Publications by Costantino Grana

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.

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.

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.

In this work, we present a general purpose systemfor hierarchical structural segmentation and automaticannotation of video clips, by means of standardizedlow level features. We propose to automatically extractsome prototypes for each class with a context basedintra-class clustering. Clips are annotated followingthe MPEG-7 standard directives to provide easierportability. Results of automatic annotation and semiautomaticmetadata creation are provided.

In this work, we describe in detail the new MPEG-7 Perceptual 3D Shape Descriptor and provide a set of tests with different 3D objects databases, mainly with the Princeton Shape Benchmark. With this purpose we created a function library called Retrieval-3D and fixed some bugs of the MPEG-7 eXperimentation Model (XM). We explain how to match the Attributed Relational Graph (ARG) of every 3D model with the modified nested Earth Mover’s Distance (mnEMD). Finally we compare our results with the best found in literature, including the first MPEG-7 3D descriptor, i.e. the Shape Spectrum Descriptor.

This paper presents multimedia ontologies, where multimedia data and traditional textual ontologies are merged. A solution for their implementation for the soccer video domain and a method to perform automatic soccer video annotation using these extended ontologies is shown. 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 more general concepts of the sport domain (e.g. play/break, crowd, etc.) are put in correspondence with the more general visual features of the video like color and texture, while the more specific concepts of the soccer domain (e.g. highlights such as attack actions) are put in correspondence with domain specific visual feature like the soccer playfield and the players. Experimental results for annotation of soccer videos using generic concepts are presented.

In this work, we focus on two aspects of the comparison of video shots. We present a new approach to extract a variable number of key frames from a shot, by the use of a hierarchical clustering with automatic level selection, in order to provide optimal allocation of features on different parts of the shot. We then employ the Mallows distance as an effective technique to compare the discrete distributions of features, independently from the features selected for the specific application. Results and comparisons on a soccer documentary video are provided.

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 worldwide incidence of cutaneous melanoma has increased dramatically over the past decades. It is well known that a good prognosis of melanoma is only expected for thin lesions. Preventive effort has therefore been concentrated on identification of early lesions facilitated by the introduction and dissemination of standardized clinical criteria and by the use of dermoscopy (epiluminescence microscopy). However, the interpretation of dermoscopic criteria is often confusing especially for the inexperienced observer. This chapter summarizes recent computer techniques to help the clinician in these tasks.

In this work, we analyze the effectiveness of perceptual features to automatically annotate video clips in domain-specific video digital libraries. Typically, automatic annotation is provided by computing clip similarity with respect to given examples, which constitute the knowledgebase, in accordance with a given ontology or a classification scheme. Since the amount of training clips is normally very large, we propose to automatically extract some prototypes, or visual concepts, for each class instead of using the whole knowledge base. The prototypes are generated after a Complete Link clustering based on perceptual features with an automatic selection of the number of clusters. Context based information are used in an intra-class clustering framework to provide selection of more discriminative clips. Reducing the number of samples makes the matching process faster and lessens the storage requirements. Clips are annotated following the MPEG-7 directives to provide easier portability. Results are provided on videos taken from sports and news digital libraries.