This paper presents a vision-based obstacle avoidance method for blind pedestrians in an outdoor sidewalk environ- ment. Unlike many existing travel-aid systems using stereo-vi- sion based methods, the proposed method...This paper presents a vision-based obstacle avoidance method for blind pedestrians in an outdoor sidewalk environ- ment. Unlike many existing travel-aid systems using stereo-vi- sion based methods, the proposed method is able to get obstacle position as well as user motion information by just one monocu- lar camera fixed at the belly of the user. To achieve this goal, a top-view transformation of the road image is used for obstacle detection and user motion estimation, based on which a grid map is generated for navigation. For detection part, the bottom points of erect obstacles are detected by extracting local-maxima and minima on the top-view image while user motion is estimat- ed by analysing the optical flow vector field in the user sur- rounding area. For the obstacle avoidance part, a step score is calculated on the grid map for evaluating the safety of next moving step. Experiments with several sidewalk video-clips show that the proposed obstacle avoidance method is able to provide useful guidance instructions under certain sidewalk environments.展开更多
基金supported by the Brain Korea 21 Project in2010the ITRC support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2010-(C1090-1021-0010))
文摘This paper presents a vision-based obstacle avoidance method for blind pedestrians in an outdoor sidewalk environ- ment. Unlike many existing travel-aid systems using stereo-vi- sion based methods, the proposed method is able to get obstacle position as well as user motion information by just one monocu- lar camera fixed at the belly of the user. To achieve this goal, a top-view transformation of the road image is used for obstacle detection and user motion estimation, based on which a grid map is generated for navigation. For detection part, the bottom points of erect obstacles are detected by extracting local-maxima and minima on the top-view image while user motion is estimat- ed by analysing the optical flow vector field in the user sur- rounding area. For the obstacle avoidance part, a step score is calculated on the grid map for evaluating the safety of next moving step. Experiments with several sidewalk video-clips show that the proposed obstacle avoidance method is able to provide useful guidance instructions under certain sidewalk environments.
