Sistema biométrico de detección facial sobre vídeo basado en patrones binarios locales aplicados sobre el color

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Transformaciones basadas en el algoritmo Local Binary Pattern de imágenes capturadas con la Kinect para clasificación facial

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

A comparison of face and facial feature detectors based on the viola-jones general object detection framework

[EN]The human face provides useful information during interaction; therefore, any system integrating Vision- BasedHuman Computer Interaction requires fast and reliable face and facial feature detection. Different approaches have focused on this ability but only open source implementations have been extensively used by researchers. A good example is the Viola–Jones object detection framework that particularly in the context of facial processing has been frequently used.

A video database for facial behavior understanding

[EN]The use of new technologies in order to step up the inter- action between humans and machines is the main proof that faces are important in videos. Therefore we suggest a novel Face Video Database for development, testing and veri cation of algorithms related to face- based applications and to facial recognition applications. In addition of facial expression videos, the database includes body videos. The videos are taken by three di erent cameras, working in real time, without vary- ing illumination conditions.

Competition on counter measures to 2-D facial spoofing attacks

[EN]Spoofing identities using photographs is one of the most common techniques to attack 2-D face recognition systems. There seems to exist no comparative stud- ies of di erent techniques using the same protocols and data. The motivation behind this competition is to com- pare the performance of di erent state-of-the-art algo- rithms on the same database using a unique evaluation method. Six di erent teams from universities around the world have participated in the contest.

Combining face and facial feature detectors for face detection performance improvement

[EN]In this paper, we experimentally study the combination of face and facial feature detectors to improve face detection performance. The face detection problem, as suggeted by recent face detection challenges, is still not solved. Face detectors traditionally fail in large-scale problems and/or when the face is occluded or di erent head rotations are present. The combination of face and facial feature detectors is evaluated with a public database. The obtained results evidence an improvement in the positive detection rate while reducing the false detection rate. Additionally, we prove that the integration of facial feature detectors provides useful information for pose estimation and face alignment.

Automatic initialization for facial analysis in interactive robotics

[EN]This paper focuses on four different initialization methods for determining the initial shape for the AAM algorithm and their particular performance in two different classification tasks with respect to either the facial expression DaFEx database and to the real world data obtained from a robot’s point of view.

An analysis of facial description in static images and video streams

[ES]This paper describes an analysis performed for facial description in static images and video streams. The still image context is first analyzed in order to decide the optimal classifier configuration for each problem: gender recognition, race classification, and glasses and moustache presence. These results are later applied to significant samples which are automatically extracted in real-time from video streams achieving promising results in the facial description of 70 individuals by means of gender, race and the presence of glasses and moustache.