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.

Multiple face detection at different resolutions for perceptual user interfaces

[EN]This paper describes in detail a real-time multiple face detection system for video streams. The system adds to the good performance provided by a window shift approach, the combination of different cues available in video streams due to temporal coherence. The results achieved by this combined solution outperform the basic face detector obtaining a 98% success rate for around 27000 images, providing additionally eye detection and a relation between the successive detections in time by means of detection threads.

Who are you?

[EN]Most automatic recognition systems are focused on recognizing, given a single mug-shot of an individual, any new image of that individual. Most verification systems are designed to authenticate an identity provided by the user. However, the previous work rarely focus on the problem of detecting when a new individual, i.e., an unknown one, is present. The goal of the work presented in this paper deals with the possibility of providing the system with basic tools to detect when a new individual starts an interactive session, in order to allow the system to add or improve an identity model in the database. Experiments carried out with a set of 36 different individuals show promising results.