Negative obstacle detection from image sequences

摘要：

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.

关键词： Negative obstacle detection stereo vision image sequence Bayesian framework occlusion detection

作者: Tingbo Hu Yiming Nie Tao Wu Hangen He

作者单位: Mcchatronics & Automation School, National University of Defense Technology,Changsha, Hunan, China

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 175-181

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）