Fast Human Activity Recognition Based On A Massively Parallel Implementation Of Random Forest
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2016, PT II(2016)
摘要
This article elaborates on the task of Human Activity Recognition being solved with the Random Forest algorithm. A performance measure is provided in terms of both recognition accuracy and computation speed. In addition, the Random Forest algorithm was implemented using CUDA, a technology providing options for massively parallel computations on low-cost hardware. The results suggest that Random Forest is a suitable and highly reliable technique for recognising human activities and that Graphics Processing Units can significantly improve the computation times of this otherwise rather time-consuming algorithm.
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关键词
Random forests, Classification, GPU, CUDA, Parallelisation
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