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MM
2004
ACM
124views Multimedia» more  MM 2004»
14 years 9 days ago
An online-optimized incremental learning framework for video semantic classification
This paper considers the problems of feature variation and concept uncertainty in typical learning-based video semantic classification schemes. We proposed a new online semantic c...
Jun Wu, Xian-Sheng Hua, HongJiang Zhang, Bo Zhang
TRECVID
2008
13 years 8 months ago
Florida International University and University of Miami TRECVID 2008 - High Level Feature Extraction
This paper describes the FIU-UM group TRECVID 2008 high level feature extraction task submission. We have used a correlation based video semantic concept detection system for this...
Guy Ravitz, Lin Lin, Mei-Ling Shyu, Michael Armell...
SPIESR
2004
196views Database» more  SPIESR 2004»
13 years 8 months ago
Automatic textual annotation of video news based on semantic visual object extraction
In this paper, we present our work for automatic generation of textual metadata based on visual content analysis of video news. We present two methods for semantic object detectio...
Nozha Boujemaa, François Fleuret, Val&eacut...
SAMT
2007
Springer
136views Multimedia» more  SAMT 2007»
14 years 1 months ago
Ontology-Driven Semantic Video Analysis Using Visual Information Objects
In this paper, an ontology-driven approach for the semantic analysis of video is proposed. This approach builds on an ontology infrastructure and in particular a multimedia ontolog...
Georgios Th. Papadopoulos, Vasileios Mezaris, Ioan...
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
14 years 13 days ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang