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Efficient migration of complex off-line computer vision software to real-time system implementation on generic computer hardware

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5 Author(s)
J. A. Tyrrell ; Rensselaer Polytech. Inst., Troy, NY, USA ; J. M. LaPre ; C. D. Carothers ; B. Roysam
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This paper addresses the problem of migrating large and complex computer vision code bases that have been developed off-line, into efficient real-time implementations avoiding the need for rewriting the software, and the associated costs. Creative linking strategies based on Linux loadable kernel modules are presented to create a simultaneous realization of real-time and off-line frame rate computer vision systems from a single code base. In this approach, systemic predictability is achieved by inserting time-critical components of a user-level executable directly into the kernel as a virtual device driver. This effectively emulates a single process space model that is nonpreemptable, nonpageable, and that has direct access to a powerful set of system-level services. This overall approach is shown to provide the basis for building a predictable frame-rate vision system using commercial off-the-shelf hardware and a standard uniprocessor Linux operating system. Experiments on a frame-rate vision system designed for computer-assisted laser retinal surgery show that this method reduces the variance of observed per-frame central processing unit cycle counts by two orders of magnitude. The conclusion is that when predictable application algorithms are used, it is possible to efficiently migrate to a predictable frame-rate computer vision system.

Published in:

IEEE Transactions on Information Technology in Biomedicine  (Volume:8 ,  Issue: 2 )