Abstract

Abstract-A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008.

The estimation of time to impact is of vital importance for animals as well as for autonomous robots. The optical ow, which is the two-dimensional projection on the retinal plane of the relative, three-dimensional motion between the observer and the objects in the scene can be used to estimate the time to impact. In this paper the application of an anthropomorphic, retina-like visual sensor and the advantages of polar and log-polar mapping for visual navigation are investigated. From a static view point the main advantage of a log-polar sensor, apart from the shape invariance property to scaling and rotations ?, ?] stems from the considerable data reduction obtained with the non-uniform sampling, in conjunction with a high resolution in the central part of the eld of view (which, if properly directed, corresponds to the focus of attention). Considering a dynamic image sequence, there are further advantages in performing the log-polar transformation. In this paper we demonstrate that the motion equations that relate the egomotion and/or the motion of the objects in the scene to the optical ow are considerably simpli ed if the velocity is represented in a polar coordinate system. The analysis is conducted for tracking egomotion, but is then generalized to arbitrary sensor and object motion. The main result stems from the abundance of equations that can be written directly relating the polar optical ow with the time-toimpact. Finally, it is shown how the equations can be generalized to process images digitized with a conventional raster CCD array. Experiments performed on images acquired from real scenes are also presented.

Abstract-This paper presents a new face identification system based on Graph Matching Technique on SIFT features extracted from face images. Although SIFT features have been successfully used for general object detection and recognition, only recently they were applied to face recognition. This paper further investigates the performance of identification techniques based on Graph matching topology drawn on SIFT features which are invariant to rotation, scaling and translation. Face projections on images, represented by a graph, can be matched onto new images by maximizing a similarity function taking into account spatial distortions and the similarities of the local features. Two graph based matching techniques have been investigated to deal with false pair assignment and reducing the number of features to find the optimal feature set between database and query face SIFT features. The experimental results, performed on the BANCA database, demonstrate the effectiveness of the proposed system for automatic face identification.

Innovation has formed much of the rich history in biometrics. The field of soft biometrics was originally aimed to augment the recognition process by fusion of metrics that were sufficient to discriminate populations rather than individuals. This was later refined to use measures that could be used to discriminate individuals, especially using descriptions that can be perceived using human vision and in surveillance imagery. A further branch of this new field concerns approaches to estimate soft biometrics, either using conventional biometrics approaches or just from images alone. These three strands combine to form what is now known as soft biometrics. We survey the achievements that have been made in recognition by and in estimation of these parameters, describing how these approaches can be used and where they might lead to. The approaches lead to a new type of recognition, and one similar to Bertillonage which is one of the earliest approaches to human identification.