Abstract:
In recent times, there are increasing numbers of computer vision and
pattern recognition (CVPR) technologies being applied to real time video processing
using single processor PCs. However, these multiple computational expensive
tasks are generating bottlenecks in real-time processing. We propose a
scheme to achieve both high throughput and accommodation to user-specified
scheduling rules. The scheduler is then distributing ‘slices’ of the latency insensitive
tasks such as video object recognition and facial localization among the
latency sensitive ones. We show our proposed work in detail, and illustrating its
application in a real-time e-learning streaming system. We also provide discussions
into the scheduling implementations, where a novel concept using interleaved
SIMD execution is discussed. The experiments have indicated successful
scheduling results on a high end consumer grade PC.
