Real-time implementation of fast discriminative scale space tracking algorithm

Walid Walid, Muhammad Awais, Ashfaq Ahmed, Guido Masera, Maurizio Martina

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

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× reduction in resource utilization, and singular value decomposition yields a 3.8× 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 × 240, the proposed architecture achieves a mean 25.38 fps.

Original languageBritish English
Pages (from-to)2347-2360
Number of pages14
JournalJournal of Real-Time Image Processing
Volume18
Issue number6
DOIs
StatePublished - Dec 2021

Keywords

  • DFT
  • Discriminative correlation filter
  • DSST
  • FPGA
  • QR
  • Real time
  • SVD

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