User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions
During the last decade, surveillance cameras have spread quickly; their spread is predicted to increase rapidly in the following years. Therefore, browsing and analyzing these vast amounts of created surveillance videos effectively is vital in surveillance applications. Recently, a video synopsis ap...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/3/1521 |
| _version_ | 1797623228014788608 |
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| author | Rasha Shoitan Mona M. Moussa Sawsan Morkos Gharghory Heba A. Elnemr Young-Im Cho Mohamed S. Abdallah |
| author_facet | Rasha Shoitan Mona M. Moussa Sawsan Morkos Gharghory Heba A. Elnemr Young-Im Cho Mohamed S. Abdallah |
| author_sort | Rasha Shoitan |
| collection | DOAJ |
| description | During the last decade, surveillance cameras have spread quickly; their spread is predicted to increase rapidly in the following years. Therefore, browsing and analyzing these vast amounts of created surveillance videos effectively is vital in surveillance applications. Recently, a video synopsis approach was proposed to reduce the surveillance video duration by rearranging the objects to present them in a portion of time. However, performing a synopsis for all the persons in the video is not efficacious for crowded videos. Different clustering and user-defined query methods are introduced to generate the video synopsis according to general descriptions such as color, size, class, and motion. This work presents a user-defined query synopsis video based on motion descriptions and specific visual appearance features such as gender, age, carrying something, having a baby buggy, and upper and lower clothing color. The proposed method assists the camera monitor in retrieving people who meet certain appearance constraints and people who enter a predefined area or move in a specific direction to generate the video, including a suspected person with specific features. After retrieving the persons, a whale optimization algorithm is applied to arrange these persons reserving chronological order, reducing collisions, and assuring a short synopsis video. The evaluation of the proposed work for the retrieval process in terms of precision, recall, and F1 score ranges from 83% to 100%, while for the video synopsis process, the synopsis video length compared to the original video is decreased by 68% to 93.2%, and the interacting tube pairs are preserved in the synopsis video by 78.6% to 100%. |
| first_indexed | 2024-03-11T09:25:41Z |
| format | Article |
| id | doaj.art-e069d76e834b478692f2afc2f7bba91b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T09:25:41Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e069d76e834b478692f2afc2f7bba91b2023-11-16T18:02:17ZengMDPI AGSensors1424-82202023-01-01233152110.3390/s23031521User Preference-Based Video Synopsis Using Person Appearance and Motion DescriptionsRasha Shoitan0Mona M. Moussa1Sawsan Morkos Gharghory2Heba A. Elnemr3Young-Im Cho4Mohamed S. Abdallah5Computer and Systems Department, Electronics Research Institute (ERI), Cairo 11843, EgyptComputer and Systems Department, Electronics Research Institute (ERI), Cairo 11843, EgyptComputer and Systems Department, Electronics Research Institute (ERI), Cairo 11843, EgyptComputer and Systems Department, Electronics Research Institute (ERI), Cairo 11843, EgyptDepartment of Computer Engineering, Gachon University, Seongnam 13415, Republic of KoreaDepartment of Computer Engineering, Gachon University, Seongnam 13415, Republic of KoreaDuring the last decade, surveillance cameras have spread quickly; their spread is predicted to increase rapidly in the following years. Therefore, browsing and analyzing these vast amounts of created surveillance videos effectively is vital in surveillance applications. Recently, a video synopsis approach was proposed to reduce the surveillance video duration by rearranging the objects to present them in a portion of time. However, performing a synopsis for all the persons in the video is not efficacious for crowded videos. Different clustering and user-defined query methods are introduced to generate the video synopsis according to general descriptions such as color, size, class, and motion. This work presents a user-defined query synopsis video based on motion descriptions and specific visual appearance features such as gender, age, carrying something, having a baby buggy, and upper and lower clothing color. The proposed method assists the camera monitor in retrieving people who meet certain appearance constraints and people who enter a predefined area or move in a specific direction to generate the video, including a suspected person with specific features. After retrieving the persons, a whale optimization algorithm is applied to arrange these persons reserving chronological order, reducing collisions, and assuring a short synopsis video. The evaluation of the proposed work for the retrieval process in terms of precision, recall, and F1 score ranges from 83% to 100%, while for the video synopsis process, the synopsis video length compared to the original video is decreased by 68% to 93.2%, and the interacting tube pairs are preserved in the synopsis video by 78.6% to 100%.https://www.mdpi.com/1424-8220/23/3/1521motion descriptorsvisual descriptorstrackletswhale optimizationvideo abstraction |
| spellingShingle | Rasha Shoitan Mona M. Moussa Sawsan Morkos Gharghory Heba A. Elnemr Young-Im Cho Mohamed S. Abdallah User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions Sensors motion descriptors visual descriptors tracklets whale optimization video abstraction |
| title | User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions |
| title_full | User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions |
| title_fullStr | User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions |
| title_full_unstemmed | User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions |
| title_short | User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions |
| title_sort | user preference based video synopsis using person appearance and motion descriptions |
| topic | motion descriptors visual descriptors tracklets whale optimization video abstraction |
| url | https://www.mdpi.com/1424-8220/23/3/1521 |
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