Biometric systems based on human traits like fingerprinting, face, iris, etc., even widely explored in literature, cannot be used in scenarios like video surveillance of crowded envinroments. A different class of biometry, usually referred as soft biometry, including individual's height, weight, skin color, clothes color, trajectory, etc., can be more easily extracted from cameras in a large network to provide some useful information about the users. In this work we focus our attention on the color of human clothes. We apply color based soft biometric to a specific scenario, i.e. to prevent hooligans fights, based on the color of the clothes they wear. A video surveillance system able to quickly identify the presence of rival teams fans in a specific location would be helpful in avoiding vandalism and destructive behaviour.

In multimedia applications, there has been an increasing interest in the use of quality measures based on human perception; however, research has not dealt with distortions due to geometric transformations. In this paper, we propose a method to objectively assess the perceptual quality of geometrically distorted images, based on image features processed by human vision. The proposed approach is a full-reference image quality metric focusing on the problem of local geometric distortions and is based on the use of Gabor filters that have received considerable attention because the characteristics of certain cells in the visual cortex of some mammals can be approximated by these filters. The novelty of the proposed technique is that it considers both the displacement field describing the distortion and the structure of the image. The experimental results show the good performances of the proposed metric.

In this paper a methodology for understanding the effectiveness of motion estimation techniques is presented. Unlike other performances evaluation systems, that are based on measuring the errors between the actual and the predicted displacements, the proposed technique is inspired to the Human Visual System. More in detail, the perceptual impact of geometric distortions induced by non accurate motion estimation is considered by means of an objective measure of the perceived distortion impact. Some of the most common block-based motion estimation algorithms have been tested. For each of them the performances have been evaluated by comparing the proposed metric with the state of the art metrics. A subjective experiment has been performed to assess the effectiveness of the estimation algorithms from a perceptual point of view. The obtained results show that the scores obtained with the tested metrics generally do not match with the perceived quality, while the proposed methodology does. Therefore, the presented tool can be used in the design and in the verification of a generic motion estimation algorithm.

Geometric transformations are known to be one of the most serious threats against any digital watermarking scheme. The goal of this work is to design an objective measurement scheme for geometric distortions in order to investigate the perceptual quality impact of geometric attacks on the watermarked images. The proposed approach is a full-reference image quality metric focusing on the problem of local geometric attacks and it is based on the use of Gabor filters. The novelty of the proposed metric is that it considers both the displacement field describing the distortion and the structure of the image.The experimental results show the good performances of the metric.

The use of digital watermarking in real applications is impeded by the weakness of current available algorithms against signal processing manipulations leading to the desynchronization of the watermark embedder and detector. For this reason, the problem of watermarking under geometric attacks has received considerable attention throughout recent years. Despite their importance, only few classes of geometric attacks are considered in the literature, most of which consist of global geometric attacks. The random bending attack contained in the Stirmark benchmark software is the most popular example of a local geometric transformation. In this paper, we introduce two new classes of local desynchronization attacks (DAs). The effectiveness of the new classes of DAs is evaluated from different perspectives including perceptual intrusiveness and desynchronization efficacy. This can be seen as an initial effort towards the characterization of the whole class of perceptually admissible DAs, a necessary step for the theoretical analysis of the ultimate performance reachable in the presence of watermark desynchronization and for the development of a new class of watermarking algorithms that can efficiently cope with them.