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학술대회 Scene-segmented Video Information Annotation System V2.0
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저자
이호재, 곽창욱, 손정우, 함경준, 한민호, 김선중
발행일
202010
출처
International Conference on Multimedia (MM) 2020, pp.4506-4508
DOI
https://dx.doi.org/10.1145/3394171.3414396
협약과제
20ZH1200, 초실감 입체공간 미디어·콘텐츠 원천기술연구, 이태진
초록
We have built the scene-segmented video information annotation system and upgraded it to version 2.0. The system imports the video by user selection and splits into the scene units. Each scene clips are annotated by the integration of visual features derived by state-of-the-art deep learning techniques. The proposed system uses the multiview deep convolutional neural network for video segmentation and a supervised movie caption model for video annotation. Each functionality has been installed in two different sub-systems and connected through the web interface. The web interface allows connecting to external content providers in order to expand the capability of the system.
KSP 제안 키워드
Convolution neural network(CNN), Deep convolutional neural networks, Video Annotation, Video Segmentation, Visual features, annotation system, deep learning(DL), state-of-The-Art, user selection, version 2, video information