An optimal design of moving objects tracking algorithm on FPGA

Elkhatib, Lina Noaman; Hussin, Fawnizu Azmadi; Xia, Likun; Sebastian, Patrick

doi:10.1109/icias.2012.6306112

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…For example, Liu et al [2] incorporate a background subtraction-based algorithm to implement an object tracking system, which can reach more than 100X for complex video inputs. Additionally, Elkhatib et al [3] propose an object tracking hardware system which can deal with the 640x480 input images run on a 20MHz processor. Furthermore, Singh et al [4] concentrate on the integration of modified particle filters and SAD for object tracking, their implemented system can robustly track the objects based on Xilinx Virtex V. All of the hardware systems mentioned above have achieved significant tracking results.…”

Section: Introductionmentioning

confidence: 99%

A novel low-cost FPGA-based real-time object tracking system

Gao

Yuan

Zhao

et al. 2017

2017 IEEE 12th International Conference on ASIC (ASICON)

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In current visual object tracking system, the CPU or GPUbased visual object tracking systems have high computational cost and consume a prohibitive amount of power. Therefore, in this paper, to reduce computational burden of Camshift algorithm, we propose a novel visual object tracking algorithm by exploiting the properties of binary classifier and Kalman predictor. Moreover, we present a low-cost FPGA-based real-time object tracking hardware architecture. Extensive evaluations on OTB benchmark demonstrate that the proposed system has extremely compelling real-time, stability and robustness. The evaluation results show that the accuracy of our algorithm is about 48%, and the average speed is about 309 frames per second. DDR3 Address generator ROI MAP RAM P1 P2 P3 … PN Comparator 1 Result RAM 1

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Section: Introductionmentioning

confidence: 99%

A novel low-cost FPGA-based real-time object tracking system

Gao

Yuan

Zhao

et al. 2017

2017 IEEE 12th International Conference on ASIC (ASICON)

View full text Add to dashboard Cite

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Real-Time FPGA-Based Object Tracker with Automatic Pan-Tilt Features for Smart Video Surveillance Systems

2017

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Abstract:The design of smart video surveillance systems is an active research field among the computer vision community because of their ability to perform automatic scene analysis by selecting and tracking the objects of interest. In this paper, we present the design and implementation of an FPGA-based standalone working prototype system for real-time tracking of an object of interest in live video streams for such systems. In addition to real-time tracking of the object of interest, the implemented system is also capable of providing purposive automatic camera movement (pan-tilt) in the direction determined by movement of the tracked object. The complete system, including camera interface, DDR2 external memory interface controller, designed object tracking VLSI architecture, camera movement controller and display interface, has been implemented on the Xilinx ML510 (Virtex-5 FX130T) FPGA Board. Our proposed, designed and implemented system robustly tracks the target object present in the scene in real time for standard PAL (720 × 576) resolution color video and automatically controls camera movement in the direction determined by the movement of the tracked object.

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An optimal design of moving objects tracking algorithm on FPGA

Cited by 2 publications

References 10 publications

A novel low-cost FPGA-based real-time object tracking system

A novel low-cost FPGA-based real-time object tracking system

Real-Time FPGA-Based Object Tracker with Automatic Pan-Tilt Features for Smart Video Surveillance Systems

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