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Embedded human detection system based on thermal and infrared sensors for anti-poaching application

机译:基于热和红外传感器的嵌入式人体检测系统用于反偷猎

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Poaching for massive traditional medicine demands is the single greatest threat of extinction that looms over most wildlife especially the endangered tiger. One way to curb the poaching activity is to have tighter monitoring of the protected area by using camera traps. In this research, an embedded system with human detection features for anti-poaching application is proposed. The system uses a 4 × 4 pixels' thermal sensor to detect any heat presence before an infrared camera is activated to capture video images. The images will be processed with a human detection algorithm based on frame differencing and orientation features. The detected human will then be verified using a Support Vector Machine (SVM) classifier. Once a human is identified, the image and the location of the human can then be sent through a long range data connection to a ranger office to alert the authorities. The system was implemented on a Raspberry Pi 2 board. Experiments have been conducted to evaluate the functionality of the system in non-urban environment during day and night times. The results showed that it can successfully detect human in an average of less than 2s even during night time with complete darkness.
机译:偷猎对大量传统医学的需求,是绝大部分野生生物尤其是濒临灭绝的老虎所面临的最大的灭绝威胁。遏制偷猎活动的一种方法是通过使用摄像机陷阱对保护区进行更严格的监控。在这项研究中,提出了一种具有人类检测功能的嵌入式系统,用于反偷猎。该系统使用4×4像素的热传感器来检测是否存在任何热量,然后再激活红外摄像头以捕获视频图像。图像将使用基于帧差异和方向特征的人类检测算法进行处理。然后,将使用支持向量机(SVM)分类器对检测到的人进行验证。一旦识别出人员,就可以通过远程数据连接将人员的图像和位置发送到护林员办公室,以向当局发出警报。该系统在Raspberry Pi 2板上实现。已经进行了实验,以评估白天和晚上在非城市环境中系统的功能。结果表明,即使在完全黑暗的夜晚,它也可以平均不到2秒成功检测到人。

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