The MultimediaN concert-video browser demonstrates a video interaction environment for efficiently browsing the live performance records in the pop, rock and other music concerts. The underlying automatic analyzer extracts the instrumental solos and applause sections in the concert videos and also the level of excitement along the performances. The extracted information is provided to the user via a web-based interface to let them enjoy a much more advanced experience of browsing through the concerts. Taking the unorganized structure of the concerts and the desire for non-sequential access to the content, our system is a step-forward to make large concert video databases accessible. The demo system also allows us to exhibit the power and robustness of our algorithms that are able to perform well in a highly heterogeneous and noisy context of music concerts.

The MultimediaN concert-video browser demonstrates a video interaction environment for efficiently browsing video registrations of pop, rock and other music concerts. The exhibition displays the current state of the project for developing an advanced concert-video browser in 2007. Three demos are provided: 1) a high-level content analysis methodology for modeling the "experience" of the concert at its different stages, and for automatically detecting and identifying semantically coherent temporal segments in concert videos, 2) a general-purpose video editor that associates semantic descriptions with the video segments using both manual and automatic inputs, and a video browser that applies ideas from information foraging theory and demonstrates patch-based video browsing, 3) the Fabplayer, specifically designed for patch-based browsing of concert videos by a dedicated user-group, making use of the results of automatic concert-video segmentation

The ever-increasing complexity of generic multimedia-content-analysis-based (MCA) solutions, their processing power demanding nature and the need to prototype and assess solutions in a fast and cost-saving manner motivated the development of the Cassandra framework. The combination of state-of-the-art network and grid-computing solutions and recently standardized interfaces facilitated the set-up of this framework, forming the basis for multiple cross-domain and cross-organizational collaborations. It enables distributed computing scenario simulations for e.g. distributed content analysis (DCA) across consumer electronics (CE) in-home networks, but also the rapid development and assessment of complex multi-MCA-algorithm-based applications and system solutions. Furthermore, the framework's modular nature-logical MCA units are wrapped into so-called service units (SU)-ease the split between system-architecture- and algorithmic-related work and additionally facilitate reusability, extensibility and upgrade ability of those SUs