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In this paper, we present the main results of the BioSecure Signature Evaluation Campaign (BSEC'2009). The objective of BSEC'2009 was to evaluate different online signature algorithms on two tasks: the first one aims at studying the influence of acquisition conditions (digitizing tablet or PDA) on systems' performance; the second one aims at studying the(More)
Authentication of individuals is rapidly becoming an important issue. On-line signature verification is one of the methods that use biometric features. This paper proposes a new HMM algorithm is for on-line signature verification. After preprocessing, input signature is discretized in a polar coordinate system. This particular discretization leads to a(More)
A camera-based online signature verification system is proposed in this paper. One web camera is used for data acquisition, and a sequential Monte Carlo method is used for tracking a pen tip. Several distances are computed from an online signature, and a fusion model trained by using Ad-aBoost combines the distances and computes a final score. Preliminary(More)
Camera-based gait recognition is a useful method for authenticating a person from a distance, even if the resolution of the acquired images is not high. However, different views of the compared gallery and probe decrease the recognition accuracy. To solve this problem, we propose a gait based authentication method that uses an arbitrary view transformation(More)
Gait recognition is a useful biometric trait for person authentication because it is usable even with low image resolution. One challenge is robustness to a view change (cross-view matching); view transformation models (VTMs) have been proposed to solve this. The VTMs work well if the target views are the same as their discrete training views. However, the(More)
This paper describes a method for multi-view multi-modal biometrics from a single walking image sequence. As multi-modal cues, we adopt not only face and gait but also the actual height of a person, all of which are simultaneously captured by a single camera. As multi-view cues, we use the variation in the observation views included in a single image(More)