On the use of simple geometric descriptors provided by RGB-D sensors for re-identification

[EN]The re-identification problem has been commonly accomplished using appearance features based on salient points and color information. In this paper, we focus on the possibilities that simple geometric features obtained from depth images captured with RGB-D cameras may offer for the task, particularly working under severe illumination conditions. The results achieved for different sets of simple geometric features extracted in a top-view setup seem to provide useful descriptors for the re-identification task, which can be integrated in an ambient intelligent environment as part of a sensor network.

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 human perception and geometric restrictions for automatic pedestrian detection

[EN]Automatic detection systems do not perform as well as human observers, even on simple detection tasks. A potential solution to this problem is training vision systems on appropriate regions of interests (ROIs), in contrast to training on predefined and arbitrarily selected regions. Here we focus on detecting pedestrians in static scenes. Our aim is to answer the following question: Can automatic vision systems for pedestrian detection be improved by training them on perceptually-defined ROIs?