Молимо вас користите овај идентификатор за цитирање или овај линк до ове ставке:
https://open.uns.ac.rs/handle/123456789/8460
Назив: | Automatic player position detection in basketball games | Аутори: | Ivanković, Zdravko Racković, Miloš Ivković, Miodrag |
Датум издавања: | 1-јан-2014 | Часопис: | Multimedia Tools and Applications | Сажетак: | This paper presents us with a framework for the automatic player position detection (APPD) in the game of basketball. Court players are detected in the images broadcasted via television stations. In them, at any point of time, the view is from only one camera. This makes the detection process much more difficult. The player detection is based on the mixture of non-oriented pictorial structures. The detection of body parts is performed by the Support Vector Machine (SVM) algorithm. The results of these detections are combined together with constraints on their locations, which specify the position of one body part with respect to the parent body part. In order to train the whole model, we used a latent form of SVM called the latent SVM (LSVM). Such approach generated the statistical accuracy of about 82 %, which represents one of the best results in basketball player detection framework. Beside players, the algorithm detected a certain number of false positive objects. These are mostly people from the audience and the referees as well. This paper contains a simple and robust solution to remove them all, based on the play court boundaries and the histogram comparison. Separating players in different teams is done by k-means clustering. The inputs to this algorithm are saturation histograms calculated on the jerseys. A spatial transformation is determined by the detected play court boundaries and the actual court measures. Using this transformation, points representing the location of detected players in TV images are mapped to the actual location of players on the court, which was the main goal of our research. The proposed solution is sound and efficient. In addition, it is backed up by the experimental results obtained using the model of the actual footage of basketball games. © 2013 Springer Science+Business Media New York. | URI: | https://open.uns.ac.rs/handle/123456789/8460 | ISSN: | 13807501 | DOI: | 10.1007/s11042-013-1580-z |
Налази се у колекцијама: | FTN Publikacije/Publications |
Приказати целокупан запис ставки
SCOPUSTM
Навођења
17
проверено 20.11.2023.
Преглед/и станица
33
Протекла недеља
18
18
Протекли месец
0
0
проверено 03.05.2024.
Google ScholarTM
Проверите
Алт метрика
Ставке на DSpace-у су заштићене ауторским правима, са свим правима задржаним, осим ако није другачије назначено.