Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/41141
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dc.titleA robust Hough-based algorithm for partial ellipse detection in broadcast soccer video
dc.contributor.authorYu, X.
dc.contributor.authorLeong, H.W.
dc.contributor.authorXu, C.
dc.contributor.authorTian, Q.
dc.date.accessioned2013-07-04T08:20:34Z
dc.date.available2013-07-04T08:20:34Z
dc.date.issued2004
dc.identifier.citationYu, X.,Leong, H.W.,Xu, C.,Tian, Q. (2004). A robust Hough-based algorithm for partial ellipse detection in broadcast soccer video. 2004 IEEE International Conference on Multimedia and Expo (ICME) 3 : 1555-1558. ScholarBank@NUS Repository.
dc.identifier.isbn0780386035
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41141
dc.description.abstractThis paper presents a robust Hough-based algorithm for partial slightly-oblique ellipse detection in broadcast soccer video. The successful identification of the ellipses will significantly facilitate soccer video analysis. The existing standard and various modified ellipse Hough transforms measure a cell in the Hough space as though the ellipse defined by the cell were a complete ellipse. Hence, they are not robust when they are applied to detect the partial ellipses appearing in broadcast soccer video. This paper proposes a new measure function that is able to fairly measure whole and partial ellipses. With the improved measure function, we propose an algorithm to detect the partial ellipses in broadcast, soccer video. The proposed algorithm first estimates the target ellipse by using the symmetry of the ellipse and the domain knowledge of soccer video. Then for each estimated ellipse, the algorithm searches around the estimated ellipses to find the ellipse with the highest measured value. Our algorithm is efficient and memory-little, i.e. it overcomes two main problems of the standard ellipse Hough transform. More importantly, the proposed algorithm is much more robust than the existing ellipse Hough transforms. Experimental results show that the proposed algorithm achieves above 96% recall and 100% precision. Our algorithm may be the first one that is able to detect ellipses from commercial video in pseudo real-time.
dc.sourceScopus
dc.subjectEllipse Detection
dc.subjectHough Transform
dc.subjectMeasure Function
dc.subjectSoccer Video
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitle2004 IEEE International Conference on Multimedia and Expo (ICME)
dc.description.volume3
dc.description.page1555-1558
dc.identifier.isiutNOT_IN_WOS
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