Movie scene segmentation using object detection and set theory
Movie data has a prominent role in the exponential growth of multimedia data over the Internet, and its analysis has become a hot topic with computer vision. The initial step towards movie analysis is scene segmentation. In this article, we investigated this problem through a novel intelligent Convo...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-06-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147719845277 |
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| _version_ | 1832556852236255232 |
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| author | Ijaz Ul Haq Khan Muhammad Tanveer Hussain Soonil Kwon Maleerat Sodanil Sung Wook Baik Mi Young Lee |
| author_facet | Ijaz Ul Haq Khan Muhammad Tanveer Hussain Soonil Kwon Maleerat Sodanil Sung Wook Baik Mi Young Lee |
| author_sort | Ijaz Ul Haq |
| collection | DOAJ |
| description | Movie data has a prominent role in the exponential growth of multimedia data over the Internet, and its analysis has become a hot topic with computer vision. The initial step towards movie analysis is scene segmentation. In this article, we investigated this problem through a novel intelligent Convolutional Neural Network (CNN) based three folded framework. The first fold segments the input movie into shots, the second fold detects objects in the segmented shots and the third fold performs object-based shots matching for detecting scene boundaries. Texture and shape features are fused for shots segmentation, and each shot is represented by a set of detected objects acquired from a light-weight CNN model. Finally, we apply set theory with the sliding window–based approach to integrate the same shots to decide scene boundaries. The experimental evaluation indicates that our proposed approach outran the existing movie scene segmentation approaches. |
| format | Article |
| id | doaj-art-d855a092152a429e8f9adcb1f51a038b |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2019-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-d855a092152a429e8f9adcb1f51a038b2025-02-03T05:44:18ZengWileyInternational Journal of Distributed Sensor Networks1550-14772019-06-011510.1177/1550147719845277Movie scene segmentation using object detection and set theoryIjaz Ul Haq0Khan Muhammad1Tanveer Hussain2Soonil Kwon3Maleerat Sodanil4Sung Wook Baik5Mi Young Lee6Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, Republic of KoreaDepartment of Software, Sejong University, Seoul, Republic of KoreaIntelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, Republic of KoreaDepartment of Software, Sejong University, Seoul, Republic of KoreaKing Mongkut’s University of Technology North Bangkok, Bangkok, ThailandIntelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, Republic of KoreaIntelligent Media Laboratory, Digital Contents Research Institute, Sejong University, Seoul, Republic of KoreaMovie data has a prominent role in the exponential growth of multimedia data over the Internet, and its analysis has become a hot topic with computer vision. The initial step towards movie analysis is scene segmentation. In this article, we investigated this problem through a novel intelligent Convolutional Neural Network (CNN) based three folded framework. The first fold segments the input movie into shots, the second fold detects objects in the segmented shots and the third fold performs object-based shots matching for detecting scene boundaries. Texture and shape features are fused for shots segmentation, and each shot is represented by a set of detected objects acquired from a light-weight CNN model. Finally, we apply set theory with the sliding window–based approach to integrate the same shots to decide scene boundaries. The experimental evaluation indicates that our proposed approach outran the existing movie scene segmentation approaches.https://doi.org/10.1177/1550147719845277 |
| spellingShingle | Ijaz Ul Haq Khan Muhammad Tanveer Hussain Soonil Kwon Maleerat Sodanil Sung Wook Baik Mi Young Lee Movie scene segmentation using object detection and set theory International Journal of Distributed Sensor Networks |
| title | Movie scene segmentation using object detection and set theory |
| title_full | Movie scene segmentation using object detection and set theory |
| title_fullStr | Movie scene segmentation using object detection and set theory |
| title_full_unstemmed | Movie scene segmentation using object detection and set theory |
| title_short | Movie scene segmentation using object detection and set theory |
| title_sort | movie scene segmentation using object detection and set theory |
| url | https://doi.org/10.1177/1550147719845277 |
| work_keys_str_mv | AT ijazulhaq moviescenesegmentationusingobjectdetectionandsettheory AT khanmuhammad moviescenesegmentationusingobjectdetectionandsettheory AT tanveerhussain moviescenesegmentationusingobjectdetectionandsettheory AT soonilkwon moviescenesegmentationusingobjectdetectionandsettheory AT maleeratsodanil moviescenesegmentationusingobjectdetectionandsettheory AT sungwookbaik moviescenesegmentationusingobjectdetectionandsettheory AT miyounglee moviescenesegmentationusingobjectdetectionandsettheory |