Publications

Distributed surveillance systems are nowadays widely adopted to monitor large areas for security purposes. In this paper, we present a complete multicamera system designed for people tracking from multiple partially overlapped views and capable of inferring and detecting abnormal people trajectories. Detection and tracking are performed by means of background suppression and an appearance-based probabilistic approach. Objects' label ambiguities are geometrically solved and the concept of "normality" is learned from data using a robust statistical model based on Von Mises distributions. Abnormal trajectories are detected using a first-order Bayesian network and, for each abnormal event, the appearance of the subject from each view is logged. Experiments demonstrate that our system can process with real-time performance up to three cameras simultaneously in an unsupervised setup and under varying environmental conditions.

This paper proposes the exploitation of a dynamic programming technique for efficiently comparing people trajectories adopting an encoding scheme that jointly takes into account both the direction and the velocity of movement. With this approach, each pair of trajectories in the training set is compared and the corresponding distance computed. Clustering is achieved by using the k-medoids algorithm and each cluster is modeled with a 1-D Gaussian over the distance from the medoid. A MAP framework is adopted for the testing phase. The reported results are encouraging.

In-house video surveillance can represent an excellent support for people with some difficulties (e.g. elderly or disabled people) living alone and with a limited autonomy. New hardware technologies and in particular digital cameras are now affordable and they have recently gained credit as tools for (semi-)automatically assuring people's safety. In this paper a multi-camera vision system for detecting and tracking people and recognizing dangerous behaviours and events such as a fall is presented. In such a situation a suitable alarm can be sent, e.g. by means of an SMS. A novel technique of warping people's silhouette is proposed to exchange visual information between partially overlapped cameras whenever a camera handover occurs. Finally, a multi-client and multi-threaded transcoding video server delivers live video streams to operators/remote users in order to check the validity of a received alarm. Semantic and event-based transcoding algorithms are used to optimize the bandwidth usage. A two-room setup has been created in our laboratory to test the performance of the overall system and some of the results obtained are reported.

This paper presents a open-source system for low-latency video streaming on PDAs, specifically addressing mobile video surveillance requirements. The system is based on H.264 and suitably modified to obtain the best trade-off between image quality and video fluidity, working also at very limited bandwidths. Moreover, the used con- trols allow to keep the number of lost frames very low. A large set of experiments and comparisons have been carried out and the achieved results demonstrate the efficacy and efficiency of our system.

Background: To overcome subjectivity and variability in the interpretation of dermoscopic images, image analysis programs, enabling the numerical description of melanocytic lesion images, have been developed. Objectives: Our aim was to assess a method for the description of colours in melanocytic lesion images, based on the subdivision of image colours into red, green and blue clusters. Methods: Melanomas and naevi of the test set were described by means of 23 colour clusters previously selected by a training set comprising 369 melanocytic lesion images. The diagnostic performance obtained by this automated method was compared to sensitivity and specificity of diagnosis of 4 dermatologists. Results: Colour cluster values significantly differed between melanomas and naevi. Moreover, sensitivity and specificity values of computer diagnosis were similar to those achieved by the dermatologists. Conclusion: Our image analysis program based on the assessment of one single parameter has the diagnostic accuracy of dermatologists employing dermoscopy on a regular basis.

In this work, we propose a system for shot comparison directly working on the MPEG-1 stream in the compressed domain, extracting both color, texture and motion features considering all frames with a reasonable computational cost, and results comparable to those obtained on uncompressed keyframes. In particular a summary descriptor for each Group Of Pictures (GOP) is computed and employed for shot characterization and comparison. The Mallows distance allows to match different length clips in a unified framework.

Sketch-based image retrieval systems need to handle two main problems. First of all, they have to recognize shapes similar but not necessarily identical to the user’s query. Hence, exact object identification techniques do not fit in this case. The second problem is the selection of the image features to compare with the user’s sketch. In domain-independent visual repositories, real-life images with non-uniform background and possible occluding objects make this second task particularly hard. We address the second problem proposing a variant of the well-known Generalized Hough Transform (GHT), which is a robust object identification technique for unsegmented images. Moreover, we solve the first problem modifying the GHT to deal with an inexact matching problem. In this paper, we show how this idea can be efficiently and accurately realized. Experimental results are shown with two different databases of real, unsegmented images.