The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1297–1302, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1297-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1297–1302, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1297-2020

  14 Aug 2020

14 Aug 2020

BINOCULAR VISUAL ENVIRONMENT PERCEPTION TECHNOLOGY FOR UNMANNED SURFACE VEHICLE

Y. Wang1, M. Peng1, Z. Liu1, W. Wan1, K. Di1, C. Hu2,3, L. Liu2, T. Lv2, and C. Yang2 Y. Wang et al.
  • 1State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
  • 2Beijing Institute of Aerospace Control Instruments, Beijing, China
  • 3Pilot National Laboratory for Marine Science and Technology, Qingdao, China

Keywords: Stereo vision, Localization, Calibration, Deep learning, Target recognition, Unmanned surface vehicle

Abstract. 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.