Optimized visual recognition algorithm in service robots. (9th June 2020) - Wu, Jun W; Cai, Wei; Yu, Shi M; Xu, Zhuo L; He, Xue Y
Vision-based detection methods often require consideration of the robot's sight. For example, panoramic images cause image distortion, which negatively affects the target recognition and spatial localization. Furthermore, the original you only look once method does not have a reasonable performance for the image recognition in the panoramic images. Consequently, some failures have been reported so far when implementing the visual recognition on the robot. In the present study, it is intended to optimize the conventional you only look once algorithm and propose the modified you only look once algorithm. Comparing the obtained results with the experiment shows that the modified you only look once method can be effectively applied in the graphics processing unit to reach the panoramic recognition speedup to 32 frames rate per second, which meets the real-time requirements in diverse applications. It is found that the accuracy of the object detection when applying the proposed modified you only look once method exceeds 70% in the studied cases.