Ball-like observation model and multi-peak distribution estimation based particle filter for 3D Ping-pong ball tracking

Ziwei Deng, Xina Cheng, Takeshi Ikenaga

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

3D ball tracking is of great significance to ping-pong game analysis, which can be utilized to applications such as TV content and tactic analysis. To achieve a high success rate in ping-pong ball tracking, the main problems are the lack of unique features and the complexity of background, which make it difficult to distinguish the ball from similar noises. This paper proposes a ball-like observation model and a multi-peak distribution estimation to improve accuracy. For the balllike observation model, we utilize gradient feature from the edge of upper semicircle to construct a histogram, besides, ball-size likelihood is proposed to deal with the situation when noises are different in size with the ball. The multi-peak distribution estimation aims at obtaining a precise ball position in case the partidles' weight distribution has multiple peaks. Experiments are based on ping-pong videos recorded in an official match from 4 perspectives, which in total have 122 hit cases with 2 pairs of players. The tracking success rate finally reaches 99.33%.

本文言語English
ホスト出版物のタイトルProceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ390-393
ページ数4
ISBN(電子版)9784901122160
DOI
出版ステータスPublished - 2017 7 19
イベント15th IAPR International Conference on Machine Vision Applications, MVA 2017 - Nagoya, Japan
継続期間: 2017 5 82017 5 12

Other

Other15th IAPR International Conference on Machine Vision Applications, MVA 2017
国/地域Japan
CityNagoya
Period17/5/817/5/12

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • コンピュータ ビジョンおよびパターン認識

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