Parallel particle filter object tracking based on embedded multicore DSP systems
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作者:
Tian, Li
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机构:
Image Processing Center, School of Astronautics, Beihang University, Beijing,100191, ChinaImage Processing Center, School of Astronautics, Beihang University, Beijing,100191, China
Tian, Li
[1
]
Zhou, Fugen
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机构:
Image Processing Center, School of Astronautics, Beihang University, Beijing,100191, ChinaImage Processing Center, School of Astronautics, Beihang University, Beijing,100191, China
Zhou, Fugen
[1
]
Meng, Cai
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机构:
Image Processing Center, School of Astronautics, Beihang University, Beijing,100191, ChinaImage Processing Center, School of Astronautics, Beihang University, Beijing,100191, China
Meng, Cai
[1
]
机构:
[1] Image Processing Center, School of Astronautics, Beihang University, Beijing,100191, China
Monte Carlo methods - Parallel processing systems - Digital signal processing - Embedded systems - Application programming interfaces (API);
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摘要:
The object tracking servo system requires a low delay from an object moving to starting of rotations while the inherent computational complexity of PF (Particle Filter) affects the tracking precision. In this paper, a multicore DSP parallel implementation strategy for particle filter object tracking was proposed. Firstly, the PA module on chip was used to reduce the GigE image capturing delay and the CPU occupancy. The CPU load was considerably reduced from 31% to 10%. Secondly, by manually FLUSH after writing and INVALID before reading, the memory consistency problem was addressed and cacheable shared image data can be accessed at high efficiency. Finally, a mechanism of parallel computing on multi-core processor was introduced by adding proxy task. The computational intensive stages of particle filter were dispatched to 8 cores to eliminate system delay. Experimental results show that the tracking response time was decreased and algorithmic speedup runs up to 7 and exceeds OpenMP.