Publications by Rita Cucchiara

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.

This paper proposes the use of a mixture of Von Mises distributions to detect abnormal behaviors of moving people. The mixture is created from an unsupervised training set by exploiting k-medoids clustering algorithm based on Bhattacharyya distance between distributions. The extracted medoids are used as modes in the multi-modal mixture whose weights are the priors of the specific medoid. Given the mixture model a new trajectory is verified on the model by considering each direction composing it as independent. Experiments over a real scenario composed of multiple, partially-overlapped cameras are reported.

In this paper, we present the dynamic pictorial ontology paradigm for video annotation. Ontologies are often used to describe a given domain for different goals, including description of multimedia data. In the case of video annotation, the visual knowledge cannot be described using only abstract concepts but is more effectively represented in a visual form. To this aim, we introduce visual concepts, elicited from the data set as the most representative prototypes that specialize abstract concepts. The ontology created is intrinsically dynamic since it must embrace the perceptual and visual experience during annotation. Thus visual concepts can change, adapting to the multimedia content analyzed. Motivation for this new ontology paradigm are discussed together with a proposal of a framework for ontology creation, maintenance, and automatic annotation of video. The creation and usage of dynamic pictorial ontologies have been tested for soccer domain exploiting low level perceptual features and higher level domain features.

The paper presents the design and implementation of a system of autonomous navigation of a mobile robot with stereo vision. © 2007 IEEE.

Color is one of the most meaningful features used in content based retrieval of visual data. In video content based retrieval, color features computed on selected frames are integrated with other low-level features concerning texture, shape and motion in order to find clip similarities. For example, the Scalable Color feature defined in the MPEG-7 standard exploits HSV histograms to create color feature vectors. HSV is a widely adopted space in image and video retrieval, but its quantization for histogram generation can create misleading errors in classification of achromatic and low saturated colors. In this paper we propose an Enhanced HSV Histogram with achromatic point detection based on a single Hue and Saturation parameter that can correct this limitation. The enhanced histograms have proven to be effective in color analysis and they have been used in a system for automatic clip annotation called PEANO, where pictorial concepts are extracted by a clip clustering and used for similarity based automatic annotation.

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In this paper, we propose an automatic system forvideo shot segmentation, called Linear Transition Detector (LTD),unique for both cuts and linear transitions detection. Comparisonwith publicly available shot detection systems is reported ondifferent sports (Formula 1, basket, soccer and cycling) andTRECVID 2005 results are also reported.

This paper presents a system for remote live video surveillance. Videos are acquired from a fixed camera at 10 fps and QVGA resolution, compressed at 5 or 20 kbit/s with H.264, and streamed to a remote site, where they get processed by an automatic video surveillance system. The target surveillance application performs moving object segmentation and tracking. Both ends (video acquisition and processing) could be connected through a wireless network, specifically GPRS.The whole system is studied and optimized to maintain low latency. The reported experiments demonstrate that the proposed system is able to send up to four video streams over GPRS or E-GPRS network, without significantly affecting the performance of the automatic video surveillance system. Comparative tests have been performed with other existing streaming solutions.

In this paper we focus on the problem of automatic classification of melanocytic lesions, aiming at identifying the presence of reticular patterns. The recognition of reticular lesions is an important step in the description of the pigmented network, in order to obtain meaningful diagnostic information. Parameters like color, size or symmetry could benefit from the knowledge of having a reticular or non-reticular lesion. The detection of network patterns is performed with a three-steps procedure. The first step is the localization of line points, by means of the line points detection algorithm, firstly described by Steger. The second step is the linking of such points into a line considering the direction of the line at its endpoints and the number of line points connected to these. Finally a third step discards the meshes which couldn't be closed at the end of the linking procedure and the ones characterized by anomalous values of area or circularity. The number of the valid meshes left and their area with respect to the whole area of the lesion are the inputs of a discriminant function which classifies the lesions into reticular and non-reticular. This approach was tested on two balanced (both sets are formed by 50 reticular and 50 non-reticular images) training and testing sets. We obtained above 86% correct classification of the reticular and non-reticular lesions on real skin images, with a specificity value never lower than 92%.