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Optical flow or image subtraction in human detection from infrared camera on mobile robot

机译:通过移动机器人上的红外摄像头进行人体检测时的光流或图像相减

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摘要

Perceiving the environment is crucial in any application related to mobile robotics research. In this paper, a new approach to real-time human detection through processing video captured by a thermal infrared camera mounted on the autonomous mobile platform mSecurit is introduced. The approach starts with a phase of static analysis for the detection of human candidates through some classical image processing techniques such as image normalization and thresholding. Then, the proposal starts a dynamic image analysis phase based in optical flow or image difference. Optical flow is used when the robot is moving, whilst image difference is the preferred method when the mobile platform is still. The results of both phases are compared to enhance the human segmentation by infrared camera. Indeed, optical flow or image difference will emphasize the foreground hot spot areas obtained at the initial human candidates' detection.
机译:在与移动机器人研究相关的任何应用中,感知环境至关重要。本文介绍了一种通过处理安装在自主移动平台mSecurit上的热红外摄像机捕获的视频来进行实时人体检测的新方法。该方法从静态分析阶段开始,该阶段通过一些经典的图像处理技术(例如图像归一化和阈值化)来检测人类候选者。然后,该提案开始基于光流或图像差异的动态图像分析阶段。当机器人移动时使用光流,而当移动平台静止时,图像差异是首选方法。比较两个阶段的结果,以通过红外热像仪增强人体分割效果。实际上,光流或图像差异将强调在最初的人类候选者检测时获得的前景热点区域。

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