Deep Learning-Based Obstacle Detection and Depth Estimation

Yi Yu Hsieh, Wei Yu Lin, Dong Lin Li, Jen Hui Chuang

研究成果: Conference contribution同行評審

8 引文 斯高帕斯(Scopus)

摘要

This paper proposed a modified YOLOv3 which has an extra object depth prediction module for obstacle detection and avoidance. We use a pre-processed KITTI dataset to train the proposed, unified model for (i) object detection and (ii) depth prediction and use the AirSim flight simulator to generate synthetic aerial images to verify that our model can be applied in different data domains. Experimental results show that the proposed model compares favorably with other depth map prediction methods in terms of accuracy in the prediction of object depth for pre-processed KITTI dataset, while the unified approach can actually improve both (i) and (ii) at the same time.

原文English
主出版物標題2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings
發行者IEEE Computer Society
頁面1635-1639
頁數5
ISBN(電子)9781538662496
DOIs
出版狀態Published - 9月 2019
事件26th IEEE International Conference on Image Processing, ICIP 2019 - Taipei, Taiwan
持續時間: 22 9月 201925 9月 2019

出版系列

名字Proceedings - International Conference on Image Processing, ICIP
2019-September
ISSN(列印)1522-4880

Conference

Conference26th IEEE International Conference on Image Processing, ICIP 2019
國家/地區Taiwan
城市Taipei
期間22/09/1925/09/19

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