An Algorithm for Obstacle Detection based on YOLO and Light Filed Camera
Rumin Zhang, Yifeng Yang, Wenyi Wang, Liaoyuan Zeng, Jianwen Chen, Sean McGrath · 2018
This paper presents a novel obstacle detection algorithm in the indoor environment. The algorithm combines the YOLO object detection algorithm and the light field camera which is more simple than normal RGB-D sensor and acquires depth image and high-resolution images at the same in one exposure. The RGB Image rendered by the light filed camera is taken as an input of the YOLO model which was trained base on nearly 100 categories of common objects. According to the object information and the depth map, the obstacle was accurately calculated including its size and position. Experimental results demonstrate that the proposed method can provide higher detection accuracy under indoor environment.