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A modular system architecture for online parallel vision pipelines

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4 Author(s)
Papon, J. ; Bernstein Center for Comput. Neurosci. (BCCN), Georg-August Univ. of Gottingen, Gottingen, Germany ; Abramov, A. ; Aksoy, E. ; Worgotter, F.

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

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