Publications

In vivo reflectance-mode confocal laser microscopy enables the visualization of the skin at quasi- histopathologic resolution. The aim of our study was to describe confocal features in melanocytic lesions, to evaluate their diagnostic significance for melanoma identification, to develop a simple algorithm useful for diagnostic purposes. A total of 102 consecutive melanocytic lesions (37 melanomas, 49 acquired nevi and 16 Spitz nevi), corresponding to lesions with equivocal aspects at clinical and dermoscopic inspection and excised in order to rule out a melanoma, were investigated by means of confocal microscopy (Vivascope 1000). In superficial layers the general pattern and the presence and aspects of pagetoid cells were evaluated. At basal cell layer dermal papilla features and cytological aspects, suggesting the presence of cellular atypia, were described. In dermal papilla, the presence and morphology of melanocytic nests and the presence and aspect of solitary cells were evaluated. Some features were more frequently observed in melanomas. In multivariate analysis 6 features appeared independently correlated with melanoma diagnosis. The presence of non edged dermal papillae, atypical cells in basal layers and isolated nucleated cells within dermal papilla were strongly correlated with melanoma diagnosis and were considered as major criteria (scored 2 points), whereas the presence of pagetoid cells, a widespread pagetoid infiltration in superficial layers and cerebriform nests in upper dermis were considered ‘‘minor’’ criteria (scored 1 point). A total score, ranging between 0 to 9, was obtained for each lesion and a ROC curve with an area under the curve of 0.951 was obtained on our dataset. In conclusion, characterization of confocal microscopy features of melanomas and nevi seems to improve diagnostic accuracy for difficult to diagnose melanocytic lesions.

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 video surveillance can provide good support for people with some difficulties (e.g. elderly or disabled people) living alone and with limited autonomy. A key aspect in video surveillance systems for domotics is that of analyzing behaviours of the monitored people. To accomplish this task, people must be detected and tracked, and their posture must be analyzed in order to model behaviours recognizing abrupt changes in it. Problems related to reliable software solutions are not completely solved, in particular luminance changes, shadows and frequent posture changes must be taken into account. Long-lasting occlusions are common due to the proximity of the cameras and the presence of furniture and doors that can often hide parts of a person’s body. For these reasons, a probabilistic and appearance-based tracking, particularly conceivable for people tracking and posture classification, has been developed. However, despite its effectiveness for long-lasting and large occlusions, this approach tends to fail whenever the person is monitored with multiple cameras and he appears in one of them already occluded. Different views provided by multiple cameras can be exploited to solve occlusions by warping known object appearance into the occluded view. To this aim, this paper describes an approach to posture classification based on projection histograms, reinforced by HMM for assuring temporal coherence of the posture.

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.

In this paper we propose a system for automatic detection of shots in sport videos. Our work covers two main aspects: the first is robust shot detection in presence of fast object motion and camera operations. To this aim we propose a new algorithm, unique for both cuts and linear transitions detection, which only needs the tuning of two parameters. An extended comparison with four transition detection algorithms, representing the state of the art in literature, is reported. Examples with formula 1, basket, soccer and cycling videos are analyzed. The second aspect is an in depth discussion on the annotation of shots and transitions with the MPEG-7 standard.

The integration of video technology and sensor networks constitutes the fundamental infrastructure for new generations of multimedia surveillance systems, where many different media streams (audio, video, images, textual data, sensor signals) will concur to provide an automatic analysis of the controlled environment and a real-time interpretation of the scene. New solutions can be devised to enlarge the view of traditional surveillance systems by means of distributed architectures with fixed and active cameras, to enhance their view with other sensed data, to explore multi-resolution views with zooming and omnidirectional cameras. Applications regard surveillance of wide indoor and outdoor area and particularly people surveillance: in this case, multimedia surveillance systems can be enriched with biometric technology; the best views of detected persons and their extracted visual features (e.g. faces, voices, trajectories)can be exploited for people identification. VSSN05 is the third edition of the workshop, co-located at ACM Multimedia Conference, that embraces research reports on video surveillance and, since the edition of 2004, sensor networks. Thispaper gives a short overview of the hot topics in multimedia surveillance systems and introduces some research activities currently engaged in the world and presented at VSSN05.

Background/purpose: Since in early melanoma (MM) and especially in in situ MM differential structures, which are diagnostic for MM may be lacking, pigment distribution asymmetry represents an important diagnostic feature. Our aim was to automatically assess pigment distribution in images referring to MMs, atypical nevi (AN) and clearly benign nevi (BN), and to evaluate the diagnostic capability of numerical parameters describing a non homogeneous distribution of pigmentation. Methods: An image analysis program enabling the numerical assessment of pigment distribution in melanocytic lesions (ML), based on evaluation and comparison of red, green, blue (RGB) colour components inside image colour blocks, was employed on 459 videomicroscopic digital images, referring to 95 MMs, 76 AN and 288 BN. Results: Significant differences in pigment distribution parameters (mean RGB distance, variance and maximum distance) between the three ML populations were observed, permitting a good discrimination of MMs. On the test set comprising 230 lesion images, the area under the curve value of the receiver operating characteristic curve was 0.933. For a D score equal to 0, corresponding to the best diagnostic accuracy (86.6%), a sensitivity of 87.5% and a specificity of 85.7% were obtained. Conclusion: This original evaluation method for digital pigment distribution, based on mathematical description and comparison of colours in different image blocks, provides numerical parameters to be implemented in image analysis programs for computer-aided MM diagnosis.

Posture classification is a key process for analyzing thepeople’s behaviour. Computer vision techniques can behelpful in automating this process, but clutteredenvironments and consequent occlusions make this taskoften difficult. Different views provided by multiplecameras can be exploited to solve occlusions by warpingknown object appearance into the occluded view. To thisaim, this paper describes an approach to postureclassification based on projection histograms, reinforcedby HMM for assuring temporal coherence of the posture.The single camera posture classification is then exploitedin the multi-camera system to solve the cases in which theocclusions make the classification impossible.Experimental results of the classification from both thesingle camera and the multi-camera system are provided.

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.

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.