Abrupt shot boundary detection based on averaged two-dependence estimators learning
Video shot boundary detection is the process of automatically detecting the meaningful boundary in video data. It becomes an essential pre-processing step to video analysis, summarisation and other content-based retrieval. Video frame feature representation also plays an important role in the proces...
| Main Authors: | , , , |
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| Format: | Conference Paper |
| Published: |
IEEE
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/59364 |
| _version_ | 1848760459798249472 |
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| author | Tippaya, Sawitchaya Sitjongsataporn, S. Tan, Tele Chamnongthai, K. |
| author_facet | Tippaya, Sawitchaya Sitjongsataporn, S. Tan, Tele Chamnongthai, K. |
| author_sort | Tippaya, Sawitchaya |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Video shot boundary detection is the process of automatically detecting the meaningful boundary in video data. It becomes an essential pre-processing step to video analysis, summarisation and other content-based retrieval. Video frame feature representation also plays an important role in the process where it directly affects to the performance of the system. Histogram dissimilarity-based with the pre-processed features scheme are proposed to represent the temporal characteristic in videos. Motivated by the practical applications with moderate computational time, supervised abrupt shot boundary detection with averaged two-dependence estimators probabilistic classification learning scheme is proposed in this paper. The performance evaluation is performed by TRECVID 2007 videos dataset containing various types of video category. The performance of the proposed scheme can be expressed in terms of precision and recall to detect the correct abrupt video shot. |
| first_indexed | 2025-11-14T10:16:07Z |
| format | Conference Paper |
| id | curtin-20.500.11937-59364 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:16:07Z |
| publishDate | 2014 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-593642018-05-08T00:47:42Z Abrupt shot boundary detection based on averaged two-dependence estimators learning Tippaya, Sawitchaya Sitjongsataporn, S. Tan, Tele Chamnongthai, K. Video shot boundary detection is the process of automatically detecting the meaningful boundary in video data. It becomes an essential pre-processing step to video analysis, summarisation and other content-based retrieval. Video frame feature representation also plays an important role in the process where it directly affects to the performance of the system. Histogram dissimilarity-based with the pre-processed features scheme are proposed to represent the temporal characteristic in videos. Motivated by the practical applications with moderate computational time, supervised abrupt shot boundary detection with averaged two-dependence estimators probabilistic classification learning scheme is proposed in this paper. The performance evaluation is performed by TRECVID 2007 videos dataset containing various types of video category. The performance of the proposed scheme can be expressed in terms of precision and recall to detect the correct abrupt video shot. 2014 Conference Paper http://hdl.handle.net/20.500.11937/59364 10.1109/ISCIT.2014.7011968 IEEE restricted |
| spellingShingle | Tippaya, Sawitchaya Sitjongsataporn, S. Tan, Tele Chamnongthai, K. Abrupt shot boundary detection based on averaged two-dependence estimators learning |
| title | Abrupt shot boundary detection based on averaged two-dependence estimators learning |
| title_full | Abrupt shot boundary detection based on averaged two-dependence estimators learning |
| title_fullStr | Abrupt shot boundary detection based on averaged two-dependence estimators learning |
| title_full_unstemmed | Abrupt shot boundary detection based on averaged two-dependence estimators learning |
| title_short | Abrupt shot boundary detection based on averaged two-dependence estimators learning |
| title_sort | abrupt shot boundary detection based on averaged two-dependence estimators learning |
| url | http://hdl.handle.net/20.500.11937/59364 |