Moving target detection through omni-orientational vision fixed on AGV

Shu-Ying Yang; Zuo-Liang Cao; Pei-Lian He

doi:10.1117/12.690971

2 October 2006 Moving target detection through omni-orientational vision fixed on AGV

Shu-Ying Yang, Zuo-Liang Cao, Pei-Lian He

Proceedings Volume 6384, Intelligent Robots and Computer Vision XXIV: Algorithms, Techniques, and Active Vision; 63840I (2006) https://doi.org/10.1117/12.690971
Event: Optics East 2006, 2006, Boston, Massachusetts, United States

Abstract

Extremely wide view of the omni-vision performs highly advanced for the vehicle navigation and target detection. However moving targets detection through omni-vision fixed on AGV (Automatic Guided Vehicle) involves more complex environments, where both the targets and the vehicle are in the moving condition. The moving targets will be detected in a moving background. After analyzing the character on omniorientational vision and image, we propose to use the estimation in optical flow fields, Gabor filter over optical flow fields for detecting moving objects. Because polar angle θ and polar radius R of polar coordinates are being changed as the targets moving, we improved optical flow approach which can be calculated based on the polar coordinates at the omniorientational center. We constructed Gabor filter which has 24 orientations every 15°, and filter optical flow fields at 24 orientations. By the contrast of the Gabor filter images at the same orientation and the same AGV position between the situation which there aren't any moving targets in the environment and the situation which there are some moving targets in the same environment, the moving targets' optical flow fields could be recognized. Experiment results show that the proposed approach is feasible and effective.

Citation Download Citation

Shu-Ying Yang, Zuo-Liang Cao, and Pei-Lian He "Moving target detection through omni-orientational vision fixed on AGV", Proc. SPIE 6384, Intelligent Robots and Computer Vision XXIV: Algorithms, Techniques, and Active Vision, 63840I (2 October 2006); https://doi.org/10.1117/12.690971

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KEYWORDS

Optical flow

Image filtering

Target detection

Optical filters

Cameras

Environmental sensing

Target recognition

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