A PARALLEL OPTIMIZATION METHOD FOR KERNEL CORRELATION FILTER BASED ON MULTI-CORE DSP

Wancang Wu; Qingzhong Jia; Shan Li; Bingqing Teng

doi:10.1049/icp.2021.0602

A PARALLEL OPTIMIZATION METHOD FOR KERNEL CORRELATION FILTER BASED ON MULTI-CORE DSP

Wancang Wu^*, Qingzhong Jia, Shan Li, Bingqing Teng

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Target tracking is an important branch in the field of computer vision. In recent years, parallel computing efficiency becomes the key to improving real-time performance in multi-core DSP platforms. This paper proposes the concept of execution parallelism based on Open MP, optimizes Kernel Correlation Filter (KCF) with execution parallelism parameters, and compares it with inter-processor Communication (IPC). This paper aims at the KCF algorithm on the TMS320C6678 platform for the multi-core parallel development of the above two methods. With multiple data-sets, the results are all higher than 60 frames/s. With physical verification by connecting the video board, parallel scheme based on Open MP can achieve a tracking effect of 75 FPS, which has certain engineering practical significance.

Original language	English
Title of host publication	IET Conference Proceedings
Publisher	Institution of Engineering and Technology
Pages	1416-1420
Number of pages	5
Volume	2020
Edition	9
ISBN (Electronic)	9781839535406
DOIs	https://doi.org/10.1049/icp.2021.0602
Publication status	Published - 2020
Externally published	Yes
Event	5th IET International Radar Conference, IET IRC 2020 - Virtual, Online Duration: 4 Nov 2020 → 6 Nov 2020

Conference

Conference	5th IET International Radar Conference, IET IRC 2020
City	Virtual, Online
Period	4/11/20 → 6/11/20

Keywords

KCF
MULTI-CORE DSP
OPENMP
PARALLEL OPTIMIZATION

Access to Document

10.1049/icp.2021.0602

Cite this

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title = "A PARALLEL OPTIMIZATION METHOD FOR KERNEL CORRELATION FILTER BASED ON MULTI-CORE DSP",

abstract = "Target tracking is an important branch in the field of computer vision. In recent years, parallel computing efficiency becomes the key to improving real-time performance in multi-core DSP platforms. This paper proposes the concept of execution parallelism based on Open MP, optimizes Kernel Correlation Filter (KCF) with execution parallelism parameters, and compares it with inter-processor Communication (IPC). This paper aims at the KCF algorithm on the TMS320C6678 platform for the multi-core parallel development of the above two methods. With multiple data-sets, the results are all higher than 60 frames/s. With physical verification by connecting the video board, parallel scheme based on Open MP can achieve a tracking effect of 75 FPS, which has certain engineering practical significance.",

keywords = "KCF, MULTI-CORE DSP, OPENMP, PARALLEL OPTIMIZATION",

author = "Wancang Wu and Qingzhong Jia and Shan Li and Bingqing Teng",

note = "Publisher Copyright: {\textcopyright} 2020 IET Conference Proceedings. All rights reserved.; 5th IET International Radar Conference, IET IRC 2020 ; Conference date: 04-11-2020 Through 06-11-2020",

year = "2020",

doi = "10.1049/icp.2021.0602",

language = "English",

volume = "2020",

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booktitle = "IET Conference Proceedings",

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AU - Jia, Qingzhong

AU - Li, Shan

AU - Teng, Bingqing

PY - 2020

Y1 - 2020

N2 - Target tracking is an important branch in the field of computer vision. In recent years, parallel computing efficiency becomes the key to improving real-time performance in multi-core DSP platforms. This paper proposes the concept of execution parallelism based on Open MP, optimizes Kernel Correlation Filter (KCF) with execution parallelism parameters, and compares it with inter-processor Communication (IPC). This paper aims at the KCF algorithm on the TMS320C6678 platform for the multi-core parallel development of the above two methods. With multiple data-sets, the results are all higher than 60 frames/s. With physical verification by connecting the video board, parallel scheme based on Open MP can achieve a tracking effect of 75 FPS, which has certain engineering practical significance.

AB - Target tracking is an important branch in the field of computer vision. In recent years, parallel computing efficiency becomes the key to improving real-time performance in multi-core DSP platforms. This paper proposes the concept of execution parallelism based on Open MP, optimizes Kernel Correlation Filter (KCF) with execution parallelism parameters, and compares it with inter-processor Communication (IPC). This paper aims at the KCF algorithm on the TMS320C6678 platform for the multi-core parallel development of the above two methods. With multiple data-sets, the results are all higher than 60 frames/s. With physical verification by connecting the video board, parallel scheme based on Open MP can achieve a tracking effect of 75 FPS, which has certain engineering practical significance.

KW - KCF

KW - MULTI-CORE DSP

KW - OPENMP

KW - PARALLEL OPTIMIZATION

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U2 - 10.1049/icp.2021.0602

DO - 10.1049/icp.2021.0602

M3 - Conference contribution

AN - SCOPUS:85174651562

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SP - 1416

EP - 1420

BT - IET Conference Proceedings

PB - Institution of Engineering and Technology

T2 - 5th IET International Radar Conference, IET IRC 2020

Y2 - 4 November 2020 through 6 November 2020

ER -

A PARALLEL OPTIMIZATION METHOD FOR KERNEL CORRELATION FILTER BASED ON MULTI-CORE DSP

Abstract

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Keywords

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