OpenCV在TI 达芬奇以及OMAP平台下的移植与性能评估
In today’s advancing market, the growing
performance and decreasing price of embedded
processors are opening many doors
for developers to design highly sophisticated
solutions for different end applications.
The complexities of these systems can create
bottlenecks for developers in the form of
longer development times, more complicated
development environments and issues with
application stability and quality. Developers
can address these problems using sophisticated
software packages such as OpenCV,
but migrating this software to embedded
platforms poses its own set of challenges.
This paper will review how to mitigate some
of these issues, including C++ implementation,
memory constraints, floating-point
support and opportunities to maximize performance
using vendor-optimized libraries
and integrated accelerators or co-processors.
Finally, we will introduce a new effort by
Texas Instruments (TI) to optimize vision systems
by running OpenCV on the C6000™
digital signal processor (DSP) architecture.
Benchmarks will show the advantage of using
the DSP by comparing the performance
of a DSP+ARM® system-on-chip (SoC)
processor against an ARM-only device.
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