rapid-communication

Modality-correlation-aware sparse representation for RGB-infrared object tracking

Authors:

Shengping Zhang,

Pong C. YuenAuthors Info & Claims

Volume 130, Issue C

Pages 12 - 20

https://doi.org/10.1016/j.patrec.2018.10.002

Published: 01 February 2020 Publication History

Highlights

•

A modality-correlation-aware sparse representation model is proposed for RGB-infrared object tracking.

•

A effective and efficient learning algorithm is derived to obtain the optimal model parameters.

•

Extensive experiments are performed to demonstrate the effectiveness of the proposed method on some large appearance variations such as low illumination condition.

Abstract

To intelligently analyze and understand video content, a key step is to accurately perceive the motion of the interested objects in videos. To this end, the task of object tracking, which aims to determine the position and status of the interested object in consecutive video frames, is very important, and has received great research interest in the last decade. Although numerous algorithms have been proposed for object tracking in RGB videos, most of them may fail to track the object when the information from the RGB video is not reliable (e.g. in dim environment or large illumination change). To address this issue, with the popularity of dual-camera systems for capturing RGB and infrared videos, this paper presents a feature representation and fusion model to combine the feature representation of the object in RGB and infrared modalities for object tracking. Specifically, this proposed model is able to (1) perform feature representation of objects in different modalities by employing the robustness of sparse representation, and (2) combine the representation by exploiting the modality correlation. Extensive experiments demonstrate the effectiveness of the proposed method.

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Cited By

Zhang ZWang JLi SJin LWu HZhao JZhang B(2024)Review and Analysis of RGBT Single Object Tracking Methods: A Fusion PerspectiveACM Transactions on Multimedia Computing, Communications, and Applications10.1145/365130820:8(1-27)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3651308
Zhang HYang JQian JGao GLan XZha ZWen B(2024)Efficient Image Classification via Structured Low-Rank Matrix Factorization RegressionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.333771719(1496-1509)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2023.3337717
He YMa ZWei XGong Y(2024)Knowledge Synergy Learning for Multi-Modal TrackingIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.335257334:7(5519-5532)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/TCSVT.2024.3352573
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Index Terms

Modality-correlation-aware sparse representation for RGB-infrared object tracking
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object recognition
        Tracking
      2. Computer vision tasks
        Scene understanding
  2. Machine learning

Index terms have been assigned to the content through auto-classification.

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cover image Pattern Recognition Letters

Pattern Recognition Letters Volume 130, Issue C

Feb 2020

386 pages

ISSN:0167-8655

Issue’s Table of Contents

Elsevier B.V.

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Elsevier Science Inc.

United States

Publication History

Published: 01 February 2020

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Cited By

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https://dl.acm.org/doi/10.1145/3651308
Zhang HYang JQian JGao GLan XZha ZWen B(2024)Efficient Image Classification via Structured Low-Rank Matrix Factorization RegressionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.333771719(1496-1509)Online publication date: 1-Jan-2024
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He YMa ZWei XGong Y(2024)Knowledge Synergy Learning for Multi-Modal TrackingIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.335257334:7(5519-5532)Online publication date: 1-Jul-2024
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Zhou MZhao XLuo FLuo JPu HXiang T(2023)Robust RGB-T Tracking via Adaptive Modality Weight Correlation Filters and Cross-modality LearningACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363010020:4(1-20)Online publication date: 25-Oct-2023
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Tu ZLin CZhao WLi CTang J(2022)M⁵L: Multi-Modal Multi-Margin Metric Learning for RGBT TrackingIEEE Transactions on Image Processing10.1109/TIP.2021.312550431(85-98)Online publication date: 1-Jan-2022
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