Video shot boundary detection based on candidate segment selection and transition pattern analysis
© 2015 IEEE.Video shot boundary detection or shot segmentation is an integral part of semantic video analysis. The objective of this process is to automatically detect the boundary region in video that further segment the video into meaningful shot, scene and so on. Video frame feature representatio...
| Main Authors: | , , , , |
|---|---|
| Format: | Conference Paper |
| Published: |
2015
|
| Online Access: | http://hdl.handle.net/20.500.11937/52157 |
| _version_ | 1848758859687002112 |
|---|---|
| author | Tippaya, S. Sitjongsataporn, S. Tan, Tele Chamnongthai, K. Khan, M. |
| author_facet | Tippaya, S. Sitjongsataporn, S. Tan, Tele Chamnongthai, K. Khan, M. |
| author_sort | Tippaya, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2015 IEEE.Video shot boundary detection or shot segmentation is an integral part of semantic video analysis. The objective of this process is to automatically detect the boundary region in video that further segment the video into meaningful shot, scene and so on. Video frame feature representation therefore plays an important role in the process where it directly affects the overall performance of the system. The transition points between meaningful scenes can be emphasised by the extracted features. In this paper, a combination of global and local feature descriptors is implemented to represent the temporal characteristic in video. Motivated by computational efficiency and practical implementation, a video shot boundary detection scheme using adaptive thresholding is proposed. Candidate segment selection and transition pattern analysis are implemented by the dissimilarity score between video frames. The performance evaluation is constructed on a golf video dataset using the precision and recall performance measures. |
| first_indexed | 2025-11-14T09:50:41Z |
| format | Conference Paper |
| id | curtin-20.500.11937-52157 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:50:41Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-521572017-09-13T15:38:44Z Video shot boundary detection based on candidate segment selection and transition pattern analysis Tippaya, S. Sitjongsataporn, S. Tan, Tele Chamnongthai, K. Khan, M. © 2015 IEEE.Video shot boundary detection or shot segmentation is an integral part of semantic video analysis. The objective of this process is to automatically detect the boundary region in video that further segment the video into meaningful shot, scene and so on. Video frame feature representation therefore plays an important role in the process where it directly affects the overall performance of the system. The transition points between meaningful scenes can be emphasised by the extracted features. In this paper, a combination of global and local feature descriptors is implemented to represent the temporal characteristic in video. Motivated by computational efficiency and practical implementation, a video shot boundary detection scheme using adaptive thresholding is proposed. Candidate segment selection and transition pattern analysis are implemented by the dissimilarity score between video frames. The performance evaluation is constructed on a golf video dataset using the precision and recall performance measures. 2015 Conference Paper http://hdl.handle.net/20.500.11937/52157 10.1109/ICDSP.2015.7252033 restricted |
| spellingShingle | Tippaya, S. Sitjongsataporn, S. Tan, Tele Chamnongthai, K. Khan, M. Video shot boundary detection based on candidate segment selection and transition pattern analysis |
| title | Video shot boundary detection based on candidate segment selection and transition pattern analysis |
| title_full | Video shot boundary detection based on candidate segment selection and transition pattern analysis |
| title_fullStr | Video shot boundary detection based on candidate segment selection and transition pattern analysis |
| title_full_unstemmed | Video shot boundary detection based on candidate segment selection and transition pattern analysis |
| title_short | Video shot boundary detection based on candidate segment selection and transition pattern analysis |
| title_sort | video shot boundary detection based on candidate segment selection and transition pattern analysis |
| url | http://hdl.handle.net/20.500.11937/52157 |