User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shoitan, Rasha | - |
dc.contributor.author | Moussa, Mona M. | - |
dc.contributor.author | Gharghory, Sawsan Morkos | - |
dc.contributor.author | Elnemr, Heba A. | - |
dc.contributor.author | Cho, Young-Im | - |
dc.contributor.author | Abdallah, Mohamed S. | - |
dc.date.accessioned | 2023-03-14T07:40:28Z | - |
dc.date.available | 2023-03-14T07:40:28Z | - |
dc.date.created | 2023-03-10 | - |
dc.date.issued | 2023-02 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/87106 | - |
dc.description.abstract | 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%. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.relation.isPartOf | SENSORS | - |
dc.title | User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000929596400001 | - |
dc.identifier.doi | 10.3390/s23031521 | - |
dc.identifier.bibliographicCitation | SENSORS, v.23, no.3 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.scopusid | 2-s2.0-85147895768 | - |
dc.citation.title | SENSORS | - |
dc.citation.volume | 23 | - |
dc.citation.number | 3 | - |
dc.contributor.affiliatedAuthor | Cho, Young-Im | - |
dc.contributor.affiliatedAuthor | Abdallah, Mohamed S. | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | motion descriptors | - |
dc.subject.keywordAuthor | visual descriptors | - |
dc.subject.keywordAuthor | tracklets | - |
dc.subject.keywordAuthor | whale optimization | - |
dc.subject.keywordAuthor | video abstraction | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Instruments & Instrumentation | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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