Active Tracking of Moving Objects with Speed Variations Using a Novel PTZ Camera-based Machine Vision Technique.
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| Title: | Active Tracking of Moving Objects with Speed Variations Using a Novel PTZ Camera-based Machine Vision Technique. |
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| Authors: | Feng Lu1 1849048346@qq.com, Youchun Xu1 xu56419@126.com, Yuan Zhu1 mm1849048346@126.com, Zhichao Zhang1 zzcjake6688@163.com, Yulin Ma2 mayulin@mail.ahpu.edu.cn, Kang Mao maokang94@163.com |
| Source: | Electronics & Electrical Engineering. 2025, Vol. 31 Issue 2, p60-70. 11p. |
| Subjects: | Computer vision, Spherical coordinates, Image stabilization, Evidence gaps, Cameras |
| Abstract: | Most existing methods of active tracking focus mainly on slow-moving objects, resulting in limited adaptability to objects with variable speeds. To bridge this research gap, a novel spherical coordinate guided adaptive active tracking (SCAAT) approach based on the pan–tilt–zoom (PTZ) camera machine vision system is proposed in this study. For object detection and tracking, YOLOv5 and DeepSORT are employed in the PTZ vision system. The spherical coordinates and angular speeds of the moving object can be acquired under the spherical coordinate system. For practical application, the start-time and start-angle delay of the PTZ cameras are calibrated, and a speed control equation is conducted in the spherical coordinate system to reduce rapid location deviation between the PTZ and the moving object. To adapt different speeds of the object and avoid camera shaking under different zooms, an adaptive tracking window is designed to keep the object within the camera field of view. Experimental testing has been performed to evaluate the proposed SCAAT method. The results indicate that the SCATT can not only expand the effective following distance and zoom of the PTZ camera, but also effectively improve the accuracy and stability of active tracking for the moving object with large speed variations. [ABSTRACT FROM AUTHOR] |
| Copyright of Electronics & Electrical Engineering is the property of Electronics & Electrical Engineering 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.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 186229496 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Active Tracking of Moving Objects with Speed Variations Using a Novel PTZ Camera-based Machine Vision Technique. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Feng+Lu%22">Feng Lu</searchLink><relatesTo>1</relatesTo><i> 1849048346@qq.com</i><br /><searchLink fieldCode="AR" term="%22Youchun+Xu%22">Youchun Xu</searchLink><relatesTo>1</relatesTo><i> xu56419@126.com</i><br /><searchLink fieldCode="AR" term="%22Yuan+Zhu%22">Yuan Zhu</searchLink><relatesTo>1</relatesTo><i> mm1849048346@126.com</i><br /><searchLink fieldCode="AR" term="%22Zhichao+Zhang%22">Zhichao Zhang</searchLink><relatesTo>1</relatesTo><i> zzcjake6688@163.com</i><br /><searchLink fieldCode="AR" term="%22Yulin+Ma%22">Yulin Ma</searchLink><relatesTo>2</relatesTo><i> mayulin@mail.ahpu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Kang+Mao%22">Kang Mao</searchLink><i> maokang94@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Electronics+%26+Electrical+Engineering%22">Electronics & Electrical Engineering</searchLink>. 2025, Vol. 31 Issue 2, p60-70. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+vision%22">Computer vision</searchLink><br /><searchLink fieldCode="DE" term="%22Spherical+coordinates%22">Spherical coordinates</searchLink><br /><searchLink fieldCode="DE" term="%22Image+stabilization%22">Image stabilization</searchLink><br /><searchLink fieldCode="DE" term="%22Evidence+gaps%22">Evidence gaps</searchLink><br /><searchLink fieldCode="DE" term="%22Cameras%22">Cameras</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Most existing methods of active tracking focus mainly on slow-moving objects, resulting in limited adaptability to objects with variable speeds. To bridge this research gap, a novel spherical coordinate guided adaptive active tracking (SCAAT) approach based on the pan–tilt–zoom (PTZ) camera machine vision system is proposed in this study. For object detection and tracking, YOLOv5 and DeepSORT are employed in the PTZ vision system. The spherical coordinates and angular speeds of the moving object can be acquired under the spherical coordinate system. For practical application, the start-time and start-angle delay of the PTZ cameras are calibrated, and a speed control equation is conducted in the spherical coordinate system to reduce rapid location deviation between the PTZ and the moving object. To adapt different speeds of the object and avoid camera shaking under different zooms, an adaptive tracking window is designed to keep the object within the camera field of view. Experimental testing has been performed to evaluate the proposed SCAAT method. The results indicate that the SCATT can not only expand the effective following distance and zoom of the PTZ camera, but also effectively improve the accuracy and stability of active tracking for the moving object with large speed variations. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Electronics & Electrical Engineering is the property of Electronics & Electrical Engineering 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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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.5755/j02.eie.40016 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 60 Subjects: – SubjectFull: Computer vision Type: general – SubjectFull: Spherical coordinates Type: general – SubjectFull: Image stabilization Type: general – SubjectFull: Evidence gaps Type: general – SubjectFull: Cameras Type: general Titles: – TitleFull: Active Tracking of Moving Objects with Speed Variations Using a Novel PTZ Camera-based Machine Vision Technique. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Feng Lu – PersonEntity: Name: NameFull: Youchun Xu – PersonEntity: Name: NameFull: Yuan Zhu – PersonEntity: Name: NameFull: Zhichao Zhang – PersonEntity: Name: NameFull: Yulin Ma – PersonEntity: Name: NameFull: Kang Mao IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 13921215 Numbering: – Type: volume Value: 31 – Type: issue Value: 2 Titles: – TitleFull: Electronics & Electrical Engineering Type: main |
| ResultId | 1 |
