@conference {13122,
	title = {Kernel integral images: A framework for fast non-uniform filtering},
	booktitle = {Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on},
	year = {2008},
	month = {2008/06//},
	pages = {1 - 8},
	abstract = {Integral images are commonly used in computer vision and computer graphics applications. Evaluation of box filters via integral images can be performed in constant time, regardless of the filter size. Although Heckbert (1986) extended the integral image approach for more complex filters, its usage has been very limited, in practice. In this paper, we present an extension to integral images that allows for application of a wide class of non-uniform filters. Our approach is superior to Heckbertpsilas in terms of precision requirements and suitability for parallelization. We explain the theoretical basis of the approach and instantiate two concrete examples: filtering with bilinear interpolation, and filtering with approximated Gaussian weighting. Our experiments show the significant speedups we achieve, and the higher accuracy of our approach compared to Heckbertpsilas.},
	keywords = {approximated, equations;interpolation;, filtering;bilinear, filtering;kernel, Gaussian, graphics;computer, images;approximation, integral, interpolation;computer, nonuniform, processing;integral, theory;filtering, theory;image, vision;fast, weighting},
	doi = {10.1109/CVPR.2008.4587641},
	author = {Hussein,M. and Porikli, F. and Davis, Larry S.}
}
@conference {13163,
	title = {Constraint Integration for Multiview Pose Estimation of Humans with Self-Occlusions},
	booktitle = {3D Data Processing, Visualization, and Transmission, Third International Symposium on},
	year = {2006},
	month = {2006/06//},
	pages = {900 - 907},
	abstract = {Detection of articulated objects such as humans is an important task in computer vision. We present a system that incorporates a variety of constraints in a unified multi- view framework to automatically detect humans in possibly crowded scenes. These constraints include the kinematic constraints, the occlusion of one part by another and the high correlation between the appearance of parts such as the two arms. The graphical structure (non-tree) obtained is optimized in a nonparametric belief propagation framework using prior based search.},
	keywords = {articulated, belief, constraint;multiview, detection;computer, detection;pose, estimation;, estimation;nonparametric, framework;self-occlusion;computer, graphics;computer, method;graphical, methods;object, object, pose, propagation, structure;kinematic, vision;correlation},
	doi = {10.1109/3DPVT.2006.45},
	author = {Gupta,A. and Mittal,A. and Davis, Larry S.}
}
