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Knowledge-Assisted Ranking: A Visual Analytic Application for Sport Event Data / David Chung; Philip Legg; Matthew Parry; Rhodri Bown; Iwan Griffiths; Robert Laramee; Min Chen

IEEE Computer Graphics and Applications, Pages: 1 - 1

Swansea University Author: Laramee, Bob

DOI (Published version): 10.1109/MCG.2015.25

Abstract

Organizing sport video data for performance analysis can be challenging, especially when this involvesmultiple attributes, and the criteria for sorting frequently changes depending on the user’s task. In thiswork, we propose a visual analytic system to convert a user’s knowledge on rankings to suppo...

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Published in: IEEE Computer Graphics and Applications
Published: 2015
Online Access: http://cs.swan.ac.uk/~csbob/research/
URI: https://cronfa.swan.ac.uk/Record/cronfa22327
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Abstract: Organizing sport video data for performance analysis can be challenging, especially when this involvesmultiple attributes, and the criteria for sorting frequently changes depending on the user’s task. In thiswork, we propose a visual analytic system to convert a user’s knowledge on rankings to support such aprocess. The system enables users to specify a sort requirement in a flexible manner without dependingon specific knowledge about individual sort keys. We use regression techniques to train different analyticalmodels for different types of sorting requirements. We use visualization to facilitate the discovery ofknowledge at different stages of the visual analytic process. This includes visualizing the parameters of theranking model, visualizing the results of a sort query for interactive exploration, and the playback of sortedvideo clips. We demonstrate the system with a case study in rugby to find key instances for analyzing teamand player performance.
Keywords: data visualization, visual analytics
College: College of Science
Start Page: 1
End Page: 1