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International audience; Segmentation of the iris is one of the key modules of an iris recognition system. For this reason, it is critical to predict failures of this module. In this article we propose a new set of segmentation quality metrics dedicated this problem. We assess the quality of our metrics based on their ability to predict the intrinsic recognition performance of a segmented image. A straightforward fusion procedure then allows generating a global segmentation quality score.

International audience; This paper concerns the implementation of our online signature verification system on a mobile device. Verification involves confirming or denying a person's claimed identity. Our system is based on a Hidden Markov Model and outputs two complementary scores: the first one is related to the likelihood given by the HMM of the claimed identity; the second one is related to the segmentation given by such an HMM on the input signature. A claimed identity is confirmed when the arithmetic mean of the two scores obtained on such an input signature is higher than a threshold. Also, a personal normalization of the local parameters of the signature is carried out to make the system robust to changes of platforms. A patent was submitted with special emphasis on the latter claim. This system is implemented on a mobile platform PDA Qtek 2020 ARM 400 MHz. An acquisition interface is developed allowing an enrollment step of a person by acquisition of 5 of his/her signatures, and a verification step of a given signature of a registered person. Enrolment speed depends on the complexity of the signature, while verification is performed in real time. Performance assessment of our system, carried out on two databases acquired on a PDA, shows a degradation of system performance on mobile platform compared to a fixed platform. In order to improve the performance in the case of mobility, we propose a strategy for enhancing the quality of the reference signatures at the enrolment phase.

International audience; Our objective is to animate an embodied conversational agent (ECA) with communicative gestures rendered with the expressivity of a real human user it represents. We describe an approach to estimate a subset of expressivity parameters defined in the literature (namely spatial and temporal extent) from captured motion trajectories. We first validate this estimation against synthesis motion and then show results with real human motion. The estimated expressivity is then sent to the animation engine of an ECA that becomes a personalized autonomous representative of that user

International audience; We present a simple scheme with three main features: (1) it induces revocability in biometrics based user authentication systems, (2) protects the biometric information, and (3) improves the verification performance. The user's biometric feature vector is shuffled with a user specific shuffling key to transform into a revocable template. Comparison between different templates is carried out in the transformed domain. If the template is compromised, it can be replaced with another template obtained by changing the shuffling key. This scheme makes cross-matching between databases impossible by issuing different templates for different applications. The performance evaluation of the system is carried out on two modalities: iris and face using publicly available databases. This scheme significantly improves the verification performance of the underlying biometric system, e.g., it reduces the Equal Error Rate (EER) from 1.67% to 0.23% on the NIST-ICE iris database. The EER on the NIST-FRGCv2 face database reduces from 8.10% to zero

International audience; The Active Appearance Models and the derived Active Models (AM) allow to robustly track the face of a single user that was previously learnt, but works poorly with multiple or unknown users. Our research aims at improving the tracking robustness by learning from video databases. In this paper, we study the relation between the face texture and the parameter gradient matrix, and propose a statistical approach to dynamically fit the AM to unknown users by estimating the gradient and update matrices from the face texture. We have implemented this algorithm for real time face tracking and experimentally demonstrate its robustness when tracking multiple or unknown users' faces

International audience; 3D human motion capture by real-time monocular vision without using markers can be achieved by registering a 3D articulated model on a video. Registration consists in iteratively optimizing the match between primitives extracted from the model and the images with respect to the model position and joint angles. We extend a previous color-based registration algorithm with a more precise edge-based registration step. We present an experimental analysis of the residual error vs. the computation time and we discuss the balance between both approaches

International audience; We analyze teletraffic capacity performance of a WDM/DS-OCDMA Passive Optical Network. Hybrid WDM/DS-OCDMA PON is proposed to increase user capacity performance and to be a cost effective method per wavelength of a WDM PON. For each prime code used in this system, an appropriate simultaneous capacity threshold has been evaluated in a manner to ensure good transmission performance (BER~10− 9). Since this capacity threshold is inferior to the nominal resource capacity of the considered code, a soft blocking of the system has been determined even if resources in the system are still available. The teletraffic capacity of the WDM/DS-OCDMA system has been then analyzed under the maximum of soft blocking probability constraint for different prime codes. This value is dependent on the probability of channel activity factor. It is demonstrated that using extended quadratic congruent codes (EQC) with better correlation properties, causes the teletraffic capacity to be closer to the nominal teletraffic capacity.

International audience; In this paper, we present some results on multimodality implementation resulting from the VINSI (“Vérification d’Identité Numérique Sécurisée Itinérante” for Secured Mobile Digital Identity Verification) French project. The VINSI handheld terminal allows identity verification in mobile conditions (airport gates) using two biometrics usable in future biometric passports (fingerprint and face). We propose an incremental fusion strategy aiming at improving the global performance of the combined system over each individual recognizer while optimizing the cost resulting from the fusion. Indeed, in this kind of application, time and complexity optimization is essential. To this aim, we split the fingerprint scores’ range into different interest zones, on which we do not apply the same strategy depending on the relative quality of the modalities at hand. Results on a virtual database corresponding to VINSI applicative conditions (Combination of BIOMET fingerprints and FRGCv2 faces) show that this incremental fusion strategy allows the same improvement in performance as global fusion methods while significantly reducing the cost

International audience; The home remote monitoring systems aim to make a protective contribution to the well being of individuals (patients, elderly persons) requiring moderate amounts of support for independent living spaces, and improving their everyday life. Existing researches of these systems suffer from lack of experimental data and a standard medical database intended for their validation and improvement. This paper presents a multi-sensors environment for acquiring and recording a multimodal medical database, which includes physiological data (cardiac frequency, activity or agitation, posture, fall), environment sounds and localization data. It provides graphical interface functions to manage, process and index these data. The paper focuses on the system implementation, its usage and it points out possibilities for future work