Spatial Object Tracking Using an Enhanced Mean Shift Method Based on Perceptual Spatial-Space Generation Model
Object tracking is one of the fundamental problems in computer vision, but existing efficient methods may not be suitable for spatial object tracking. Therefore, it is necessary to propose a more intelligent mathematical model. In this paper, we present an intelligent modeling method using an enhanc...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2013/420286 |
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| _version_ | 1832562642355486720 |
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| author | Pengcheng Han Junping Du Ming Fang |
| author_facet | Pengcheng Han Junping Du Ming Fang |
| author_sort | Pengcheng Han |
| collection | DOAJ |
| description | Object tracking is one of the fundamental problems in computer vision, but existing efficient methods may not be suitable for spatial object tracking. Therefore, it is necessary to propose a more intelligent mathematical model. In this paper, we present an intelligent modeling method using an enhanced mean shift method based on a perceptual spatial-space generation model. We use a series of basic and composite graphic operators to complete signal perceptual transformation. The Monte Carlo contour detection method could overcome the dimensions problem of existing local filters. We also propose the enhanced mean shift method with estimation of spatial shape parameters. This method could adaptively adjust tracking areas and eliminate spatial background interference. Extensive experiments on a variety of spatial video sequences with comparison to several state-of-the-art methods demonstrate that our method could achieve reliable and accurate spatial object tracking. |
| format | Article |
| id | doaj-art-db1b259fd43b4141930488ae97fc6658 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-db1b259fd43b4141930488ae97fc66582025-02-03T01:22:12ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/420286420286Spatial Object Tracking Using an Enhanced Mean Shift Method Based on Perceptual Spatial-Space Generation ModelPengcheng Han0Junping Du1Ming Fang2Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaBeijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaBeijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaObject tracking is one of the fundamental problems in computer vision, but existing efficient methods may not be suitable for spatial object tracking. Therefore, it is necessary to propose a more intelligent mathematical model. In this paper, we present an intelligent modeling method using an enhanced mean shift method based on a perceptual spatial-space generation model. We use a series of basic and composite graphic operators to complete signal perceptual transformation. The Monte Carlo contour detection method could overcome the dimensions problem of existing local filters. We also propose the enhanced mean shift method with estimation of spatial shape parameters. This method could adaptively adjust tracking areas and eliminate spatial background interference. Extensive experiments on a variety of spatial video sequences with comparison to several state-of-the-art methods demonstrate that our method could achieve reliable and accurate spatial object tracking.http://dx.doi.org/10.1155/2013/420286 |
| spellingShingle | Pengcheng Han Junping Du Ming Fang Spatial Object Tracking Using an Enhanced Mean Shift Method Based on Perceptual Spatial-Space Generation Model Journal of Applied Mathematics |
| title | Spatial Object Tracking Using an Enhanced Mean Shift Method Based on Perceptual Spatial-Space Generation Model |
| title_full | Spatial Object Tracking Using an Enhanced Mean Shift Method Based on Perceptual Spatial-Space Generation Model |
| title_fullStr | Spatial Object Tracking Using an Enhanced Mean Shift Method Based on Perceptual Spatial-Space Generation Model |
| title_full_unstemmed | Spatial Object Tracking Using an Enhanced Mean Shift Method Based on Perceptual Spatial-Space Generation Model |
| title_short | Spatial Object Tracking Using an Enhanced Mean Shift Method Based on Perceptual Spatial-Space Generation Model |
| title_sort | spatial object tracking using an enhanced mean shift method based on perceptual spatial space generation model |
| url | http://dx.doi.org/10.1155/2013/420286 |
| work_keys_str_mv | AT pengchenghan spatialobjecttrackingusinganenhancedmeanshiftmethodbasedonperceptualspatialspacegenerationmodel AT junpingdu spatialobjecttrackingusinganenhancedmeanshiftmethodbasedonperceptualspatialspacegenerationmodel AT mingfang spatialobjecttrackingusinganenhancedmeanshiftmethodbasedonperceptualspatialspacegenerationmodel |