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On-Satellite Implementation of Real-Time Multi-Object Moving Vehicle Tracking with Complex Moving Backgrounds.

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Title: On-Satellite Implementation of Real-Time Multi-Object Moving Vehicle Tracking with Complex Moving Backgrounds.
Authors: Yu, Jingyi1,2 (AUTHOR) weisiyuan20@semi.ac.cn, Wei, Siyuan2,3 (AUTHOR) wyx@semi.ac.cn, Wen, Yuxiao2,3 (AUTHOR) zhouds@semi.ac.cn, Zhou, Danshu2,3 (AUTHOR) liujian@semi.ac.cn, Dou, Runjiang2,3 (AUTHOR) dourj@semi.ac.cn, Wang, Xiuyu1 (AUTHOR) wxy@tju.edu.cn, Xu, Jiangtao1 (AUTHOR) xujiangtao@tju.edu.cn, Liu, Jian2,3 (AUTHOR) liuly@semi.ac.cn, Wu, Nanjian2,3 (AUTHOR), Liu, Liyuan2,4 (AUTHOR)
Source: Remote Sensing. Feb2025, Vol. 17 Issue 3, p418. 28p.
Subjects: Affine transformations, Gate array circuits, Relative motion, Information processing, Pixels, Artificial satellite tracking
Abstract: On-satellite information processing enables all-weather target tracking. The background of videos from satellite sensors exhibits an affine transformation due to their motion relative to the Earth. In complex moving backgrounds, moving vehicles have a small number of pixels and weak texture features. At the same time, the resources and performance of on-satellite equipment are limited. To address these issues, we propose a multi-object tracking (MOT) algorithm with a detection–association framework for moving vehicles in complex moving backgrounds and implement the algorithm on a satellite to achieve real-time MOT. We use feature matching to effectively eliminate the effects of background motion and use the neighborhood pixel difference method to extract moving vehicle targets in the detection stage. The accurate extraction of motion targets ensures the effectiveness of target association to achieve MOT of moving vehicles in complex moving backgrounds. Additionally, we use a Field-Programmable Gate Array (FPGA) to implement the algorithm completely on a satellite. We propose a pixel-level stream processing mode and a cache access processing mode, given the characteristics of on-satellite equipment and sensors. According to the experimental results, the prototype on-satellite implementation method proposed in this paper can achieve real-time processing at 1024 × 1024 px@47 fps. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: On-Satellite Implementation of Real-Time Multi-Object Moving Vehicle Tracking with Complex Moving Backgrounds.
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  Data: <searchLink fieldCode="AR" term="%22Yu%2C+Jingyi%22">Yu, Jingyi</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> weisiyuan20@semi.ac.cn</i><br /><searchLink fieldCode="AR" term="%22Wei%2C+Siyuan%22">Wei, Siyuan</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> wyx@semi.ac.cn</i><br /><searchLink fieldCode="AR" term="%22Wen%2C+Yuxiao%22">Wen, Yuxiao</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> zhouds@semi.ac.cn</i><br /><searchLink fieldCode="AR" term="%22Zhou%2C+Danshu%22">Zhou, Danshu</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> liujian@semi.ac.cn</i><br /><searchLink fieldCode="AR" term="%22Dou%2C+Runjiang%22">Dou, Runjiang</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> dourj@semi.ac.cn</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Xiuyu%22">Wang, Xiuyu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wxy@tju.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Xu%2C+Jiangtao%22">Xu, Jiangtao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> xujiangtao@tju.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Jian%22">Liu, Jian</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> liuly@semi.ac.cn</i><br /><searchLink fieldCode="AR" term="%22Wu%2C+Nanjian%22">Wu, Nanjian</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Liyuan%22">Liu, Liyuan</searchLink><relatesTo>2,4</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="DE" term="%22Affine+transformations%22">Affine transformations</searchLink><br /><searchLink fieldCode="DE" term="%22Gate+array+circuits%22">Gate array circuits</searchLink><br /><searchLink fieldCode="DE" term="%22Relative+motion%22">Relative motion</searchLink><br /><searchLink fieldCode="DE" term="%22Information+processing%22">Information processing</searchLink><br /><searchLink fieldCode="DE" term="%22Pixels%22">Pixels</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+satellite+tracking%22">Artificial satellite tracking</searchLink>
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  Data: On-satellite information processing enables all-weather target tracking. The background of videos from satellite sensors exhibits an affine transformation due to their motion relative to the Earth. In complex moving backgrounds, moving vehicles have a small number of pixels and weak texture features. At the same time, the resources and performance of on-satellite equipment are limited. To address these issues, we propose a multi-object tracking (MOT) algorithm with a detection–association framework for moving vehicles in complex moving backgrounds and implement the algorithm on a satellite to achieve real-time MOT. We use feature matching to effectively eliminate the effects of background motion and use the neighborhood pixel difference method to extract moving vehicle targets in the detection stage. The accurate extraction of motion targets ensures the effectiveness of target association to achieve MOT of moving vehicles in complex moving backgrounds. Additionally, we use a Field-Programmable Gate Array (FPGA) to implement the algorithm completely on a satellite. We propose a pixel-level stream processing mode and a cache access processing mode, given the characteristics of on-satellite equipment and sensors. According to the experimental results, the prototype on-satellite implementation method proposed in this paper can achieve real-time processing at 1024 × 1024 px@47 fps. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3390/rs17030418
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        Text: English
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        PageCount: 28
        StartPage: 418
    Subjects:
      – SubjectFull: Affine transformations
        Type: general
      – SubjectFull: Gate array circuits
        Type: general
      – SubjectFull: Relative motion
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      – SubjectFull: Information processing
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      – SubjectFull: Pixels
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      – SubjectFull: Artificial satellite tracking
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    Titles:
      – TitleFull: On-Satellite Implementation of Real-Time Multi-Object Moving Vehicle Tracking with Complex Moving Backgrounds.
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              M: 02
              Text: Feb2025
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