Publications

Classifying video elements according to some pre-defined ontology of the video content is the typical way to perform video annotation. Ontologies are built by defining relationship between linguistic terms that describe domain concepts at different abstraction levels. Linguistic terms are appropriate to distinguish specific events and object categories but they are inadequate when they must describe video entities or specific patterns of events. In these cases visual prototypes can better express pattern specifications and the diversity of visual events. To support video annotation up to the level of pattern specification enriched ontologies, that include visual concepts together with linguistic keywords, are needed. This paper presents Pictorially Enriched ontologies and provides a solution for their implementation in the soccer video domain. The pictorially enriched ontology created is used both to directly assign multimedia objects to concepts, providing a more meaningful definition than the linguistics terms, and to extend the initial knowledge of the domain, adding subclasses of highlights or new highlight classes that were not defined in the linguistic ontology. Automatic annotation of soccer clips up to the pattern specification level using a pictorially enriched ontology is discussed. © Springer-Verlag Berlin Heidelberg 2005.

Semantic video adaptation improves traditional adaptation by taking into account the degree of relevance of the different portions of the content. It employs solutions to detect the significant parts of the video and applies different compression ratios to elements that have different importance. Performance of semantic adaptation heavily depends on the quality and precision of the automatic annotation, whether it operates in strict or nonstrict real time, and the codec which is used to perform adaptation at the event or object level. It should consider the effects of the errors in the automatic extraction of objects and events over the operation of the adaptation subsystem, and relate these effects to the preferences for the objects and events of the video program, that have been decided by the user. In this paper, we present strict real time annotation and adaptation of sports video and introduce two new performance measures: Viewing Quality Loss and Bit-rate Cost Increase, that are obtained from classical PSNR and Bit Ratio, but relate the results of semantic adaptation with the user’s preferences and expectations.

Efficient solution to people tracking in distributed videosurveillance is requested to monitor crowded and large environments.This paper proposes a novel use of the EntryEdges of Field of View (E2oFoV) to solve the consistentlabeling problem between partially overlapped views. Anautomatic and reliable procedure allows to obtain the homographictransformation between two overlapped views,without any manual calibration of the cameras. Throughthe homography, the consistent labeling is established eachtime a new track is detected in one of the cameras. A CameraTransition Graph (CTG) is defined to speed up the establishmentprocess by reducing the search space. Experimentalresults prove the effectiveness of the proposed solutionalso in challenging conditions.

Many techniques and models have been proposed for vehicles surveillance in highways. In the past, tracking algorithms based on Kalman filter have been largely usedfor their efficiency in the prediction and low computationalcost. However, predictive filters can not solve long-lastingocclusions. In this paper, we propose a new mixed predictiveand probabilistic tracking that exploits the advantagesof predictive filters for moving vehicles and adopts probabilistic and appearance-based tracking for stopped vehicles. The proposed tracking is part of a complete videosurveillance system, oriented to control tunnels and highwaysfrom cluttered views, that is implemented in an embeddedDSP platform and provides background suppression,a novel shadow detection algorithm, tracking, and scenerecognition module. The experimental results are obtainedover several hours of videos acquired in pre-existing platforms of CCTV surveillance systems.

In this paper, we present a new approach to multi-camera object tracking based on the consistent labeling. An automatic and reliable procedure allows to obtain the homographic transformation between two overlapped views, without any manual calibration of the cameras. Object's positions are matched by using the homography when the object is firstly detected in one of the two views. The approach has been tested also in the case of simultaneous transitions and in the case in which people are detected as a group during the transition. Promising results are reported over a real setup of overlapped cameras.

Tools for the interpretation of significant events from video and video clip adaptation can effectively support automatic extraction and distribution of relevant content from video streams. In fact, adaptation can adjust meaningful content, previously detected and extracted, to the user/client capabilities and requirements. The integration of these two functions is increasingly important, due to the growing demand of multimedia data from remote clients with limited resources (PDAs, HCCs, Smart phones). In this paper we propose an unified framework for event-based and object-based semantic extraction from video and semantic on-line adaptation. Two cases of application, highlight detection and recognition from soccer videos and people behavior detection in domotic* applications, are analyzed and discussed.

Background/purpose: The assessment of colors is essential for melanoma (MM) diagnosis, both for pattern analysis on dermoscopic images, and when using semiquantitative methods. Our aim was to provide a simple, precise characterization and reproducible calibration of the color response for dermoscopic instruments. Methods: Three processes were used to correct the non-uniform illumination pattern of the instrument, to easily estimate the camera gamma settings and to describe the color space conversion matrices required to produce standard images, in any color space. A specific color space was also developed to optimize the representation of dermatoscopic colors. The calibration technique was tested both on synthetic reference surfaces and on real images by comparing the difference between the images colors obtained with two different equipments. Results: The differences between the images acquired by means of the two instruments, calculated on the reference patterns after calibration, were up to 10 times lower then before, while comparison of histograms referring to real images provided an improvement of about seven times on average. Conclusions: A complete workflow for dermatologic image calibration, which allows the user to continue using his own software and algorithms, but with a much higher informative content, is presented. The technique is simple and may improve cooperation between different research centers, in teleconsulting contexts or for result comparisons.

Computer vision and ubiquitous multimedia access nowadays make feasible the development of a mostly automated system for human-behavior analysis. In this context, our proposal is to analyze human behaviors by classifying the posture of the monitored person and, consequently, detecting corresponding events and alarm situations, like a fall. To this aim, our approach can be divided in two phases: for each frame, the projection histograms (Haritaoglu et al., 1998) of each person are computed and compared with the probabilistic projection maps stored for each posture during the training phase; then, the obtained posture is further validated exploiting the information extracted by a tracking module in order to take into account the reliability of the classification of the first phase. Moreover, the tracking algorithm is used to handle occlusions, making the system particularly robust even in indoors environments. Extensive experimental results demonstrate a promising average accuracy of more than 95% in correctly classifying human postures, even in the case of challenging conditions.

Objective: To characterize the microscopic aspects of the dermoscopic pigment network in vivo, by means of confocal scanning laser microscopy. Design: Confocal imaging was performed on melanocytic lesions characterized by pigment network at dermoscopy. Some confocal architectural and cytologic features, as observed at the dermoepidermal junction, were morphologically described and quantified by means of a dedicated program. Setting: University medical department. Study Population: We studied confocal images of 15 melanomas, 15 dermoscopic atypical nevi, and 15 common nevi. Main Outcome Measures: Features referring to aspect, size, regularity, homogeneity, and infiltration of dermal papillae and to cellular size, regularity, and atypia were described by 2 observers on confocal images. Mean dermal papillary diameter, mean cell area, and shape irregularity were quantified by drawing papillae and cell contours on confocal images and measured with the use of a computer program. Results: Pigment network in melanomas consisted of large basal cells that circumscribed small to medium-sized dermal papillae with marked cellular atypia, sometimes infiltrating dermal papillae. On the other hand, common acquired nevi were characterized by lack of atypical cells and edged dermal papillae. Atypical nevi presented intermediate characteristics between clearly benign and malignant lesions. Conclusion: Cellular atypia was the most sensitive feature for melanoma diagnosis, whereas the presence of nucleated cells infiltrating dermal papillae was the most specific one.