Authors:
Mikael Nilsson
1
and
Håkan Ardö
2
Affiliations:
1
Lund University, Sweden
;
2
Lund Univerisy, Sweden
Keyword(s):
3D Model, Foreground/Background Segmentation, Context, Traffic, Camera Calibration, Ground-plane.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Motion, Tracking and Stereo Vision
;
Video Surveillance and Event Detection
Abstract:
Automatic video analysis of interactions between road users is desired for city and road planning. A first step
of such a system is object localization of road users. In this work, we present a method of detecting a specific
car in an intersection from a monocular camera image. A camera calibration and segmentation are utilized
as inputs by the method in order to detect a car. Using these inputs, a sampled search space in the ground plane, including rotations, is explored with a 3D model of a car in order to produce output in form of rectangle detections in the ground plane. Evaluation on real recorded data, with ground truth for one car using GPS, indicates that a car can be detected in over 90% of the time with an average error around 0.5m.