상세정보
학술지
Toward Accurate Road Detection in Challenging Environments Using 3D Point Clouds
- 발행일
- 201506
- 출처
- ETRI Journal, v.37 no.3, pp.606-616
- ISSN
- 1225-6463
- 출판사
- 한국전자통신연구원 (ETRI)
- 초록
- In this paper, we propose a novel method for road recognition using 3D point clouds based on a Markov random field (MRF) framework in unstructured and complex road environments. The proposed method is focused on finding a solution for an analysis of traversable regions in challenging environments without considering an assumption that has been applied in many past studies; that is, that the surface of a road is ideally flat. The main contributions of this research are as follows: (a) guidelines for the best selection of the gradient value, the average height, the normal vectors, and the intensity value and (b) how to mathematically transform a road recognition problem into a classification problem that is based on MRF modeling in spatial and visual contexts. In our experiments, we used numerous scans acquired by an HDL-64E sensor mounted on an experimental vehicle. The results show that the proposed method is more robust and reliable than a conventional approach based on a quantity evaluation with ground truth data for a variety of challenging environments.
- KSP 제안 키워드
- 3D point cloud, Classification problems, Complex road, Ground truth data, Markov Random Field, Recognition problem, Road recognition, experimental vehicle, gradient value, normal vector, novel method