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Implementation of real-time object recognition system for home-service robot by integrating SURF and BRISK

机译：通过集成冲浪和快速来实现家庭服务机器人实时对象识别系统

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This paper proposes a real-time object recognition systems for recognizing known objects and searching unknown objects for home service robot. The object recognition system is mainly used in recognizing known objects, which combined Compute Unified Device Architecture (CUDA), Speeded Up Robust Features (SURF) detector and Binary Robust Invariant Scalable Keypoints (BRISK) descriptor for improving the computation speed and decreasing the consumption on memory. On the other side, the visual perception system is usually used for searching unknown objects, which calculated the depth differences and found the contours of objects. The experimental results in the laboratory and the competition in robot@home league at RoboCup Japan Open 2013 Tokyo illustrate that the robot can successfully real-time recognize the known objects and search the unknown objects.
机译：本文提出了一种用于识别已知对象并搜索家庭服务机器人的未知对象的实时对象识别系统。对象识别系统主要用于识别已知对象，组合计算统一设备架构（CUDA），加速鲁棒功能（SURD）检测器和二进制鲁棒不变可伸缩关键点（FRISK）描述符以提高计算速度并降低消耗记忆。在另一方面，视觉感知系统通常用于搜索未知对象，该物体计算得深度差异并找到对象的轮廓。实验室在实验室和机器人竞争中的实验结果@ Home联赛在Robocup Japan开放2013年Tokyo说明机器人可以成功实时识别已知的对象并搜索未知对象。

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