Using vanishing points for camera calibration
International Journal of Computer Vision
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Estimation of Relative Camera Positions for Uncalibrated Cameras
ECCV '92 Proceedings of the Second European Conference on Computer Vision
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Autocalibration from Planar Scenes
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Affine Reconstruction from Perspective Image Pairs Obtained by a Translating Camera
Proceedings of the Second Joint European - US Workshop on Applications of Invariance in Computer Vision
Metric Rectification for Perspective Images of Planes
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Self-Calibration of a Camera from Video of a Walking Human
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Planar Metric Rectification by Algebraically Estimating The Image of the Absolute Conic
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
IEEE Transactions on Pattern Analysis and Machine Intelligence
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Robust height estimation of moving objects from uncalibrated videos
IEEE Transactions on Image Processing
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This paper presents a method for video mensuration using a single stationary camera. The problem we address is simple, i.e., the mensuration of any arbitrary line segment on the reference plane using multiple frames with minimal calibration. Unlike previous solutions that are based on planar rectification, our approach is based on fitting the image of multiple concentric circles on the plane. Further, the proposed method aims to minimize the error in mensuration. Hence we can calculate the mensuration of the line segments not lying on the reference plane. Using an algorithm for detecting and tracking wheels of an automobile, we have implemented a fully automatic system for wheel base mensuration. The mensuration results are accurate enough that they can be used to determine the vehicle classes. Furthermore, we measure the line segment between any two points on the vehicle and plot them in top and side views.