Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/41141
Title: A robust Hough-based algorithm for partial ellipse detection in broadcast soccer video
Authors: Yu, X.
Leong, H.W. 
Xu, C.
Tian, Q.
Keywords: Ellipse Detection
Hough Transform
Measure Function
Soccer Video
Issue Date: 2004
Source: Yu, 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.
Abstract: This 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.
Source Title: 2004 IEEE International Conference on Multimedia and Expo (ICME)
URI: http://scholarbank.nus.edu.sg/handle/10635/41141
ISBN: 0780386035
Appears in Collections:Staff Publications

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