Real-Time Implementation of Adaptive Correlation Filter Tracking for 4K Video Stream in Zynq UltraScale+ MPSoC

Kowalczyk, Marcin; Przewłocka-Rus, Dominika; Kryjak, Tomasz

doi:10.1109/dasip48288.2019.9049203

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…Our solution dominates both in terms of power and speed the RADSST [28]. MOSSE [29] is not DSST-based tracker but relies on programmable logic. It has a higher speed at 4K resolution, but it is reported to compare power.…”

Section: Overall Resources and Speedmentioning

confidence: 99%

Real-time implementation of fast discriminative scale space tracking algorithm

Walid

Awais

Ahmed

et al. 2021

J Real-Time Image Proc

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Real-time object tracking is an important step of many modern image processing applications. The efficient hardware design of real-time object tracker must achieve the desired accuracy while satisfying the frame rate requirements for a variety of image sizes. The existing methods of visual tracking employ sophisticated algorithms and challenge the capabilities of most embedded architectures. Discriminative scale space tracking is one algorithm that is capable of demonstrating good performance with affordable complexity. It has a high degree of parallelism which can be exploited for efficient implementation of reconfigurable hardware architectures. This paper proposes a real-time implementation of the discriminative scale-space tracker on FPGA for the major blocks. A careful design exploration of core mathematical operations of the tracking algorithm is performed to improve their hardware utilization and timing performance. Among the core functional units optimized in this work, the discrete Fourier transform achieves a computational time improvement of 92% relative to existing works, QR factorization achieves a 2.3$$\times$$ × reduction in resource utilization, and singular value decomposition yields a 3.8$$\times$$ × improvement in processing time. The proposed data path architecture is designed using Vivado HLS tool set and implemented for Zync Zed Board (xc7z020clg484-1). For an input image size of 320 $$\times$$ × 240, the proposed architecture achieves a mean 25.38 fps.

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Section: Overall Resources and Speedmentioning

confidence: 99%

Real-time implementation of fast discriminative scale space tracking algorithm

Walid

Awais

Ahmed

et al. 2021

J Real-Time Image Proc

View full text Add to dashboard Cite

show abstract

“…In this work, the circuit implemented in the programmable logic of the FPGA is derived automatically using Vivado HLS 2018.1. The Zynq UltraScale+ MPSoC ZCU102 has been used also in [27], where a tracking algorithm for 4K video stream is presented. Such tracker could potentially be adopted on drones and it is based on a 2D FFT.…”

Section: Fpga Solutionsmentioning

confidence: 99%

Unmanned Vehicles in Smart Farming: a Survey and a Glance at Future Horizons

Madroñal

Palumbo

Capotondi

et al. 2021

Proceedings of the 2021 Drone Systems Engineering and Rapid Simulation and Performance Evaluation: Methods and Tools Proceeding

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Smart and Precision Agriculture is nowadays already exploiting advanced drones and machinery, but it is foreseen that in the near future more complex and intelligent applications will be required to be brought on-board to improve qualitatively and quantitative production. In this paper, we present an overview on the current usage of autonomous drones in this field and on the augmented computing capabilities that they could count on when companion computers are coupled to flight c ontrollers. T he p aper also present a novel architecture for companion computers that is under development within the Comp4Drones ECSEL-JU project.

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Real-Time Embedded Object Tracking with Discriminative Correlation Filters Using Convolutional Features

Daniłowicz

Kryjak

2022

Lecture Notes in Computer Science

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Real-Time Implementation of Adaptive Correlation Filter Tracking for 4K Video Stream in Zynq UltraScale+ MPSoC

Cited by 4 publications

References 10 publications

Real-time implementation of fast discriminative scale space tracking algorithm

Real-time implementation of fast discriminative scale space tracking algorithm

Unmanned Vehicles in Smart Farming: a Survey and a Glance at Future Horizons

Real-Time Embedded Object Tracking with Discriminative Correlation Filters Using Convolutional Features

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