Please use this identifier to cite or link to this item: https://doi.org/10.1145/1865106.1865109
Title: MultiFusion: A boosting approach for multimedia fusion
Authors: Wang, X.
Kankanhalli, M. 
Keywords: Adaboost
Atomic event multimodal fusion
Boosting
Decision fusion
Issue Date: 2010
Source: Wang, X.,Kankanhalli, M. (2010). MultiFusion: A boosting approach for multimedia fusion. ACM Transactions on Multimedia Computing, Communications and Applications 6 (4). ScholarBank@NUS Repository. https://doi.org/10.1145/1865106.1865109
Abstract: The multimodal data usually contain complementary, correlated and redundant information. Thus, multimodal fusion is useful for many multisensor applications. Here, a novel multimodal fusion algorithm is proposed, which is referred to as "MultiFusion." The approach adopts a boosting structure where the atomic event is considered as the fusion unit. The correlation of multimodal data is used to form an overall classifier in each iteration. Moreover, by adopting the Adaboost-like structure, the overall fusion performance is improved. Both the simulation experiment and the real application show the effectiveness of the MultiFusion approach. Our approach can be applied in different multimodal applications to exploit the multimedia data characteristics and improve the performance. © 2010 ACM.
Source Title: ACM Transactions on Multimedia Computing, Communications and Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/39469
ISSN: 15516857
DOI: 10.1145/1865106.1865109
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