Authors:
Wael Elloumi
;
Sylvie Treuillet
and
Rémy Leconge
Affiliation:
Polytech’Orléans, France
Keyword(s):
Vanishing Point Tracking, Camera Orientation, Video Sequences, Manhattan World.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Tracking and Visual Navigation
Abstract:
In man-made urban environments, vanishing points are pertinent visual cues for navigation task. But estimating the orientation of an embedded camera relies on the ability to find a reliable triplet of orthogonal vanishing points in real-time. Based on previous works, we propose a pipeline to achieve an accurate estimation of the camera orientation while preserving a short processing time. Our algorithm pipeline relies on two contributions: a novel sampling strategy among finite and infinite vanishing points extracted with a RANSAC-based line clustering and a tracking along a video sequence to enforce the accuracy and the robustness by extracting the three most pertinent orthogonal directions. Experiments on real images and video sequences show that the proposed strategy for selecting the triplet of vanishing points is pertinent as our algorithm gives better results than the recently published RNS optimal method (Mirzaei, 2011), in particular for the yaw angle, which is actually essen
tial for navigation task.
(More)