Publications by Costantino Grana

In this paper we describe general algorithms that are devised for MPEG-7 automatic annotation of Formula 1 videos, and in particular for camera-car shots detection. We employed a shot detection algorithm suitable for cuts and linear transitions detection, which is able to precisely detect both the transition's center and length. Statistical features based on MPEG motion compensation vectors arc then employed to provide motion characterization, using a subset of the motion types defined in MPEG-7, and shot type classification. Results on shot detection and classification are provided.

In-house video surveillance to control the safety of people living in domestic environments is considered. In this context, common problems and general purpose computer vision techniques are discussed and implemented in an integrated solution comprising a robust moving object detection module which is able to disregard shadows, a tracking module designed to handle large occlusions, and a posture detector. These factors, shadows, large occlusions and people's posture, are the key problems that are encountered with in-house surveillance systems, A distributed system with cameras installed in each room of a house can be used to provide full coverage of people's movements. Tracking is based on a probabilistic approach in which the appearance and probability of occlusions are computed for the current camera and warped in the next camera's view by positioning the cameras to disambiguate the occlusions. The application context is the emerging area of domotics (from the Latin word domus, meaning 'home', and informatics). In particular, indoor video surveillance, which makes it possible for elderly and disabled people to live with a sufficient degree of autonomy, via interaction with this new technology, which can be distributed in a house at affordable costs and with high reliability.

This year, the joint team of UCF and the University of Modenahas participated in the following tasks: (1) shot boundarydetection, (2) low-level feature extraction, (3) high-levelfeature extraction, (4) topic search and (5) BBC rushes management.The shot boundary detection was contributed bythe Image Lab at the University of Modena. The other taskswere performed by the Computer Vision Team at UCF.

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.

Background/purpose: Atypical nevi (AN) share some dermoscopic features with early melanoma (MM), and computer elaboration of digital images could represent a useful support to diagnosis to assess automatically colors in AN, and to compare the data with those referring to clearly benign nevi (BN) and MMs. Methods: An image analysis program enabling the numerical description of color areas in melanocytic lesions was used on 459 videomicroscopic images, referring to 76 AN, 288 clearly BN and 95 MMs. Results: Black, white and blue-gray were more frequently found in AN than in clearly BN, but less frequently than in MMs. Color area values significantly differed between the three groups. Conclusion: The clinical-morphological interpretation of the numerical data, based on the mathematical description of the aspect and distribution of different color areas in different lesion types may contribute to the characterization of AN and their distinction from MMs.

Metadata extraction is one of the first tasks to be performed for automatic Digital Library annotation, and in particular shot detection has been widely explored in literature. While a lot of methods have been proposed for the detection of abrupt cuts, only a small number of them has explicitly addressed the problem of gradual transitions. In this paper we propose an algorithm that exploits a precise model of linear transition. Experimental results on Formula 1 car races videos show the robustness of this method. These test videos are characterized by extreme situations such as fast camera and objects motion and very different kinds of shots. The algorithm is able to estimate the exact length of the transition and an error score is also given as a fitness measure to the linear model, to discriminate true transitions from false detections. The final shot segmentation is delivered as an MPEG7 compliant output.

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.

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.