Context The recent tendency in multimedia domain is the semantic video understanding by automatic video analyzing. For that purpose, it is very important to know and study the video contents; i.e. background, actions, objects and their movements to better understand their meaning. Accordingly, object properties are very important issues. One important property which can significantly facilitate the understanding of object
Context The analysis of instrumental activities of daily life is an important tool in the early diagnosis of dementia such as Alzheimer. The IMMED project investigates tele-monitoring technologies to support doctors in the diagnostic and follow-up of the illnesses. The project aims to automatically produce indexes to facilitate the doctor’s navigation throughout the individual video recordings. Water sound recognition is
Overview Detecting when multiple harmonic sources are present is essential for structuring various type of audio content. We propose a method for detecting area with simultaneous harmonic sources using graph analysis of the tracking of the main frequencies. As our approach seems to work on choir detection, we propose to generalise our approach to identify overlapping harmonic sources using the
The detection of unison choir is a difficult problem as the different singers aims at singing the same thing at the same time. This leads some algorithm to classify such area as monophonic. However, we can observe little divergence between the harmonics of the different singers as shown in the figure below. Example of solo and unison choir part. The
Context Based on the idea that TV series – which tend to have more and more complex plot, with numerous characters and multiple intertwined stories – are already segmented into narrative themes in post-production, we present a system able to discover the structure of an episode without a priori knowledge. The system proceeds by segmenting the episode into shots, then
Overview Rhythm is an important information for understanding audio data. On both music and speech analysis, the rhythm can help to describe and segment different kind of phenomena. The approach we present led us to propose two new representation : The Rhythm Spectrum and the Tempogram Our approach is not based on any musicological or speech knowledge and aims at finding periodicity in changes
Context Work on features extraction and segmentation carried out in our team provides sets of low-level features or segments that can be considered as basic events. Their exploitation and their combination carried out in different ways can lead to the detection of new features or events of a higher or more semantic level. In previous work, we have studied temporal relationships between basic audio
Context This research takes place in a context of audio indexing. After some work on the detection of speech and music, the problem of the position of singing appears. Actually, it is music produced by human voice. In our Speech/Music system, it is classifed mainly in the music category, but it was sometimes taken for speech. The purpose of this work
Context Most of the existing video-search engines rely on context and textual metadata such as the title of the video, tags and comments written by users, etc. In other words, no attempt at understanding the actual content of the video is performed. Content-based audiovisual analysis aims at bridging this so-called semantic gap. Overview Our approach to this problem aims at being as generic,
Context Nearly all methods of audio or video segmentation perform with a priori knowledge. These approaches are based on a spatial-temporal modelling of the content and use decision rules. Currently, it is the only way to reach the semantic quality required by search engines. But only recording collections highly structured, such as broadcast videos of news and sports programmes, and