|Institution:||KTH Royal Institute of Technology|
|Keywords:||Natural Sciences; Computer and Information Science; Computer Science; Naturvetenskap; Data- och informationsvetenskap; Datavetenskap (datalogi)|
|Full text PDF:||http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-156251|
In order to estimate the distance between a moving camera and a golfball, the projective ball size in images is measured. Two methods are evaluated based on their ability to detect golf balls in TV broadcasting images: circular Hough transform and scale-space blob detection. A tracking algorithm is then proposed where, given a known ball position, a search window is used, adapting for ball speed in the image plane, ballsize and previous window size.Various pre-processing methods are also discussed, including deinterlacing and an approximate background subtraction method. Experimentsshows that none of these pre-processing methods significantly improves the performance in terms of ball detection, although tendencies of improvement is noticed in some test sequences.The tracking algorithm is evaluated by using sequences from TV broadcasts of golf competitions. The algorithm performs well under certain circumstances, where the projective size of the ball is the key to accurate measurements of the distance between ball and camera. The noisy input data however introduces noise also to the size estimations,resulting in noisy distance estimations. Additionally, the test sequences contains no ground truth for the actual distance between ball and camera,and the accuracy of the method could therefore only be determined in terms of noise analysis.