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Identification of Football Players based on Generic Fourier Descriptor Applied for the Recognition of Numbers

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Języki publikacji
EN
Abstrakty
EN
There are various possible approaches to the task of automatic identification of football players on video sequences. In the paper the numbers on jerseys are analysed and investigated. Firstly, the algorithm for the localisation of sport shirts and consecutively numbers is described. Secondly, the method for the recognition of the extracted numbers is proposed and experimentally investigated. The approach analysed in the paper applies the Generic Fourier Descriptor for the representation of extracted binary shapes of numbers.
Twórcy
  • West Pomeranian University of Technology, Szczecin, Zolnierska 52, 71-210, Szczecin, Poland
Bibliografia
  • [1] Ancona, N., Cicirelli, G., Stella, E., Distante, A. (2003). Ball detection in static images with Support Vector Machines for classification. Image and Vision Computing, 21, 675–692
  • [2] Andrade, E. L., Khan, E., Woods, J. C., Ghanbari, M. (2003). Player Identification In In Interactive Sport Scenes Using Region Space Analysis Prioror Information And Number Recognition, Melisa EU Project
  • [3] Assfalg, J., Bertini, M., Colombo, C., Del Bimbo, A., Nunziati, W. (2003). Semantic annotation of soccer videos: automatic highlights identification. Computer Vision and Image Understanding, 92, 285–305
  • [4] Frejlichowski D. (2011). A Method for Data Extraction from Video Sequences for Automatic Identification of Football Players Based on Their Numbers. In: G. Maino and G. L. Foresti (Eds.): ICIAP 2011, Part I, Lecture Notes in Computer Science, 6978, 355–364
  • [5] Frejlichowski, D. (2011). Recognition of Trademarks During Sport Television Broadcasts. In: M. Kamel and A. Campilho (Eds.): ICIAR 2011, Part II, Lecture Notes in Computer Science, 6754, 380–388
  • [6] Frejlichowski, D., Wierzba, P. (2008). A Face-Based Automatic Identification of Football Players During a Sport Television Broadcast. Polish Journal of Environmental Studies, 17 (4C), 406–409
  • [7] Leonardi, R., Migliorati, P. (2002). Semantic indexing of multimedia documents. IEEE MultiMedia, 9 (2), 44–51
  • [8] Li, B., Errico, J. H., Pan, H., Sezan, I. (2004). Bridging the semantic gap in sports video retrieval and summarization. Journal of Visual Communication and Image Representation, 15, 393–424
  • [9] Liu, J., Tong, X., Li, W., Wang, T., Zhang, Y., Wang, H. (2009). Automatic player detection, labeling and tracking in broadcast soccer video. Pattern Recognition Letters, 30 (2), 103–113
  • [10] Martin, R., Martinez, J. M. (2014). A semi-supervised system for players detection and tracking in multi-camera soccer videos. Multimedia Tools and Applications, 73 (3), 1617–1642
  • [11] Mentzelopoulos, M., Psarrou, A., Angelopoulou, A., Rodriguez J. G. (2013). Football Video Annotation Based on Player Motion Recognition Using Enhanced Entropy. Lecture Notes in Computer Science, 7903, 488–495
  • [12] Saric, M., Dujmic, H., Papic, V., Rozic, N. (2008). Player Number Localization and Recognition in Soccer Video using HSV Color Space and Internal Contours. International Conference on Signal and Image Processing
  • [13] Seo, Y., Choi, S. Kim H., Hong, K.S. (1997). Where are the ball and players? Soccer game analysis with color-based tracking and image mosaick. International Conference on Image Analysis and Processing, Florence, Italy, 196–203
  • [14] Vandenbroucke, N., Macaire, L., Postaire, J. G. (2003). Color image segmentation by pixel classification in an adapted hybrid color space: Application to soccer image analysis. Computer Vision and Image Understanding, 90, 190–216
  • [15] Yow, D., Yeo, B.-L., Yeung, M., Liu, B. (1995). Analysis and presentation of Soccer highlights from digital video, 2nd Asian Conference on Computer Vision
  • [16] Zhang, D., Lu, G. (2002). Generic Fourier descriptor for shape-based image retrieval. IEEE International Conference on Multimedia and Expo, 1, 425–428
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-68307a4d-00d0-4b9c-899f-f06a60498243
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