TY - CONF T1 - Multi-biometric cohort analysis for biometric fusion T2 - Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on Y1 - 2008 A1 - Aggarwal,G. A1 - Ratha,N. K A1 - Bolle, R.M. A1 - Chellapa, Rama KW - (access KW - analysis;biometrics KW - biometric KW - biometrics;fingerprint KW - biometrics;multi-biometric KW - cohort KW - control);face KW - data; KW - decisions;face KW - fusion;biometric KW - identification;security KW - MATCHING KW - of KW - recognition;fingerprint AB - 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. JA - Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on M3 - 10.1109/ICASSP.2008.4518837 ER - TY - JOUR T1 - Signal Processing for Biometric Systems [DSP Forum] JF - Signal Processing Magazine, IEEE Y1 - 2007 A1 - Jain, A.K. A1 - Chellapa, Rama A1 - Draper, S.C. A1 - Memon, N. A1 - Phillips,P.J. A1 - Vetro, A. KW - (access KW - biometric KW - control);security;signal KW - forum;signal KW - magazine KW - PROCESSING KW - processing; KW - security;biometric KW - standardization;fusion KW - systems KW - technique;multibiometric KW - technique;signal KW - technology;biometrics AB - 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. VL - 24 SN - 1053-5888 CP - 6 M3 - 10.1109/MSP.2007.905886 ER - TY - CONF T1 - Video Biometrics T2 - Image Analysis and Processing, 2007. ICIAP 2007. 14th International Conference on Y1 - 2007 A1 - Chellapa, Rama A1 - Aggarwal,G. KW - (access KW - analysis;video KW - biometrics;biometrics KW - control);face KW - dynamics;ofbiometric KW - images;surveillance KW - inherent KW - MOTION KW - processing; KW - recognition;image KW - recognition;still KW - scenarios;unconstrained KW - scenarios;video KW - signal AB - 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. JA - Image Analysis and Processing, 2007. ICIAP 2007. 14th International Conference on M3 - 10.1109/ICIAP.2007.4362805 ER - TY - CONF T1 - Image Tampering Identification using Blind Deconvolution T2 - Image Processing, 2006 IEEE International Conference on Y1 - 2006 A1 - Swaminathan,A. A1 - M. Wu A1 - Liu,K. J.R KW - (access KW - approximation;blind KW - authentication;image KW - coding; KW - compression;deconvolution;filtering KW - control);data KW - deconvolution;camera;consumer KW - diagnosis;surveillance;tampering KW - editing KW - identification;approximation KW - images;filter KW - photography;digital KW - process;image KW - softwares;medical KW - theory;biometrics KW - theory;image AB - 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 JA - Image Processing, 2006 IEEE International Conference on M3 - 10.1109/ICIP.2006.312848 ER - TY - CONF T1 - Towards a view invariant gait recognition algorithm T2 - Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2003. Y1 - 2003 A1 - Kale, A. A1 - Chowdhury, A.K.R. A1 - Chellapa, Rama KW - (access KW - algorithm; KW - analysis; KW - Biometrics KW - biometrics; KW - Calibration KW - calibration; KW - camera KW - canonical KW - control); KW - equations; KW - flow; KW - Gait KW - gait; KW - human KW - image KW - invariant KW - model; KW - MOTION KW - optical KW - perspective KW - phenomenon; KW - projection KW - recognition KW - scheme; KW - sequences; KW - spatio-temporal KW - view KW - view; AB - 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. JA - Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2003. M3 - 10.1109/AVSS.2003.1217914 ER - TY - CONF T1 - Video synthesis of arbitrary views for approximately planar scenes T2 - Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on Y1 - 2003 A1 - Chowdhury, A.K.R. A1 - Kale, A. A1 - Chellapa, Rama KW - (access KW - 3D KW - applications; KW - approach; KW - approximately KW - approximation; KW - arbitrary KW - Biometrics KW - control); KW - data; KW - direction KW - estimation; KW - evaluation; KW - Gait KW - image KW - monocular KW - MOTION KW - performance KW - perspective KW - planar KW - processing; KW - projection KW - recognition; KW - recovery; KW - scenes; KW - sequence; KW - sequences; KW - side KW - signal KW - structure; KW - Surveillance KW - surveillance; KW - synthesis; KW - synthesized KW - video KW - view KW - views; AB - 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. JA - Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on VL - 3 M3 - 10.1109/ICASSP.2003.1199520 ER -