Publications

In this DEMO, we present a tool set for video digital library management that allows i) structural annotation of edited videos in MPEG-7 by automatically extracting shots and clips; ii) automatic semantic annotation based on perceptual similarity against a taxonomy enriched with pictorial concepts iii) video clip access and hierarchical summarization with stand-alone and web interface iv) access to clips from mobile platform in GPRS-UMTS videostreaming. The tools can be applied in different domain-specific Video Digital Libraries. The main novelty is the possibility to enrich the annotation with pictorial concepts that are added to a textual taxonomy in order to make the automatic annotation process more fast and often effective. The resulting multimedia ontology is described in the MPEG-7 framework. The PEANO (Perceptual Annotation of Video) tool has been tested over video art, sport (Soccer, Olimpic Games 2006, Formula 1) and news clips.

This paper describes a system for motion detection based on background suppression,specifically conceived for working in complex scenes with vacillating background,camouflage, illumination changing, etc.. The system contains proper techniques for background bootstrapping, shadow removal, ghost suppression and selective updating of the background model. The results on the challenging videos provided in VSSN '06 Open Source Algorithm Competition dataset demonstrate that the proposed system outperforms the widely-used mixture-of-Gaussians approach.

In this work, we present a general purpose system for hierarchical structural segmentation and automatic annotation of video clips, by means of standardized low level features. We propose to automatically extract some prototypes for each class with a context based intra-class clustering. Clips are annotated following the MPEG-7 standard directives to provide easier portability. Results of automatic annotation and semiautomatic metadata creation are provided

Distributed video surveillance has a direct application in intelligent home automation or domotics (from the Latin word domus, that means “home”, and informatics); in particular, in-house videosurveillance can provide good support for people with some difficulties (e.g., elderly or disabled people) living alone and with a limited autonomy. New hardware technologies for surveillance are now affordable and provide high reliability. Problems related to reliable software solutions are not completely solved, especially concerning the application of general-purpose computer vision techniques in indoor environments. Indeed, assuming the objective is to detect the presence of people, track them, and recognize dangerous behaviours by means of abrupt changes in their posture, robust techniques must cope with non-trivial difficulties. In particular, luminance changes and shadows must be taken into account, frequent posture changes must be faced, and large and long-lasting occlusions are common due to the vicinity of the cameras and the presence of furnitureand doors that can often hide parts of the person’s body. These problems are analyzed and solutions based on background suppression, appearance-based probabilistic tracking, and probabilistic reasoning for posture recognition are described.

What approach or combination of approaches did you test in each of your submitted runs?TRECVID2005_UNIMORE_??.xml: the same linear transition detector (LTD) was tested forevery run, with ten uniformly spaced thresholds for the detection.What if any significant differences (in terms of what measures) did you find among theruns?The system behaved as expected: the higher the threshold the better the recall. Of course theprecision lowered correspondently. Interesting enough, it seems that we cannot overcome theoverall limit around 80% for recall and 88% for precision, independently of the other parameter.Based on the results, can you estimate the relative contribution of each component of yoursystem/approach to its effectiveness?One of the main objective of our system was to test the performance of a single algorithm forboth cuts and gradual transitions. So all the merit and the demerits are related to our LTD.Overall, what did you learn about runs/approaches and the research question(s) thatmotivated them?The use of a single algorithm allows the system to be run without training. Just a singleparameter may be employed to tune the sensibility of the system, thus allowing its use in generalpurpose/user friendly systems.

Background Semiquantitative algorithms were applied to dermoscopic images to improve the clinical diagnosis for melanoma. Objective The aim of the study was to develop a computerized method for automated quantification of the 'A' (asymmetry) and 'B' (border cut-off) parameters, according to the ABCD rule for dermoscopy, thus reproducing human evaluation. Methods Three hundred and thirty-one melanocytic lesion images, referring to 113 melanomas and 218 melanocytic nevi, acquired by means of a digital videodermatoscope, were considered. Images were evaluated by two experienced observers and by using computer algorithms developed by us. Clinical evaluation of asymmetry was performed by attributing scores to shape asymmetry and asymmetry of pigment distribution and structures, whereas computer evaluation of shape and pigment distribution asymmetries were based on the assessment of differences in area and lightness in the two halves of the image, respectively. Borders were evaluated both by clinicians and by the computer, by attributing a score to each border segment ending abruptly. Differences between nevus and melanoma values were evaluated using the chi-square test, while Cohen's Kappa index for agreement was employed for the evaluation of the concordance between human and computer. Results Pigment distribution asymmetry appears the most striking parameter for melanoma diagnosis both for human and for automated diagnosis. A good concordance between clinicians and computer evaluation was achieved for all asymmetry parameters, and was excellent for border cut-off evaluation. Conclusions These algorithms enable a good reproduction of the 'A' and 'B' parameters of the ABCD rule for dermoscopy, and appear useful for diagnostic and learning purposes.

It is with considerable pride that we present this special issue of ACM multimedia based on the presentations at the third Video Surveillance and Sensor Network workshop, in conjunction with the ACM conference in Singapore 2005. The papers were thoroughly reviewed independently of the review process for the workshop. This special issue consists of eight papers drawn from a number of areas. It appears that we are breaking new ground as explained in this issue.Whenever we say multimedia, we think of systems and services that manage heterogeneous data for human-oriented applications; human users are normally the subjects who access and use multimedia data, multimediastreams, multimedia content, and multimedia interfaces in many different applications contexts. Following this abstraction, multimedia surveillance systems would be only a surveillance system able to produce output of the task in a multimedia format, providing distilled video, images and sounds of the monitored environment, which would possibly be annotated in an efficient and standard way or possibly transcoded in another media such as text or animation, to improve further querying to surveillance stored data.

Digital dermoscopy improves the accuracy of melanoma diagnosis. The aim of this study was to develop and validate software for assessment of asymmetry in melanocytic lesion images, based on evaluation of colour symmetry, and to compare it with assessment by human observers. An image analysis program enabling numerical assessment of asymmetry in melanocytic lesions, based on the evaluation and comparison of CIE L*a*b* colour components (CIE L*a*b* is the name of a colour space defined by the Commission Internationale de l'Eclairage) inside image colour blocks, was employed on the recorded lesion images. Clinical evaluation of asymmetry in dermoscopic images was performed on the same image set employing a 0-1 scoring system. Asymmetry judgement was expressed by the clinicians for 12.8% of benign naevi, 44.7% of atypical naevi and 64.2% of malignant melanomas, whereas the computer identified as asymmetric 6.3%, 33.3% and 82.2%, respectively. Numerical parameters referring to malignant melanomas were significantly higher, both with respect to benign naevi and atypical naevi. The numerical parameters produced could be effectively employed for computer-aided melanoma diagnosis.

In semantic video adaptation measures of performance must consider the impact of the errors in the automatic annotation over the adaptation in relationship with the preferences and expectations of the user. In this paper, we define two new performance measures Viewing Quality Loss and Bit-rate Cost Increase, that are obtained from classical peak signal-to-noise ration (PSNR) and bit rate, and relate the results of semantic adaptation to the errors in the annotation of events and objects and the user's preferences and expectations. We present and discuss results obtained with a system that performs automatic annotation of soccer sport video highlights and applies different coding strategies to different parts of the video according to their relative importance for the end user. With reference to this framework, we analyze how highlights' statistics and the errors of the annotation engine influence the performance of semantic adaptation and reflect into the quality of the video displayed at the user's client and the increase of transmission costs.