A novel Markov logic rule induction strategy for characterizing sports video footage

Windridge, David ORCID: https://orcid.org/0000-0001-5507-8516, Kittler, Josef, De Campos, Teofilo, Yan, Fei, Christmas, William and Khan, Aftab (2015) A novel Markov logic rule induction strategy for characterizing sports video footage. IEEE MultiMedia, 22 (2) . pp. 24-35. ISSN 1070-986X [Article] (doi:10.1109/MMUL.2014.36)

PDF - Final accepted version (with author's formatting)
Download (146kB) | Preview


The grounding of high-level semantic concepts is a key requirement of video annotation systems. Rule induction can thus constitute an invaluable intermediate step in characterizing protocol-governed domains, such as broadcast sports footage. We here set out a novel “clause grammar template” approach to the problem of rule-induction in video footage of court games that employs a second-order meta grammar for Markov Logic Network construction. The aim is to build an adaptive system for sports video annotation capable, in principle, both of learning ab initio and also adaptively transferring learning between distinct rule domains. The method is tested with respect to both a simulated game predicate generator and also real data derived from tennis footage via computer-vision based approaches including HOG3D based player-action classification, Hough-transform based court detection, and graph-theoretic ball-tracking. Experiments demonstrate that the method exhibits both error resilience and learning transfer in the court domain context. Moreover the clause template approach naturally generalizes to any suitably-constrained, protocol-governed video domain characterized by feature noise or detector error.

Item Type: Article
Keywords (uncontrolled): Video Annotation, Markov processes, Stochastic Logic, Markov logic network (MLN), Action Recognition, Behavior discovery, Statistical Relational Reasoning
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 19481
Notes on copyright: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Useful Links:
Depositing User: David Windridge
Date Deposited: 22 Apr 2016 10:28
Last Modified: 09 Jun 2021 17:45
URI: https://eprints.mdx.ac.uk/id/eprint/19481

Actions (login required)

View Item View Item


Activity Overview

Additional statistics are available via IRStats2.