Negative obstacle detection from image sequences

Tingbo Hu; Yiming Nie; Tao Wu; Hangen He

doi:10.1117/12.896288

8 July 2011 Negative obstacle detection from image sequences

Tingbo Hu, Yiming Nie, Tao Wu, Hangen He

Proceedings Volume 8009, Third International Conference on Digital Image Processing (ICDIP 2011); 80090Y (2011) https://doi.org/10.1117/12.896288
Event: 3rd International Conference on Digital Image Processing, 2011, Chengdu, China

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.

Citation Download Citation

Tingbo Hu, Yiming Nie, Tao Wu, and Hangen He "Negative obstacle detection from image sequences", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80090Y (8 July 2011); https://doi.org/10.1117/12.896288

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available