Fusing Multi-Modality Information for 3D Road Obstacle Detection

Yu Quan Wang, Yi Ting Chen, Man Lin Wu, Ching Hsiang Ko, Hao Wei Hwang, Yung Yao Chen*

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Considerable resources have been devoted to developing self-driving systems in industry and academia, for which three-dimensional object detection is critical. The commonly used LiDAR-based methods, in which point clouds serve as the input representation, are marred by the problems of sparsity and inhomogeneity, which make small or distant objects difficult to detect. Accordingly, we propose a LiDAR-based road obstacle detection method assisted by RGB images, which operates as follows. First, a depth completion network is used to transform RGB images into dense depth maps that can be used to create a pseudo-point cloud through matrix operations. Subsequently, both pseudo point cloud and real point cloud are transformed into a pillar form for a pillar-wise feature encoder; this is executed to generate a two-dimensional (2D) feature tensor. Finally, a standard 2D convolutional neural network detection architecture is used to learn features. This method increases the number of point features to remedy the sparsity and inhomogeneity of the original point cloud. Our method had an improvement compared with its LiDAR-based counterpart in experiments.

原文English
主出版物標題ISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems
主出版物子標題5G Dream to Reality, Proceeding
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781665419512
DOIs
出版狀態Published - 2021
事件2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021 - Hualien, Taiwan
持續時間: 16 11月 202119 11月 2021

出版系列

名字ISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems: 5G Dream to Reality, Proceeding

Conference

Conference2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021
國家/地區Taiwan
城市Hualien
期間16/11/2119/11/21

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