title: Multilevel Chinese takeaway process and label-based processes for rule induction in the context of automated sports video annotation.
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.
authors.forename: Aftab
authors.initials: A
authors.lastname: Khan
authors.forename: David
authors.initials: D
authors.lastname: Windridge
authors.forename: Josef
authors.initials: J
authors.lastname: Kittler
mesh_terms: D001334:Automobile Driving; D016000:Cluster Analysis; D066289:Data Curation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008390:Markov Chains; D013177:Sports; D013715:Tennis; D014741:Video Recording / Q000379:methods*