@conference {12576,
	title = {Fast Bilinear SfM with Side Information},
	booktitle = {Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on},
	year = {2007},
	month = {2007/10//},
	pages = {1 - 8},
	abstract = {We study the beneficial effect of side information on the Structure from Motion (SfM) estimation problem. The side information that we consider is measurement of a {\textquoteright}reference vector{\textquoteright} and distance from fixed plane perpendicular to that reference vector. Firstly, we show that in the presence of this information, the SfM equations can be rewritten similar to a bilinear form in its unknowns. Secondly, we describe a fast iterative estimation procedure to recover the structure of both stationary scenes and moving objects that capitalizes on this information. We also provide a refinement procedure in order to tackle incomplete or noisy side information. We characterize the algorithm with respect to its reconstruction accuracy, memory requirements and stability. Finally, we describe two classes of commonly occurring real-world scenarios in which this algorithm will be effective: (a) presence of a dominant ground plane in the scene and (b) presence of an inertial measurement unit on board. Experiments using both real data and rigorous simulations show the efficacy of the algorithm.},
	keywords = {bilinear, Estimation, estimation;, estimation;reference, information;image, methods;motion, procedure;motion, procedure;side, reconstruction;iterative, recovery;image, structure, vector;refinement},
	doi = {10.1109/ICCV.2007.4408874},
	author = {Ramachandran, M. and Veeraraghavan,A. and Chellapa, Rama}
}
@conference {13165,
	title = {Estimation of Anthropomeasures from a Single Calibrated Camera},
	booktitle = {Automatic Face and Gesture Recognition, 2006. FGR 2006. 7th International Conference on},
	year = {2006},
	month = {2006/04//},
	pages = {499 - 504},
	abstract = {We are interested in the recovery of anthropometric dimensions of the human body from calibrated monocular sequences, and their use in multi-target tracking across multiple cameras and identification of individual people. In this paper, we focus on two specific anthropomeasures that are relatively easy to estimate from low-resolution images: stature and shoulder breadth. Precise average estimates are obtained for each anthropomeasure by combining measurements from multiple frames in the sequence. Our contribution is two-fold: (i) a novel technique for automatic and passive estimation of shoulder breadth, that is based on modelling the shoulders as an ellipse, and (U) a novel method for increasing the accuracy of the mean estimates of both anthropomeasures. The latter is based on the observation that major sources of error in the measurements are landmark localization the 2D image and 3D modelling error, and that both of these are correlated with gait phase and body orientation with respect to the camera. Consequently, estimation error can be significantly reduced via appropriate selection or control of these two variables},
	keywords = {anthropomeasures, calibrated, camera;anthropometry;error, estimation;error, estimation;gait, identification;image, phase;image, recovery;image, resolution;image, resolution;monocular, restoration;image, sensors;image, sequences;, sequences;single, statistics;image},
	doi = {10.1109/FGR.2006.37},
	author = {BenAbdelkader,C. and Davis, Larry S.}
}
