MarsyasX : Multimédia Datflow Processing vith Implicit Patching

Luís Teixeira (1) , Luis G Martins , Mathieu Lagrange (2) , George Tzanetakis (3)

1 NOVA - Universidade Nova de Lisboa = NOVA University Lisbon
2 LS2N - Laboratoire des Sciences du Numérique de Nantes
3 UVIC - University of Victoria [Canada]

The design and implementation of multimedia signal processing systems is challenging especially when efficiency and real-time performance is desired. In many modern applications , software systems must be able to handle multiple flows of various types of multimedia data such as audio and video. Researchers frequently have to rely on a combination of different software tools for each modality to assemble proof-of-concept systems that are inefficient, brittle and hard to maintain. Marsyas is a software framework originally developed to address these issues in the domain of audio processing. In this paper we describe MarsyasX, a new open-source cross-modal analysis framework that aims at a broader score of applications. It follows a dataflow architecture where complex networks of processing objects can be assembled to form systems that can handle multiple and different types of multimedia flows with expressiveness and efficiency.

Mots clés: D211 [Software Engineering]: Software Architectures; domain-specific architectures; D213 [Software Engineer-; ing]: Reusable Software reusable libraries; Keywords; Multimedia processing framework; Dataflow processing; Open; source library

Domaines: Machine Learning [stat.ML]; Traitement du signal et de l'image [eess.SP]; Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]; Multimédia [cs.MM]; Traitement du signal et de l'image [eess.SP]

Luís Teixeira, Luis G Martins, Mathieu Lagrange, George Tzanetakis. MarsyasX : Multimédia Datflow Processing vith Implicit Patching. Proceeding of the 16th ACM international conference, Oct 2008, Vancouver, France. ⟨10.1145/1459359.1459510⟩. ⟨hal-01697481⟩