Using vanishing points for camera calibration
International Journal of Computer Vision
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera Calibration from Video of a Walking Human
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Multiple Structures Estimation with J-Linkage
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Using pedestrians walking on uneven terrains for camera calibration
Machine Vision and Applications
Monocular vision-based target detection on dynamic transport infrastructures
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
Dynamic camera calibration of roadside traffic management cameras for vehicle speed estimation
IEEE Transactions on Intelligent Transportation Systems
| Hi-index | 12.05 |
In this paper, a hierarchical monocular camera auto-calibration method is presented for applications in the framework of intelligent transportation systems (ITS). It is based on vanishing point extraction from common static elements present on the scene, and moving objects as pedestrians and vehicles. This process is very useful to recover metrics from images or applying information of 3D models to estimate 2D pose of targets, making a posterior object detection and tracking more robust to noise and occlusions. Moreover, the algorithm is independent of the position of the camera, and it is able to work with variable pan-tilt-zoom (PTZ) cameras in fully self-adaptive mode. The objective is to obtain the camera parameters without any restriction in terms of constraints or the need of prior knowledge, to deal with most traffic scenarios and possible configurations. The results achieved up to date in real traffic conditions are presented and discussed.