Share Email Print
cover

Proceedings Paper

Negative obstacle detection from image sequences
Author(s): Tingbo Hu; Yiming Nie; Tao Wu; Hangen He
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Negative obstacle detection has been a challenging topic. In the previous researches, the distance that negative obstacles can be detected is so near that vehicles have to travel at a very low speed. In this paper, a negative obstacle detection algorithm from image sequences is proposed. When negative obstacles are far from the vehicle, color appearance models are used as the cues of detecting negative obstacles, while negative obstacles get closer, geometrical cues are extracted from stereo vision. Furthermore, different cues are combined in a Bayesian framework to detect obstacles in image sequences. Massive experiments show that the proposed negative obstacle detection algorithm is quite effective. The alarming distance for 0.8 m width negative obstacle is 18m, and the confirming distance is 10 m. This supplies more space for vehicles to slow down and avoid obstacles. Then, the security of the UGV running in the field can be improved remarkably.

Paper Details

Date Published: 8 July 2011
PDF: 7 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80090Y (8 July 2011); doi: 10.1117/12.896288
Show Author Affiliations
Tingbo Hu, National Univ. of Defense Technology (China)
Yiming Nie, National Univ. of Defense Technology (China)
Tao Wu, National Univ. of Defense Technology (China)
Hangen He, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)

© SPIE. Terms of Use
Back to Top