Event recognition and classification in sports video using HMM. (5th March 2020)
- Record Type:
- Journal Article
- Title:
- Event recognition and classification in sports video using HMM. (5th March 2020)
- Main Title:
- Event recognition and classification in sports video using HMM
- Authors:
- Ellappan, Vijayan
Rajkumar, R. - Abstract:
- Sports event recognition and classification is a challenging task due to the number of possible categories. On one hand, how to characterise legitimate occasion classification names and how to acquire preparing tests for these classes should be investigated; then again, it is non-inconsequential to accomplish acceptable order execution. To address these issues, we propose the use of the spatio-temporal behaviour of an object in the footage as an embodiment of a semantic event. This is accomplished by modelling the evaluation of the position of the object with a hidden Markov model (HMM). Snooker is used as an example for this purpose of research. The system firstly parses the video sequence based on the geometry of the content in the camera view and classifies the footage as a particular view type. Secondly, we consider the relative position of the white ball on the snooker table over the duration of a clip to embody semantic events. The temporal behaviour of the white ball is modelled using a HMM where each model is representative of a particular semantic event.
- Is Part Of:
- International journal of computer aided engineering and technology. Volume 12:Number 3(2020)
- Journal:
- International journal of computer aided engineering and technology
- Issue:
- Volume 12:Number 3(2020)
- Issue Display:
- Volume 12, Issue 3 (2020)
- Year:
- 2020
- Volume:
- 12
- Issue:
- 3
- Issue Sort Value:
- 2020-0012-0003-0000
- Page Start:
- 318
- Page End:
- 327
- Publication Date:
- 2020-03-05
- Subjects:
- hidden Markov model -- HMM -- event recognition
Computer-aided engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.inderscience.com/jhome.php?jcode=ijcaet ↗
http://www.inderscience.com/ ↗ - Languages:
- English
- ISSNs:
- 1757-2657
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 12820.xml