Talking-Face Identity Verification, Audiovisual Forgery, and Robustness Issues

The robustness of a biometric identity verification (IV) system is best evaluated by monitoring its behavior under impostor attacks. Such attacks may include the transformation of one, many, or all of the biometric modalities. In this paper, we present the transformation of both speech and visual appearance of a speaker and evaluate its effects on the IV system. We propose MixTrans, a novel method for voice transformation. MixTrans is a mixture-structured bias voice transformation technique in the cepstral domain, which allows a transformed audio signal to be estimated and reconstructed in the temporal domain. We also propose a face transformation technique that allows a frontal face image of a client speaker to be animated. This technique employs principal warps to deform defined MPEG-4 facial feature points based on determined facial animation parameters (FAPs). The robustness of the IV system is evaluated under these attacks

Profiling user color perception for image retrieving

International audienceThe aim of this work is to build a user profile according to his own perception of colors for image retrieving. Images are being processed relying on a standard or initial set of parameters using the fuzzy set theory and the HLS color space (Hue, Lightness, and Saturation). We developed a dynamic construction of the user profile, which will increase his satisfaction by being more personalized and accommodated to his particular needs. We suggest two methods to define the perception and transform it into a profile; the first method is achieved by querying the user and getting answers, which will guide through the process of implementation of the profile; the second method is achieved by comparing different subjects and ending up by an appropriate aggregation. We also present a method that will recalculate the amount of colors in the image based on another set of parameters, so the colorimetric profile of the image is being modified accordingly. Avoiding the repetition of the process at the pixel level is the main target of this phase, because reprocessing each image is time consuming and turned to be not feasible

Modeling personal perception into user profile for image retrieving

International audienceThe aim of this paper is to build a user profile according to his own perception. We focus on the dynamic construction of the profile, which will increase the satisfaction of the user by being more personalized and accommodated to his particular needs. We suggest two methods to define the perception and transform it into a profile; the first method is achieved by querying the user and getting answers, which will guide through the process of implementation of the profile; the second method is achieved by comparing different subjects and ending up by an appropriate choice. As a case study, we took the example of color perception. We rely on fuzzy logic to represent the different aspects of color and to formulate the questions and answers

Color Image Profile Comparison and Computing

International audienceThis paper describes a method that analyzes the content of images while building their colorimetric profile as perceived by the user. First, images are being processed relying on a standard or initial set of parameters using the fuzzy set theory and the HLS color space (Hue, Lightness, Saturation). These parameters permit to describe and qualify the colors and their properties. Each image is processed pixel by pixel and is affected to a detailed initial colorimetric profile. Secondly, we present a method that will recalculate the amount of colors in the image based on another set of parameters, so the colorimetric profile of the image is being modified accordingly. Avoiding the repetition of the process at the pixel level is the main target of this phase, because reprocessing each image is time consuming and turned to be not feasible. Finally we present the software that processes images and that recalculates their colorimetric profiles with some examples