Content-Based Video Description for Automatic Video Genre Categorization

International audienceIn this paper, we propose an audio-visual approach to video genre categorization. Audio information is extracted at block-level, which has the advantage of capturing local temporal information. At temporal structural level, we asses action contents with respect to human perception. Further, color perception is quantified with statistics of color distribution, elementary hues, color properties and relationship of color. The last category of descriptors determines statistics of contour geometry. An extensive evaluation of this multi-modal approach based on more than 91 hours of video footage is presented. We obtain average precision and recall ratios within [87% − 100%] and [77% − 100%], respectively,nwhile average correct classification is up to 97%. Additionally, movies displayed according to feature-based coordinates in a virtual 3D browsing environment tend to regroup with respect to genre, which has potential application with real content-based browsing systems

CAMMA: Contextual Advertising System for Multimodal News Aggregations

is demo paper describes a system for contextual advertis- ing on aggregations of multimodal news items. The proto- Type is intended to demonstrate how modern content anal- ysis techniques can be profitably used to automate tasks commonly performed by humans such as the planning of the computer-assisted advertising content

"Wandering with the Times". An advanced mobile phone guide to architectural/urban heritage

The paper proposes a cell phone case study. The project intends to develop advanced knowledge services, based on sophisticated technologies, readily available through new channels (mobile phones) and aplied to a particular cultural heritage object, Architectural/Urban Space. The pilot installation and validation will perform in Piazza Duomo or Piazza dei Cavalieri, Pisa, Italy. exempl

Experimenting text summarization on multimodal aggregation

Nowadays, Web is characterized by a growing availability of multimedia data together with a strong need for integrating different media and modalities of interaction. Hence, the main goal is to bring into the Web data thought and produced for different media, such as TV or radio content. In this scenario, we focus on multimodal news aggregation retrieval and fusion. In particular, we present preliminary experiments aimed at automatically suggesting keywords to news and news aggregations. The proposed solution is based on the adoption of extraction-based text summarization techniques. Experiments are aimed at comparing the selected text summarization techniques with respect to a simple technique based on part-ofspeech tagging. Results show that the proposed solution performs better than the baseline solution in terms of precision, recall, and F1

Applying contextual advertising to multimodal information content

Contextual Advertising, a major sources of income for a large number of websites, is aimed at suggesting products and services to the ever growing population of Internet users. In this paper, we focus on the problem of suggesting suitable advertisements to news aggregation from television and from the Internet. To our best knowledge, this is the first attempt to perform this task in the field of multimodal aggregation. The proposed system suggests from 1 to 5 advertisements related to the main topic of aggregated news items. 15 users were asked to evaluate the relevance of the suggested advertisements. Preliminary results are encouraging for further development and application of contextual advertising in the field of multimodal aggregation

Content-based Keywords Extraction and Automatic Advertisement Associations to Multimodal News Aggregations

Nowadays, Web is characterized by a growing availability of multimedia data together with a strong need for integrating different media and modalities of interaction. Hence, one of the main challenges is to bring into the Web data thought and produced for different media, such as TV or press content. In this scenario, we focus on multimodal news aggregation retrieval and fusion. Multimodality, here, is intended as the capability of processing, gathering, manipulating, and organizing data from multiple media. In particular, we tackle two main issues: to extract relevant keywords to news and news aggregations, and to automatically associate suitable advertisements to aggregated data. To achieve the first goal, we propose a solution based on the adoption of extraction-based text summarization techniques; whereas to achieve the second goal, we developed a contextual advertising system that works on multimodal aggregated data. To assess the proposed solutions, we performed experiments on Italian news aggregations. Results show that, in both cases, the proposed solution performs better than the adopted baseline solutions

Modes Detection of Color Histogram and Merging Algorithm by Mode Adjacency Graph Analysis for Color Image Segmentation

International audienceIn this work we present an approach for color image segmentation based on pixel classification. Such methods are based on the assumption that meaningful regions are defined by homogeneous colors and give rise to compact clusters in the color space. Each cluster defined a class of pixels which share similar color properties The construction of the pixel classes is performed by detecting the modes of the color histogram of the image. To identify these modes, mathematical morphology techniques are used. The application of watersheds on the color histogram leads to an over partitioning of the color plane, which can be processed by mode merging algorithms based on mode adjacency graph analysing. Depending the merging criterion we present in this paper two merging algorithms, the first relies on the gravity centers of the modes as a merging criterion, and in the second we introduce a new merging criterion: the spatial-color compactness degree

Materiali da Anzi al Museo Archeologico Nazionale di Napoli. Catalogo

L'articolo è un catalogo delle ceramiche provenienti da vecchi scavi condotti nel centro lucano di Anzi, conservati al Museo Archeologico Nazionale di Napol