Infrared (IR) images are not affected by factors such as illumination and have the ability to work all day long, which is of great significance for night detection of unmanned platforms. We propose a multiview infrared target detection and localization algorithm (MVIDL), a complete sensory-fusion framework that uses IR images and lidar point cloud to detect and locate infrared targets (pedestrian and vehicle). MVIDL is a two-stage pipeline with an IR camera and three-dimensional lidar information as input. First, we introduce an infrared region proposal method that fuses lidar point cloud cluster results and IR image cluster results to obtain target regions and their position. In the second stage, an aggregate feature is proposed and extracted from the target regions, after which SVM is adopted to classify. Experimental results demonstrate that this algorithm can effectively detect targets and precisely get their position and size.
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