@conference {12556,
	title = {Multi-biometric cohort analysis for biometric fusion},
	booktitle = {Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on},
	year = {2008},
	month = {2008/04/31/4},
	pages = {5224 - 5227},
	abstract = {Biometric matching decisions have traditionally been made based solely on a score that represents the similarity of the query biometric to the enrolled biometric(s) of the claimed identity. Fusion schemes have been proposed to benefit from the availability of multiple biometric samples (e.g., multiple samples of the same fingerprint) or multiple different biometrics (e.g., face and fingerprint). These commonly adopted fusion approaches rarely make use of the large number of non-matching biometric samples available in the database in the form of other enrolled identities or training data. In this paper, we study the impact of combining this information with the existing fusion methodologies in a cohort analysis framework. Experimental results are provided to show the usefulness of such a cohort-based fusion of face and fingerprint biometrics.},
	keywords = {(access, analysis;biometrics, biometric, biometrics;fingerprint, biometrics;multi-biometric, cohort, control);face, data;, decisions;face, fusion;biometric, identification;security, MATCHING, of, recognition;fingerprint},
	doi = {10.1109/ICASSP.2008.4518837},
	author = {Aggarwal,G. and Ratha,N. K and Bolle, R.M. and Chellapa, Rama}
}
@article {12572,
	title = {Signal Processing for Biometric Systems [DSP Forum]},
	journal = {Signal Processing Magazine, IEEE},
	volume = {24},
	year = {2007},
	month = {2007/11//},
	pages = {146 - 152},
	abstract = {This IEEE signal processing magazine (SPM) forum discuses signal processing applications, technologies, requirements, and standardization of biometric systems. The forum members bring their expert insights into issues such as biometric security, privacy, and multibiometric and fusion techniques. The invited forum members are Prof. Anil K. Jain of Michigan State University, Prof. Rama Chellappa of the University of Maryland, Dr. Stark C. Draper of theUniversity of Wisconsin in Madison, Prof. Nasir Memon of Polytechnic University, and Dr. P. Jonathon Phillips of the National Institute of Standards and Technology. The moderator of the forum is Dr. Anthony Vetro of Mitsubishi Electric Research Labs, and associate editor of SPM.},
	keywords = {(access, biometric, control);security;signal, forum;signal, magazine, PROCESSING, processing;, security;biometric, standardization;fusion, systems, technique;multibiometric, technique;signal, technology;biometrics},
	isbn = {1053-5888},
	doi = {10.1109/MSP.2007.905886},
	author = {Jain, A.K. and Chellapa, Rama and Draper, S.C. and Memon, N. and Phillips,P.J. and Vetro, A.}
}
@conference {12578,
	title = {Video Biometrics},
	booktitle = {Image Analysis and Processing, 2007. ICIAP 2007. 14th International Conference on},
	year = {2007},
	month = {2007/09//},
	pages = {363 - 370},
	abstract = {A strong requirement to come up with secure and user- friendly ways to authenticate and identify people, to safeguard their rights and interests, has probably been the main guiding force behind biometrics research. Though a vast amount of research has been done to recognize humans based on still images, the problem is still far from solved for unconstrained scenarios. This has led to an increased interest in using video for the task of biometric recognition. Not only does video provide more information, but also is more suitable for recognizing humans in general surveillance scenarios. Other than the multitude of still frames, video makes it possible to characterize biometrics based on inherent dynamics like gait which is not possible with still images. In this paper, we describe several recent algorithms to illustrate the usefulness of videos to identify humans. A brief discussion on remaining challenges is also included.},
	keywords = {(access, analysis;video, biometrics;biometrics, control);face, dynamics;ofbiometric, images;surveillance, inherent, MOTION, processing;, recognition;image, recognition;still, scenarios;unconstrained, scenarios;video, signal},
	doi = {10.1109/ICIAP.2007.4362805},
	author = {Chellapa, Rama and Aggarwal,G.}
}
@conference {18226,
	title = {Image Tampering Identification using Blind Deconvolution},
	booktitle = {Image Processing, 2006 IEEE International Conference on},
	year = {2006},
	month = {2006/10//},
	pages = {2309 - 2312},
	abstract = {Digital images have been used in growing number of applications from law enforcement and surveillance, to medical diagnosis and consumer photography. With such widespread popularity and the presence of low-cost image editing softwares, the integrity of image content can no longer be taken for granted. In this paper, we propose a novel technique based on blind deconvolution to verify image authenticity. We consider the direct output images of a camera as authentic, and introduce algorithms to detect further processing such as tampering applied to the image. Our proposed method is based on the observation that many tampering operations can be approximated as a combination of linear and non-linear components. We model the linear part of the tampering process as a filter, and obtain its coefficients using blind deconvolution. These estimated coefficients are then used to identify possible manipulations. We demonstrate the effectiveness of the proposed image authentication technique and compare our results with existing works},
	keywords = {(access, approximation;blind, authentication;image, coding;, compression;deconvolution;filtering, control);data, deconvolution;camera;consumer, diagnosis;surveillance;tampering, editing, identification;approximation, images;filter, photography;digital, process;image, softwares;medical, theory;biometrics, theory;image},
	doi = {10.1109/ICIP.2006.312848},
	author = {Swaminathan,A. and M. Wu and Liu,K. J.R}
}
@conference {12728,
	title = {Towards a view invariant gait recognition algorithm},
	booktitle = {Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2003.},
	year = {2003},
	month = {2003/07//},
	pages = {143 - 150},
	abstract = {Human gait is a spatio-temporal phenomenon and typifies the motion characteristics of an individual. The gait of a person is easily recognizable when extracted from a side-view of the person. Accordingly, gait-recognition algorithms work best when presented with images where the person walks parallel to the camera image plane. However, it is not realistic to expect this assumption to be valid in most real-life scenarios. Hence, it is important to develop methods whereby the side-view can be generated from any other arbitrary view in a simple, yet accurate, manner. This is the main theme of the paper. We show that if the person is far enough from the camera, it is possible to synthesize a side view (referred to as canonical view) from any other arbitrary view using a single camera. Two methods are proposed for doing this: (i) using the perspective projection model; (ii) using the optical flow based structure from motion equations. A simple camera calibration scheme for this method is also proposed. Examples of synthesized views are presented. Preliminary testing with gait recognition algorithms gives encouraging results. A by-product of this method is a simple algorithm for synthesizing novel views of a planar scene.},
	keywords = {(access, algorithm;, analysis;, Biometrics, biometrics;, Calibration, calibration;, camera, canonical, control);, equations;, flow;, Gait, gait;, human, image, invariant, model;, MOTION, optical, perspective, phenomenon;, projection, recognition, scheme;, sequences;, spatio-temporal, view, view;},
	doi = {10.1109/AVSS.2003.1217914},
	author = {Kale, A. and Chowdhury, A.K.R. and Chellapa, Rama}
}
@conference {12735,
	title = {Video synthesis of arbitrary views for approximately planar scenes},
	booktitle = {Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP {\textquoteright}03). 2003 IEEE International Conference on},
	volume = {3},
	year = {2003},
	month = {2003/04//},
	pages = {III - 497-500 vol.3 - III - 497-500 vol.3},
	abstract = {In this paper, we propose a method to synthesize arbitrary views of a planar scene, given a monocular video sequence. The method is based on the availability of knowledge of the angle between the original and synthesized views. Such a method has many important applications, one of them being gait recognition. Gait recognition algorithms rely on the availability of an approximate side-view of the person. From a realistic viewpoint, such an assumption is impractical in surveillance applications and it is of interest to develop methods to synthesize a side view of the person, given an arbitrary view. For large distances from the camera, a planar approximation for the individual can be assumed. In this paper, we propose a perspective projection approach for recovering the direction of motion of the person purely from the video data, followed by synthesis of a new video sequence at a different angle. The algorithm works purely in the image and video domain, though 3D structure plays an implicit role in its theoretical justification. Examples of synthesized views using our method and performance evaluation are presented.},
	keywords = {(access, 3D, applications;, approach;, approximately, approximation;, arbitrary, Biometrics, control);, data;, direction, estimation;, evaluation;, Gait, image, monocular, MOTION, performance, perspective, planar, processing;, projection, recognition;, recovery;, scenes;, sequence;, sequences;, side, signal, structure;, Surveillance, surveillance;, synthesis;, synthesized, video, view, views;},
	doi = {10.1109/ICASSP.2003.1199520},
	author = {Chowdhury, A.K.R. and Kale, A. and Chellapa, Rama}
}
