Affective sports highlight detection

Author

Ren, Reede ; Jose, Jeomon ; He Yin

Author_Institution

Comput. Sci. Dept., Glasgow Univ., Glasgow, UK

fYear

2007

fDate

3-7 Sept. 2007

Firstpage

728

Lastpage

732

Abstract

This paper explores a psychological attention approach for sports highlight detection. A multiresolution autoregressive algorithm is proposed to fuse misaligned audio-visual time sequences and estimate an unified attention curve. Game highlights are found by ranking attention intensity; content-based events are filtered out by allocating local attention peaks. The test bed includes six complete football games from World Cup 2002, 2006 and Champion League 2006, and two content suppliers, BBC and ITV. Two evaluations are presented, the comparison on average attention and event attention, and the ranking of goal events. Experiments show this fusion framework is robust on different data collections.

Keywords

autoregressive processes; sport; affective sports highlight detection; average attention; content-based events; data collections; event attention; football games; fusion framework; game highlights; goal events; local attention peaks; misaligned audio-visual time sequences; multiresolution autoregressive algorithm; psychological attention; ranking attention intensity; unified attention curve; Estimation; Games; Markov processes; Psychology; Semantics; Streaming media; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference, 2007 15th European

Conference_Location

Poznan

Print_ISBN

978-839-2134-04-6

Type

conf

Filename

7098899