@conference {13139,
	title = {Hierarchical Part-Template Matching for Human Detection and Segmentation},
	booktitle = {Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on},
	year = {2007},
	month = {2007/10//},
	pages = {1 - 8},
	abstract = {Local part-based human detectors are capable of handling partial occlusions efficiently and modeling shape articulations flexibly, while global shape template-based human detectors are capable of detecting and segmenting human shapes simultaneously. We describe a Bayesian approach to human detection and segmentation combining local part-based and global template-based schemes. The approach relies on the key ideas of matching a part-template tree to images hierarchically to generate a reliable set of detection hypotheses and optimizing it under a Bayesian MAP framework through global likelihood re-evaluation and fine occlusion analysis. In addition to detection, our approach is able to obtain human shapes and poses simultaneously. We applied the approach to human detection and segmentation in crowded scenes with and without background subtraction. Experimental results show that our approach achieves good performance on images and video sequences with severe occlusion.},
	keywords = {analysis;global, approach;background, articulations;video, Bayesian, detection;human, detectors;hierarchical, detectors;partial, framework;Bayesian, human, likelihood, MAP, matching;human, matching;image, methods;image, occlusion, occlusions;shape, part-based, part-template, re-evaluation;global, segmentation;image, segmentation;local, sequences;, sequences;Bayes, SHAPE, subtraction;fine, template-based},
	doi = {10.1109/ICCV.2007.4408975},
	author = {Zhe Lin and Davis, Larry S. and David Doermann and DeMenthon,D.}
}
@conference {13138,
	title = {An Interactive Approach to Pose-Assisted and Appearance-based Segmentation of Humans},
	booktitle = {Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on},
	year = {2007},
	month = {2007/10//},
	pages = {1 - 8},
	abstract = {An interactive human segmentation approach is described. Given regions of interest provided by users, the approach iteratively estimates segmentation via a generalized EM algorithm. Specifically, it encodes both spatial and color information in a nonparametric kernel density estimator, and incorporates local MRF constraints and global pose inferences to propagate beliefs over image space iteratively to determine a coherent segmentation. This ensures the segmented humans resemble the shapes of human poses. Additionally, a layered occlusion model and a probabilistic occlusion reasoning method are proposed to handle segmentation of multiple humans in occlusion. The approach is tested on a wide variety of images containing single or multiple occluded humans, and the segmentation performance is evaluated quantitatively.},
	keywords = {algorithm;appearance-based, algorithm;hidden, approach;layered, density, EM, Estimation, estimation;, estimator;pose-assisted, feature, human, Kernel, mechanisms;pose, method;expectation-maximisation, model;nonparametric, occlusion, reasoning, removal;image, segmentation;inference, segmentation;interactive, segmentation;probabilistic},
	doi = {10.1109/ICCV.2007.4409123},
	author = {Zhe Lin and Davis, Larry S. and David Doermann and DeMenthon,D.}
}
@article {14230,
	title = {Motion segmentation using occlusions},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume = {27},
	year = {2005},
	month = {2005/06//},
	pages = {988 - 992},
	abstract = {We examine the key role of occlusions in finding independently moving objects instantaneously in a video obtained by a moving camera with a restricted field of view. In this problem, the image motion is caused by the combined effect of camera motion (egomotion), structure (depth), and the independent motion of scene entities. For a camera with a restricted field of view undergoing a small motion between frames, there exists, in general, a set of 3D camera motions compatible with the observed flow field even if only a small amount of noise is present, leading to ambiguous 3D motion estimates. If separable sets of solutions exist, motion-based clustering can detect one category of moving objects. Even if a single inseparable set of solutions is found, we show that occlusion information can be used to find ordinal depth, which is critical in identifying a new class of moving objects. In order to find ordinal depth, occlusions must not only be known, but they must also be filled (grouped) with optical flow from neighboring regions. We present a novel algorithm for filling occlusions and deducing ordinal depth under general circumstances. Finally, we describe another category of moving objects which is detected using cardinal comparisons between structure from motion and structure estimates from another source (e.g., stereo).},
	keywords = {3D motion estimation, algorithms, Artificial intelligence, CAMERAS, Computer vision, Filling, hidden feature removal, Image Enhancement, Image Interpretation, Computer-Assisted, image motion, Image motion analysis, Image segmentation, Layout, MOTION, Motion detection, Motion estimation, motion segmentation, Movement, Object detection, occlusion, occlusions, optical flow, ordinal depth, Pattern Recognition, Automated, Photography, Reproducibility of results, segmentation, Semiconductor device modeling, Sensitivity and Specificity, video analysis., Video Recording},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2005.123},
	author = {Ogale, A. S and Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@conference {13245,
	title = {Scalable image-based multi-camera visual surveillance system},
	booktitle = {Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2003.},
	year = {2003},
	month = {2003/07//},
	pages = {205 - 212},
	abstract = {We describe the design of a scalable and wide coverage visual surveillance system. Scalability (the ability to add and remove cameras easily during system operation with minimal overhead and system degradation) is achieved by utilizing only image-based information for camera control. We show that when a pan-tilt-zoom camera pans and tilts, a given image point moves in a circular and a linear trajectory, respectively. We create a scene model using a plan view of the scene. The scene model makes it easy for us to handle occlusion prediction and schedule video acquisition tasks subject to visibility constraints. We describe a maximum weight matching algorithm to assign cameras to tasks that meet the visibility constraints. The system is illustrated both through simulations and real video from a 6-camera configuration.},
	keywords = {ACQUISITION, algorithm;, camera;, constraints;, feature, hidden, image-based, MATCHING, maximum, multi-camera, occlusion, pan-tilt-zoom, PLAN, prediction;, processing;, removal;, scalable, scheduling;, signal, Surveillance, surveillance;, system;, task, video, view;, visibility, visual, weight},
	doi = {10.1109/AVSS.2003.1217923},
	author = {Lim,Ser-Nam and Davis, Larry S. and Elgammal,A.}
}
@article {17508,
	title = {Why not make interfaces better than 3D reality?},
	journal = {IEEE Computer Graphics and Applications},
	volume = {23},
	year = {2003},
	month = {2003/12//Nov},
	pages = {12 - 15},
	abstract = {Many constrained interfaces are designed to be simpler than the real world by restricting movement, limiting interface actions, and keeping interface objects in a plane. However, the strong utility of pure 3D interfaces for medical, architectural, product design, and scientific visualization means that interface design for pure 3D remains an important challenge. An intriguing possibility is that enhanced 3D interfaces might offer simpler navigation, more compelling functionality, safer movements, and less occlusion, than 3D reality, especially for information exploration and visualization tasks. Such features can enable superhuman capabilities such as faster-than-light teleportation, flying through objects, and X-ray vision. Enhanced 3D interfaces might have supernatural tools such as magic wands for instantly shrinking, enlarging, duplicating, or sending objects and enchanted environments that provide error prevention, history keeping, and programming-by-demonstration. Playful game designers and creative application developers have already pushed the technology further than those who seek merely to mimic reality. Advanced designs are marked by their support of rapid situation awareness through effective overviews, reduced numbers of actions to accomplish tasks; and prompt, meaningful feedback for user actions. This article reviews these clever enhanced 3D-design features and encourages approaches that facilitate user tasks rather than mimic reality.},
	keywords = {3D interfaces, 3D reality, Atmosphere, Avatars, Cities and towns, Collaboration, Computer displays, Computer Graphics, error prevention, history keeping, information exploration, Information Visualization, movements, Navigation, occlusion, overviews, programming-by-demonstration, rapid situation awareness, Testing, usability, user action feedback, User interfaces, Virtual reality, Visualization},
	isbn = {0272-1716},
	doi = {10.1109/MCG.2003.1242376},
	author = {Shneiderman, Ben}
}
@conference {14896,
	title = {Finding structurally consistent motion correspondences},
	booktitle = {Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision Image Processing., Proceedings of the 12th IAPR International Conference on},
	volume = {1},
	year = {1994},
	month = {1994/10//},
	pages = {650 -653 vol.1 - 650 -653 vol.1},
	abstract = {Much work on deriving scene structure and motion from features assumes as input a set of tracked image features that share a common 3D motion. Producing this input requires segmenting independent motions, and detecting image features that do not correspond to 3D features, originating instead, for example in occlusion boundaries or specularities. We derive a linear program that tells when a set of tracked points might have come from 3D points that share a single motion, assuming affine motion and bounded error. We can also use linear programming to place conservative bounds on the structure of the scene that corresponds to tracked points. We implement and test this algorithm on real images},
	keywords = {3D, boundaries;, common, consistent, correspondences;, estimation;, features;, image, independent, linear, MOTION, motion;, occlusion, programming;, scene, segmentation;, specularities;, structurally, structure;, tracked},
	doi = {10.1109/ICPR.1994.576388},
	author = {Jacobs, David W. and Chennubhotla,C.}
}
