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Multilevel Chinese Takeaway Process and Label-Based Processes for Rule Induction in the Context of Automated Sports Video Annotation

Lookup NU author(s): Dr Aftab Khan

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Abstract

We propose four variants of a novel hierarchical hidden Markov models strategy for rule induction in the context of automated sports video annotation including a multilevel Chinese takeaway process (MLCTP) based on the Chinese restaurant process and a novel Cartesian product label-based hierarchical bottom-up clustering (CLHBC) method that employs prior information contained within label structures. Our results show significant improvement by comparison against the flat Markov model: optimal performance is obtained using a hybrid method, which combines the MLCTP generated hierarchical topological structures with CLHBC generated event labels. We also show that the methods proposed are generalizable to other rule-based environments including human driving behavior and human actions.

Publication metadata

Author(s): Khan A, Windridge D, Kittler J

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Cybernetics

Year: 2014

Print publication date: 27/01/2014

ISSN (print): 2168-2267

ISSN (electronic): 2168-2275

Publisher: IEEE

URL: http://dx.doi.org/10.1109/TCYB.2014.2299955

DOI: 10.1109/TCYB.2014.2299955

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