Abstract: Aiming at the demand of people counting in the entrance of the public places with complicated environment, a people counting system based on the flexible pressure-sensitive sensor is presented in this study. The statistical accuracy of the proposed system is not influenced by illumination change, shelter, motion blur and complex background. The sensor is laid down at the entrance of public places. The plantar pressure data is sampled and transfers to the remote computer for further analysis through the network communication module in real time. By data denoising, image segmentation and feature extraction, the footprints of the pedestrians and their characteristic parameters are obtained. Then the algorithm of feature matching and motion trajectory planning is applied to realize pedestrian counting. Experimental results show that the proposed system not only has the merits of working stably, strong robustness and fast response, but also can provide a high statistical accuracy in all kinds of test conditions, and in some specific case, an accuracy of 98% can be obtained.

Key words: flexible force-sensitive sensor, pressure footprint, image segmentation, feature matching, motion trajectory planning, people counting

摘要： 针对复杂环境下公共场所出入口的人数统计需求，避免因光照变化、遮挡、运动模糊及复杂背景等对统计精度造成的影响，提出一种基于柔性力敏传感器的人数统计系统。该系统实时获取公共场所出入口处的行人在传感器区域留下的压力足印，并通过网络通信模块将足底压力数据传递给上位机进行数据处理与分析，经过数据去噪、图像分割和特征提取等步骤得到目标脚印及其特征参数，再运用特征匹配和运动轨迹规划算法进行人数统计。实验结果表明，该系统不仅工作稳定，具有较好的鲁棒性以及较快的响应速度，而且在不同测试场景中均可获得较高的统计准确率，特定场景下最高可达98%。

关键词: 柔性力敏传感器, 压力足印, 图像分割, 特征匹配, 运动轨迹规划, 人数统计

CLC Number: 

• TP18