域的人数。 PTZ摄像机通过将区域划分为多个区域来进行有效监视,并借助光学变焦捕获高分辨率的区域图像以检测人的头部图案,从而帮助实现了这一目标。研讨室被用作评估该系统的测试地点。级联训练的支持向量机模型用于检测图像中的头部图案。探索了诸如HAAR,HOG之类的功能来对头部图案进行建模。我们采用基于区域的检测和集成方法来组合区域检测结果。时间概率选择方法提高了头部检测的准确性。实验证明,该系统具有较高的检测精度,平均精度得分为0.92,召回得分为0.82。采用受生物启发的视网膜模型来检测低照度下的头部。该系统当前用于估计测试位置的人员占用情况。

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