Digital Image Processing
Statistical color models with application to skin detection
International Journal of Computer Vision
Appearance-Based Obstacle Detection with Monocular Color Vision
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Shape and the Stereo Correspondence Problem
International Journal of Computer Vision
Detecting free space and obstacles in omnidirectional images
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part I
A Bayes filter based adaptive floor segmentation with homography and appearance cues
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
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A novel framework based on stereo homography is proposed for robust floor/obstacle detection, capable of producing dense results. Floor surfaces and floor anomalies are identified at the pixel level using the symmetric transfer distance from the ground homography. Pixel-wise results are used as seed measurements for higher lever classification, where image regions with similar visual properties are processed and classified together. Without requiring any prior training, the method incrementally learns appearance models for the floor surfaces and obstacles in the environment, and uses the models to disambiguate regions where the homography-based classifier cannot provide a confident response. Several experiments on an indoor database of stereo images with ground truth data validate the robustness of our proposed technique.