Title
Blind late fusion in multimedia event retrieval.
Abstract
One of the challenges in Multimedia Event Retrieval is the integration of data from multiple modalities. A modality is defined as a single channel of sensory input,such as visual or audio. We also refer to this as data source. Previous research has shown that the integration of different data sources can improve performance compared to only using one source, but a clear insight of success factors of alternative fusion methods is still lacking. We introduce several new blind late fusion methods based on inversions and ratios of the state-of-the-art blind fusion methods and compare performance in both simulations and an international benchmark data set in multimedia event retrieval named TRECVID MED.The results showthat five of the proposed methods outperform the state-of-the-art methods in a case with sufficient training examples (100 examples). The novel fusion method named JRER is not only the best method with dependent data sources, but this method is also a robust method in all simulations with sufficient training examples.
Year
DOI
Venue
2016
10.1007/s13735-016-0112-9
IJMIR
Keywords
Field
DocType
Multimedia event retrieval, Multimodal, Integration, Late fusion
Data source,Data mining,Success factors,Multiple modalities,Computer science,TRECVID,Communication channel,Fusion,Event retrieval,Artificial intelligence,Multimedia,Machine learning
Journal
Volume
Issue
ISSN
5
4
2192-662X
Citations 
PageRank 
References 
1
0.37
11
Authors
6
Name
Order
Citations
PageRank
Maaike de Boer110.37
Klamer Schutte217318.26
Hao Zhang3536.42
Yi-Jie Lu461.15
C. W. Ngo54271211.46
Wessel Kraaij62420235.83