Motion Field and Optical Flow: Qualitative Properties
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovery of Ego-Motion Using Region Alignment
IEEE Transactions on Pattern Analysis and Machine Intelligence
Global rigidity constraints in image displacement fields
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Vehicle Ego-Motion Estimation and Moving Object Detection using a Monocular Camera
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Efficient cumulative matching for image registration
Image and Vision Computing
Efficient plane detection from a single moving camera
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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We propose an efficient method for detecting 3D planes from a moving uncalibrated camera. It assumes only a 3D translation for the egomotion. The original idea is to get around the dependence between the 2D motion field, the depth (i.e. scene structure) and the ignored egomotion. Relations are established between predicted iso-velocity curves and 3D surface parameters in eliminating the depth variable from equations. Surface assessment is performed within a simple velocity voting-space: a 3D surface, like a given plane, emerges as a curve, like a parabola. Experimentations validate our approach for several applications including automatic driver assistance, showing a surprising robustness. The aim of the present paper is to analyze this robustness. Five main perturbations are focused on and their influence on the plane detection process is studied in details.