Binocular vision system is an essential way for target localization in many fields, which has been widely used as payload of unmanned surface vehicles (USV). High resolution cameras, which can provide richer information, are utilized more often on a USV. This brings challenges of computing tremendous data for target detection and localization in real-time. In this paper, we propose an framework to automatically detect and localize target using high resolution binocular cameras for environment perception of USV. Instead of processing the whole image, the feature extraction and matching are executed within the target region of interest determined by a deep convolution network. Then the target can be localized using triangulation principle with calibrated binocular camera parameters. Experiments show that our proposed strategy can achieve both precise detection and high accurate localization results in real-time applications.
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