IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques
International Journal of Computer Vision
Independent component analysis: algorithms and applications
Neural Networks
The statistics of optical flow
Computer Vision and Image Understanding
Properties of Independent Components of Self-Motion Optical Flow
ISMVL '00 Proceedings of the 30th IEEE International Symposium on Multiple-Valued Logic
Optic flow and beyond
On the Spatial Statistics of Optical Flow
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Topographic Independent Component Analysis
Neural Computation
Dominant plane detection from optical flow for robot navigation
Pattern Recognition Letters
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Model-based plane-segmentation using optical flow and dominant plane
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
A neural model of human object recognition development
BVAI'05 Proceedings of the First international conference on Brain, Vision, and Artificial Intelligence
Dominant plane detection using optical flow and independent component analysis
BVAI'05 Proceedings of the First international conference on Brain, Vision, and Artificial Intelligence
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In this paper, we present an algorithm for detecting obstacles using independent components of optical flow fields for visual navigation of a mobile robot. For the computation of optical flow, the pyramid transform of an image sequence is used for the analysis of global motion and local motion. We detect obstacles from optical flow fields at each layer in the pyramid. Therefore, our algorithm allows us to achieve both global perception and local perception for the robot vision. We show experimental results for both test image sequences and real image sequences captured by a mobile robot.