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IJCAI
2003
14 years 1 months ago
Mining Video Associations for Efficient Database Management
To support more efficient video database management, this paper explores the concept of video association mining, with which the association patterns are characterized by sequenti...
Xingquan Zhu, Xindong Wu
MM
2000
ACM
98views Multimedia» more  MM 2000»
14 years 4 months ago
Key-frame extraction and shot retrieval using nearest feature line (NFL)
Query by key frame or video example is a convenient and often effective way to search in video database. This paper proposes a new approach to support such searches. The main cont...
Li Zhao, Wei Qi, Stan Z. Li, Shi-Qiang Yang, HongJ...
ICIAR
2005
Springer
14 years 6 months ago
A Multi-level Framework for Video Shot Structuring
Video shots provide the most basic meaningful segments for video analysis and understanding. In this paper, we present a detection and classification framework for the video shot ...
Yun Zhai, Mubarak Shah
MMM
2005
Springer
152views Multimedia» more  MMM 2005»
14 years 6 months ago
Semantic Video Summarization Using Mutual Reinforcement Principle and Shot Arrangement Patterns
We propose a novel semantic video summarization framework, which generates video skimmings that guarantee both the balanced content coverage and the visual coherence. First, we co...
Shi Lu, Michael R. Lyu, Irwin King
MMSP
2008
IEEE
144views Multimedia» more  MMSP 2008»
14 years 6 months ago
Spatiotemporal semantic video segmentation
—In this paper, we propose a framework to extend semantic labeling of images to video shot sequences and achieve efficient and semantic-aware spatiotemporal video segmentation. ...
Eric Galmar, Thanos Athanasiadis, Benoit Huet, Yan...
ICPR
2008
IEEE
14 years 6 months ago
Automatic video annotation with adaptive number of key words
Retrieving videos using key words requires obtaining the semantic features of the videos. Most work reported in the literature focuses on annotating a video shot with a fixed numb...
Fangshi Wang, Wei Lu, Jingen Liu, Mubarak Shah, De...