@inproceedings{61d7b902ebb740be95dd91b22b6260d2,
title = "An algorithm for obstacle detection based on YOLO and light filed camera",
abstract = "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.",
keywords = "depth map, light field camera, Obstacle detection, YOLO",
author = "Rumin Zhang and Yifeng Yang and Wenyi Wang and Liaoyuan Zeng and Jianwen Chen and Sean McGrath",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 12th International Conference on Sensing Technology, ICST 2018 ; Conference date: 04-12-2018 Through 06-12-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/ICSensT.2018.8603600",
language = "English",
series = "Proceedings of the International Conference on Sensing Technology, ICST",
publisher = "IEEE Computer Society",
pages = "223--226",
booktitle = "2018 12th International Conference on Sensing Technology, ICST 2018",
}