Ball Detection using Yolo and Mask R-CNN (CROSBI ID 675790)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Burić, Matija ; Pobar, Miran ; Ivašić-Kos, Marina
engleski
Ball Detection using Yolo and Mask R-CNN
Many computer vision applications rely on accurate and fast object detection, and in our case, ball detection serves as a prerequisite for action recognition in handball scenes. We compare the performance of two of the state-of- the-art convolutional neural network-based object detectors for the task of ball detection in non-staged, real-world conditions. The comparison is performed in terms of speed and accuracy measures on a dataset comprising custom handball footage and a sample of images obtained from the Internet. The performance of the models is compared with and without additional training with examples from our dataset.
action recognition ; object detection ; ball detection
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Podaci o prilogu
319-323.
2018.
objavljeno
10.1109/CSCI46756.2018.00068
Podaci o matičnoj publikaciji
Proceedings - 2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018
Las Vegas (NV):
978-172811360-9
Podaci o skupu
2018 International Conference on Computational Science and Computational Intelligence (CSCI 2018)
predavanje
13.12.2018-15.12.2018
Las Vegas (NV), Sjedinjene Američke Države
Povezanost rada
Informacijske i komunikacijske znanosti, Računarstvo