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학술대회 Scene Boundary Detection with Graph Embedding
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저자
손정우, 박원주, 한민호, 김선중
발행일
201702
출처
International Conference on Advanced Communication Technology (ICACT) 2017, pp.451-453
DOI
https://dx.doi.org/10.23919/ICACT.2017.7890129
협약과제
16ZC2200, 오픈 시나리오 기반 프로그래머블 인터랙티브 미디어 창작 서비스 플랫폼 개발, 박종현
초록
Scene boundary detection is a well-known task in both computer vision and machine learning. Due to the different characteristics of scene boundaries according to applied aspects, scene boundary detection can be casted into an unsupervised learning with multi-view data. This paper suggested the scene boundary detection method which adopts several ways to handle information in multi-view data. More specifically, in the proposed method, a shot is represented with multiple features and then their relations are represented with multiple affinity graphs. In this situation, this paper explains how multiple graphs are combined in a single complementary graph without information loss. In experiments, we tested five methods to combine graphs by using six Korean TV-series.
키워드
Clustering multi-view data, Graph embedding, Scene boundary detection, Spectral clustering, Video segmentation
KSP 제안 키워드
Clustering multi-view data, Complementary graph, Computer Vision(CV), Detection Method, Graph Embedding, Information Loss, Multiple graphs, Spectral clustering, Video Segmentation, affinity graphs, machine Learning