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Chapter 5. Multimedia clustering based on cluster ensembles
fusion may not be advantageous (that is, there may exist modalities that do not contribute
positively to the obtention of a good partition of the data, see appendix B.2). In our opinion,
this constitutes one of the main strengths of our proposal, as it allows the user to employ
any modality created by feature-level fusion besides the original modalities of the data for
obtaining the final partition of the data.
This aprioripositive openhandedness entails two negative consequences: firstly, it increases
the computational complexity of the consensus process, although such inconvenience
can be sorted out by the application of the efficient consensus hierchical consensus architectures
proposed in chapter 3. The second drawback is the inclusion of the poorest modality
clustering results in the consensus clustering process, but this can be alleviated by the use
of the consensus-based self-refining procedures described in chapter 4, achieving notable
results when applied on the intermodal consensus clustering solutions.
In future works, the implementation of selection-based self-refining processes (see section
4.3) on multimodal cluster ensembles will be investigated, as we expect that it may yield
higher quality multimodal partitions than the ones presented in this chapter. Furthermore,
as already stated in chapter 4, it will be necessary to devise novel, more precise supraconsensus
functions, capable of selecting with a higher degree of accuracy the top quality
consensus clustering solution in an unsupervised manner.
5.5 Related publications
None of the work regarding multimedia clustering presented in this chapter has been published
yet. Nevertheless, we would like to hihglight the following paper, focused on applying
early fusion of modalities for conducting jointly multimodal data analysis and synthesis of
facial video sequences (Sevillano et al., 2009). The details of this work, published as a book
chapter, are presented next.
Authors: Xavier Sevillano, Javier Melenchón, Germán Cobo, Joan Claudi Socoró
and Francesc Alías
Title: Audiovisual Analysis and Synthesis for Multimodal Human-Computer Interfaces
In: Engineering the User Interface: From Research to Practice
Publisher: Springer
Editors: Miguel Redondo, Crescencio Bravo and Manuel Ortega
Pages: 179–194
Year: 2009
ISBN: 978-1-84800-135-0
Abstract: Multimodal signal processing techniques are called to play a salient role
in the implementation of natural computer-human interfaces. In particular, the development
of efficient interface front ends that emulate interpersonal communication
would benefit from the use of techniques capable of processing the visual and auditory
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