By Topic

A modular system architecture for online parallel vision pipelines

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Jeremie Papon ; Bernstein Center for Computational Neuroscience (BCCN), III Physikalisches Institut - Biophysik, Georg-August University of Göttingen, Germany ; Alexey Abramov ; Eren Aksoy ; Florentin Wörgötter

We present an architecture for real-time, online vision systems which enables development and use of complex vision pipelines integrating any number of algorithms. Individual algorithms are implemented using modular plugins, allowing integration of independently developed algorithms and rapid testing of new vision pipeline configurations. The architecture exploits the parallelization of graphics processing units (GPUs) and multi-core systems to speed processing and achieve real-time performance. Additionally, the use of a global memory management system for frame buffering permits complex algorithmic flow (e.g. feedback loops) in online processing setups, while maintaining the benefits of threaded asynchronous operation of separate algorithms. To demonstrate the system, a typical real-time system setup is described which incorporates plugins for video and depth acquisition, GPU-based segmentation and optical flow, semantic graph generation, and online visualization of output. Performance numbers are shown which demonstrate the insignificant overhead cost of the architecture as well as speed-up over strictly CPU and single threaded implementations.

Published in:

Applications of Computer Vision (WACV), 2012 IEEE Workshop on

Date of Conference:

9-11 Jan. 2012