A survey of face detection, extraction and recognition

The goal of this paper is to present a critical survey of existing literatures on human face recognition over the last 4-5 years. Interest and research activities in face recognition have increased significantly over the past few years, especially after the American airliner tragedy on September 11 in 2001. While this growth largely is driven by growing application demands, such as static matching of controlled photographs as in mug shots matching, credit card verification to surveillance video images, identification for law enforcement and authentication for banking and security system access, advances in signal analysis techniques, such as wavelets and neural networks, are also important catalysts. As the number of proposed techniques increases, survey and evaluation becomes important

Signal Processing Research Program

Contains table of contents for Part III, table of contents for Section 1, an introduction and reports on fourteen research projects.Charles S. Draper Laboratory Contract DL-H-404158U.S. Navy - Office of Naval Research Grant N00014-89-J-1489National Science Foundation Grant MIP 87-14969Battelle LaboratoriesTel-Aviv University, Department of Electronic SystemsU.S. Army Research Office Contract DAAL03-86-D-0001The Federative Republic of Brazil ScholarshipSanders Associates, Inc.Bell Northern Research, Ltd.Amoco Foundation FellowshipGeneral Electric FellowshipNational Science Foundation FellowshipU.S. Air Force - Office of Scientific Research FellowshipU.S. Navy - Office of Naval Research Grant N00014-85-K-0272Natural Science and Engineering Research Council of Canada - Science and Technology Scholarshi

A Statistical Approach To View Synthesis

View Synthesis is the challenging problem of predicting a new view or pose of an object given an exemplar view or set of views. This thesis presents a novel approach for the problem of view synthesis. The proposed method uses global features rather than local geometry to achieve an effect similar to that of the well known view morphing method . While previous approaches to the view synthesis problem have shown impressive results, they are highly dependent on being able to solve for epipolar geometry and therefore have a very precise correspondence between reference images. In cases where this is not possible such as noisy data, low contrast data, or long wave infrared data an alternative approach is desirable. Here two problems will be considered. The proposed view synthesis method will be used to synthesis new views given a set of reference views. Additionally the algorithm will be extended to synthesis new lighting conditions and thermal signatures. Finally the algorithm will be applied toward enhancing the ATR problem by creating additional training data to increase the likelihood of detection and classification

Electrocardiogram pattern recognition and analysis based on artificial neural networks and support vector machines: a review.

Computer systems for Electrocardiogram (ECG) analysis support the clinician in tedious tasks (e.g., Holter ECG monitored in Intensive Care Units) or in prompt detection of dangerous events (e.g., ventricular fibrillation). Together with clinical applications (arrhythmia detection and heart rate variability analysis), ECG is currently being investigated in biometrics (human identification), an emerging area receiving increasing attention. Methodologies for clinical applications can have both differences and similarities with respect to biometrics. This paper reviews methods of ECG processing from a pattern recognition perspective. In particular, we focus on features commonly used for heartbeat classification. Considering the vast literature in the field and the limited space of this review, we dedicated a detailed discussion only to a few classifiers (Artificial Neural Networks and Support Vector Machines) because of their popularity; however, other techniques such as Hidden Markov Models and Kalman Filtering will be also mentioned