IEEE Transactions on Pattern Analysis and Machine Intelligence
Achieving Artificial Intelligence through Building Robots
Achieving Artificial Intelligence through Building Robots
A Diffusion Mechanism for Obstacle Detection from Size-Change Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analyzing Looming Motion Components From Their Spatiotemporal Spectral Signature
IEEE Transactions on Pattern Analysis and Machine Intelligence
A General Motion Model and Spatio-Temporal Filters forComputing Optical Flow
International Journal of Computer Vision
Dynamic Vergence Using Log-Polar Images
International Journal of Computer Vision
New Visual Invariants for Terrain Navigation Without 3DReconstruction
International Journal of Computer Vision
Temporal Analysis of Motion in Video Sequences through Predictive Operators
International Journal of Computer Vision
The Applicability of Green‘s Theorem to Computation of Rate of Approach
International Journal of Computer Vision
Neural Processing Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Accuracy of the Computation of Optical Flow and of the Recovery of Motion Parameters
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Obstacle Detection Based on Qualitative and Quantitative 3D Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Time-to-Collision Estimation from Motion Based on Primate Visual Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hardware implementation of optical flow constraint equation using FPGAs
Computer Vision and Image Understanding
Monocular Vision Based Obstacle Detection for Robot Navigation in Unstructured Environment
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
An architecture for vision and action
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Hardware implementation of optical flow constraint equation using FPGAs
Computer Vision and Image Understanding
A new framework for force feedback teleoperation of robotic vehicles based on optical flow
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Expansion segmentation for visual collision detection and estimation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Derivation of qualitative information in motion analysis
Image and Vision Computing
A modified model for the Lobula Giant Movement Detector and its FPGA implementation
Computer Vision and Image Understanding
Behaviour of SFM algorithms with erroneous calibration
Computer Vision and Image Understanding
Biologically inspired path execution using SURF flow in robot navigation
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
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The use of certain measures of flow field divergence is investigated as a qualitative cue for obstacle avoidance during visual navigation. It is shown that a quantity termed the directional divergence of the 2-D motion field can be used as a reliable indicator of the presence of obstacles in the visual field of an observer undergoing generalized rotational and translational motion. The necessary measurements can be robustly obtained from real image sequences. Experimental results are presented showing that the system responds as expected to divergence in real-world image sequences, and the use of the system to navigate between obstacles is demonstrated.