Binocular visible light camera and thermal infrared camera-based target identification method

Abstract

The invention discloses a binocular visible light camera and thermal infrared camera-based target identification method. The method comprises the steps of calibrating internal and external parametersof two cameras of a binocular visible light camera through a position relationship between an image collected by the binocular visible light camera and a pseudo-random array stereoscopic target in a world coordinate system, and obtaining a rotation and translation matrix position relationship, between world coordinate systems, of the two cameras; according to an image collected by a thermal infrared camera, calibrating internal and external parameters of the thermal infrared camera; calibrating a position relationship between the binocular visible light camera and the thermal infrared camera;performing binocular stereoscopic visual matching on the images collected by the two cameras of the binocular visible light camera by adopting a sift feature detection algorithm, and calculating a visible light binocular three-dimensional point cloud according to a matching result; performing information fusion on temperature information of the thermal infrared camera and the three-dimensional point cloud of the binocular visible light camera; and inputting an information fusion result to a trained deep neural network for performing target identification.

Description

technical field [0001] The invention relates to the field of intelligent monitoring, in particular to a target recognition method based on a binocular visible light camera and a thermal infrared camera. Background technique [0002] In video surveillance, the detection, recognition and automatic alarm of moving targets has always been a hot research issue, and it has important applications in the fields of vehicle safety, security monitoring and robotics. In the past ten years, there have been many mature algorithms in pedestrian detection technology, but there are still many problems and difficulties. In the case of good lighting, only the visible light camera is needed to obtain texture information-rich images, but in the case of rainy days, heavy fog, and low light at night, the target features in the visible light camera images are not obvious. Compared with other video images, the infrared video image has a simple background and less interference objects, which is cond...

AI Technical Summary

Problems solved by technology

However, the human form in the infrared video is easily disturbed by external factors, such as the material of the clothes, wearing a hat and scarf, and the distance, etc., which makes the human form in the lens stretch and break, making it difficult to distinguish the characteristics of the human form

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