Segmentation sémantique des contenus audio-visuels

Dans ce travail, nous avons mis au point une méthode de segmentation des contenus audiovisuels applicable aux appareils de stockage domestiques pour cela nous avons expérimenté un système distribué pour l’analyse du contenu composé de modules individuels d’analyse : les Service Unit. L’un d’entre eux a été dédié à la caractérisation des éléments hors contenu, i.e. les publicités, et offre de bonnes performances. Parallèlement, nous avons testé différents détecteurs de changement de plans afin de retenir le meilleur d’entre eux pour la suite. Puis, nous avons proposé une étude des règles de production des films, i.e. grammaire de films, qui a permis de définir les séquences de Parallel Shot. Nous avons, ainsi, testé quatre méthodes de regroupement basées similarité afin de retenir la meilleure d’entre elles pour la suite. Finalement, nous avons recherché différentes méthodes de détection des frontières de scènes et avons obtenu les meilleurs résultats en combinant une méthode basée couleur avec un critère de longueur de plan. Ce dernier offre des performances justifiant son intégration dans les appareils de stockage grand public.In this work we elaborated a method for semantic segmentation of audiovisual content applicable for consumer electronics storage devices. For the specific solution we researched first a service-oriented distributed multimedia content analysis framework composed of individual content analysis modules, i.e. Service Units. One of the latter was dedicated to identify non-content related inserts, i.e. commercials blocks, which reached high performance results. In a subsequent step we researched and benchmarked various Shot Boundary Detectors and implement the best performing one as Service Unit. Here after, our study of production rules, i.e. film grammar, provided insights of Parallel Shot sequences, i.e. Cross-Cuttings and Shot-Reverse-Shots. We researched and benchmarked four similarity-based clustering methods, two colour- and two feature-point-based ones, in order to retain the best one for our final solution. Finally, we researched several audiovisual Scene Boundary Detector methods and achieved best results combining a colour-based method with a shot length based criteria. This Scene Boundary Detector identified semantic scene boundaries with a robustness of 66% for movies and 80% for series, which proofed to be sufficient for our envisioned application Advanced Content Navigation

CHORUS Deliverable 3.3: Vision Document - Intermediate version

The goal of the CHORUS vision document is to create a high level vision on audio-visual search engines in order to give guidance to the future R&D work in this area (in line with the mandate of CHORUS as a Coordination Action). This current intermediate draft of the CHORUS vision document (D3.3) is based on the previous CHORUS vision documents D3.1 to D3.2 and on the results of the six CHORUS Think-Tank meetings held in March, September and November 2007 as well as in April, July and October 2008, and on the feedback from other CHORUS events. The outcome of the six Think-Thank meetings will not just be to the benefit of the participants which are stakeholders and experts from academia and industry – CHORUS, as a coordination action of the EC, will feed back the findings (see Summary) to the projects under its purview and, via its website, to the whole community working in the domain of AV content search. A few subjections of this deliverable are to be completed after the eights (and presumably last) Think-Tank meeting in spring 2009

Impartment of spicy, fruity and herbal aromas from the Czech hop varieties of Ceres, Pluto and Saturn to beer

The aim of the study is to evaluate the intensity and character of the beer aroma in selected hop varieties. In 2022 and 2023, new Czech Flavour hop varieties of Ceres, Pluto, and Saturn were registered. Ceres exhibits a mild citrusy and fruity hop aroma. Pluto has an intense fruity and herbal aroma, while Saturn has an intense fruity aroma with a milder citrus note. Differences in the intensity and character of the beer aroma were identified based on the hop variety used and the cold hopping dose. These varieties and their combinations were tested under cold hopping at 3 g/l and 6 g/l to assess the impartment of the aromas to beer. The combination of Pluto + Saturn shows the highest intensity of a spicy aroma, while Ceres exhibits the highest intensity of both the fruity and herbal aromas – all this at 6 g/l. The best character of the spicy aroma is observed with Ceres at 3 g/l. Ceres also demonstrates the best character of the fruity aroma, and Ceres + Pluto combination excels in the herbal aroma, both at the dose of 6 g/l. The popularity of beer is crucial, with the combination of Ceres + Pluto at 3 g/l proving to be the most popular. The results have practical applications in breweries producing bottom-fermented beers that utilize dry hopping. It is obvious which hop varieties or their combinations can be used to accentuate individual aroma profiles