@article {12478,
	title = {Video Metrology Using a Single Camera},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {32},
	year = {2010},
	month = {2010/07//},
	pages = {1329 - 1335},
	abstract = {This paper presents a video metrology approach using an uncalibrated single camera that is either stationary or in planar motion. Although theoretically simple, measuring the length of even a line segment in a given video is often a difficult problem. Most existing techniques for this task are extensions of single image-based techniques and do not achieve the desired accuracy especially in noisy environments. In contrast, the proposed algorithm moves line segments on the reference plane to share a common endpoint using the vanishing line information followed by fitting multiple concentric circles on the image plane. A fully automated real-time system based on this algorithm has been developed to measure vehicle wheelbases using an uncalibrated stationary camera. The system estimates the vanishing line using invariant lengths on the reference plane from multiple frames rather than the given parallel lines, which may not exist in videos. It is further extended to a camera undergoing a planar motion by automatically selecting frames with similar vanishing lines from the video. Experimental results show that the measurement results are accurate enough to classify moving vehicles based on their size.},
	keywords = {camera;vanishing, circles;uncalibrated, concentric, image-based, information;vehicle, line, measurement;video, metrology;cameras;image, processing;, segment;multiple, segmentation;video, signal, single, techniques;line, wheelbase},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2010.26},
	author = {Guo,Feng and Chellapa, Rama}
}
