Viewpoint Distortion Compensation in Practical Surveillance Systems
Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to all previous work we wish to achieve this using from low-level, spatio-temporally local motion features used in commercial semi-automatic surveillance systems. We: (i) describe a dense a...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE
2015
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| Subjects: | |
| Online Access: | http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7160935 http://hdl.handle.net/20.500.11937/21572 |
| _version_ | 1848750626741157888 |
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| author | Arandjelovic, O. Pham, DucSon Venkatesh, S. |
| author2 | Enrico Magli |
| author_facet | Enrico Magli Arandjelovic, O. Pham, DucSon Venkatesh, S. |
| author_sort | Arandjelovic, O. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to all previous work we wish to achieve this using from low-level, spatio-temporally local motion features used in commercial semi-automatic surveillance systems. We: (i) describe a dense algorithm which uses motion features to estimate the perspective distortion at each image locus and then polls all such local estimates to arrive at the globally best estimate, (ii) present an alternative coarse algorithm which subdivides the image frame into blocks, and uses motion features to derive block-specific motion characteristics and constrain the relationships between these characteristics, with the perspective estimate emerging as a result of a global optimization scheme, and (iii) report the results of an evaluation using nine large sets acquired using existing close-circuit television (CCTV) cameras. Our findings demonstrate that both of the proposed methods are successful, their accuracy matching that of human labelling using complete visual data. |
| first_indexed | 2025-11-14T07:39:50Z |
| format | Conference Paper |
| id | curtin-20.500.11937-21572 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:39:50Z |
| publishDate | 2015 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-215722023-02-27T07:34:27Z Viewpoint Distortion Compensation in Practical Surveillance Systems Arandjelovic, O. Pham, DucSon Venkatesh, S. Enrico Magli Stefano Tubaro Anthony Vetro normalization Surveillance novelty Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to all previous work we wish to achieve this using from low-level, spatio-temporally local motion features used in commercial semi-automatic surveillance systems. We: (i) describe a dense algorithm which uses motion features to estimate the perspective distortion at each image locus and then polls all such local estimates to arrive at the globally best estimate, (ii) present an alternative coarse algorithm which subdivides the image frame into blocks, and uses motion features to derive block-specific motion characteristics and constrain the relationships between these characteristics, with the perspective estimate emerging as a result of a global optimization scheme, and (iii) report the results of an evaluation using nine large sets acquired using existing close-circuit television (CCTV) cameras. Our findings demonstrate that both of the proposed methods are successful, their accuracy matching that of human labelling using complete visual data. 2015 Conference Paper http://hdl.handle.net/20.500.11937/21572 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7160935 IEEE restricted |
| spellingShingle | normalization Surveillance novelty Arandjelovic, O. Pham, DucSon Venkatesh, S. Viewpoint Distortion Compensation in Practical Surveillance Systems |
| title | Viewpoint Distortion Compensation in Practical Surveillance Systems |
| title_full | Viewpoint Distortion Compensation in Practical Surveillance Systems |
| title_fullStr | Viewpoint Distortion Compensation in Practical Surveillance Systems |
| title_full_unstemmed | Viewpoint Distortion Compensation in Practical Surveillance Systems |
| title_short | Viewpoint Distortion Compensation in Practical Surveillance Systems |
| title_sort | viewpoint distortion compensation in practical surveillance systems |
| topic | normalization Surveillance novelty |
| url | http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7160935 http://hdl.handle.net/20.500.11937/21572 |