Members
Overall Objectives
Research Program
Application Domains
Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
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Section: New Results

SUP

Participants : Julien Gueytat, François Brémond.

keywords: SUP, Software, Video Processing

Presentation

SUP is a Scene Understanding Software Platform writtent in C++ designed for analyzing video content. (see Figure 44 ) SUP is splitting the workflow into several modules, such as acquisition, segmentation, etc., up to activity recognition. Each module has a specific interface, and different plugins implementing these interfaces can be used for each step of the video processing.

Figure 44. SUP workflow
IMG/SUP-architecture.jpg

The plugins cover the following research topics:

The software is already widely disseminated among researchers, universities, and companies:

And new sites are coming: EHPAD Valrose, Institut Claude Pompidou, Delvalle and Biot.

Improvements

Our team focuses on developing a Scene Understanding Platform (SUP). This platform has been designed for analyzing video content. SUP is able to recognize events such as 'falling', 'walking' of a person. We can easily build new analyzing systems thanks to a set of algorithms also called plugins. The order of those plugins and their parameters can be changed at run time and the result visualized on a dedicated GUI. This platform has many more advantages such as easy serialization to save and replay a scene, portability to Mac, Windows or Linux, and easy deployment to quickly setup an experimentation anywhere. All those advantages are available since we are working together with the Inria software developer team SED. Many Inria teams are pushing together to improve a common Inria development toolkit DTK. Our SUP framework is one of the DTK-like framework developed at Inria.

Currently, the OpenCV library is fully integrated with SUP. OpenCV provides standardized dataypes, a lot of video analysis algorhithms and an easy access to OpenNI sensors such as the Kinect or the ASUS Xtion PRO LIVE.

Updates and presentations of our framework can be found on our team website https://team.inria.fr/stars/software . Detailed tips for users are given on our Wiki website http://wiki.inria.fr/stars and sources are hosted thanks to the software developer team SED.