RGB-T Target Tracking Algorithm Based on CNN Features
Aiming at the problem of poor robustness and low tracking accuracy of target tracking under a single image source,this paper proposes a robust tracking algorithm of RGB-T target based on Convolutional Neural Network(CNN)features.Firstly,layered CNN features are used to encode RGB images and thermal infrared images.Secondly,targets are tracked based on SiamDW tracking framework.Then according to the results of tracking in a short period of time the results of each CNN features for adaptive fusion and locate in the end,the RGB image and the result of thermal infrared image fusion and locate experiments show that com-pared with the existing siamese tracking algorithm,this algorithm has better performance in a central location deviation and overlap rate and better robustness in complex situations.
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