以軟硬體協同設計之混合型即時影像多目標物體追蹤系統 Hardware/Software Co-design of a Hybrid Multiple-Object Tracking System Based on Particle Filter and Particle Swarm Optimization

Date
2014
Authors
朱永青
Yung-Ching Chu
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Abstract
本文提出了一種混合型即時影像多目標物體追蹤系統,結合粒子群聚最佳化法(Particle Swarm Optimization, PSO)與粒子濾波器(Particle Filter, PF)兩種演算法之優點,以提升多目標物體追蹤的性能。並且在可程式規劃系統晶片(System On a Programmable Chip, SOPC)之架構下,利用FPGA(Field Programmable Gate Array)的硬體電路,將此混合型演算法以軟硬體協同設計(HW/SW Co-design)之方式實現出來。此方式不僅可以達到硬體加速的功能,還能有彈性地設計整個電路,當軟體部分驗證完成後,即可以全硬體方式實現整個多目標物體追蹤系統,進一步提升整體系統的效能。
This thesis presents a hybrid algorithm incorporating Particle Swarm Optimization (PSO) and Particle Filter (PF) for multiple-object tracking to improve the system performance. Based on the System on a Programmable Chip (SOPC) technique, we use hardware/software (HW/SW) co-design method to implement the hybrid algorithm on the FPGA circuit. As a result, the tracking efficiency can be greatly improved, while maintaining design flexibility for various applications. To further improve the performance of the multiple-object tracking system, full hardware implementation of the tracking system can be realized once the prototype testing of the system is completed.
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多目標物體追蹤, 可程式規劃系統晶片, 粒子群聚最佳化法, 粒子濾波器, Multiple-object tracking, System on a Programmable Chip (SOPC), Particle Swarm Optimization, Particle Filter
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