research-article

Real-time Target Tracking Based on PCANet-CSK Algorithm

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Pu DongAuthors Info & Claims

CSAI '19: Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence

Pages 343 - 346

https://doi.org/10.1145/3374587.3374607

Published: 04 March 2020 Publication History

Abstract

This paper presents a real-time target tracking method by combining PCANet and CSK. To speed up PCANet feature extraction, we give a lightweight PCANet to simplify the structure of PCANet. In tracking step, in order to improve tracking performance, we integrate the scale adaptive module into traditional CSK algorithm and optimize its model updating mechanism inspired by LMCF. The experimental results on OTB50 validate the effeteness of our method. Compared with the traditional CSK algorithm using gray features, the tracking success rate of our method is about 26% higher, and the tracking accuracy increases about 29%.

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Cited By

Zhang YZhu MGui KYu JHao YSun H(2024)Development and Application of a Monte Carlo Tree Search Algorithm for Simulating Da Vinci Code Game Strategies2024 5th International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI)10.1109/ICHCI63580.2024.10807882(5-11)Online publication date: 27-Sep-2024
https://doi.org/10.1109/ICHCI63580.2024.10807882

Index Terms

Real-time Target Tracking Based on PCANet-CSK Algorithm
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Tracking

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CSAI '19: Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence

December 2019

370 pages

ISBN:9781450376273

DOI:10.1145/3374587

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Shenzhen University: Shenzhen University

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Association for Computing Machinery

New York, NY, United States

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Published: 04 March 2020

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CSAI2019

CSAI2019: 2019 3rd International Conference on Computer Science and Artificial Intelligence

December 6 - 8, 2019

IL, Normal, USA

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Cited By

Zhang YZhu MGui KYu JHao YSun H(2024)Development and Application of a Monte Carlo Tree Search Algorithm for Simulating Da Vinci Code Game Strategies2024 5th International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI)10.1109/ICHCI63580.2024.10807882(5-11)Online publication date: 27-Sep-2024
https://doi.org/10.1109/ICHCI63580.2024.10807882

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