Qualitative image analysis of group behaviour

Kawashima,; Yoshino,; Aoki, Ryôzô

doi:10.1109/cvpr.1994.323777

Cited by 25 publications

(10 citation statements)

References 3 publications

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“…Kawashima et al [19] propose an algorithm to analyze qualitatively group behaviour in soccer video sequences. The algorithm uses histogram backprojection to detect and classify each player in a colour image.…”

Section: Relevant Workmentioning

confidence: 99%

Video analysis of hockey play in selected game situations

Woodham

2009

Image and Vision Computing

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Section: Relevant Workmentioning

confidence: 99%

Video analysis of hockey play in selected game situations

Woodham

2009

Image and Vision Computing

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“…An example of single-view tracking with two grouped players is shown in Figure 2. After tracking of the players, an estimate of the category (color of uniform) is added to each measurement using a histogram-intersection method [23]. The result for each object 9 is a seven-element vector…”

Section: Filtering and Categorizing Of Playersmentioning

confidence: 99%

Multi-camera video surveillance for real-time analysis and reconstruction of soccer games

Ren

Orwell

et al. 2009

Machine Vision and Applications

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This version is available at https://strathprints.strath.ac.uk/29261/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Experimental results on real data from long sequences are demonstrated.

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“…When identifying player's team, Kawashima, Yoshino and AOK in [1] adopted the histogram back-projection, while Seo, Choi, Kim and Hong in [2] proposed the Color vertical distribution method. However, both lost part of the color spatial information and had poor robustness of discrimination.…”

Section: Introductionmentioning

confidence: 99%

Player classification algorithm based on digraph in soccer video

Sun

Cui

2014

2014 IEEE 7th Joint International Information Technology and Artificial Intelligence Conference

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Player classification method based on the tradition histograms lacks color spatial information, which leads to low classification performance, and, in addition, it needs priori template information. According to this, a novel player classification algorithm based on digraph was proposed in this paper. Firstly, the candidate players were extracted through the main color under the HSV Model Space of Color and equal-area rectangle partitioning strategy was adopted to partition the image. Secondly, HSV color space was quantified in each block and color histogram was extracted as color features. Thirdly, the distance among images was calculated according to the color features and the digraph was generated based on the distance matrix. Finally, the player classification was implemented by classifying the vertexes of digraph. Experimental results show that the proposed method, without priori template information, is an effective way of classifying the players positioned around the classification boundary with an average classification accuracy of 98.82%. Compared with traditional method, the proposed method has a remarkable promotion on classification effect.

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Qualitative image analysis of group behaviour

Cited by 25 publications

References 3 publications

Video analysis of hockey play in selected game situations

Video analysis of hockey play in selected game situations

Multi-camera video surveillance for real-time analysis and reconstruction of soccer games

Player classification algorithm based on digraph in soccer video

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