TrackNet: A Deep Learning Network for Tracking High-speed and Tiny Objects in Sports Applications

Yu Chuan Huang, I. No Liao, Ching Hsuan Chen, Tsi-Ui Ik, Wen-Chih Peng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Ball trajectory data are one of the most fundamental and useful information in the evaluation of players' performance and analysis of game strategies. It is still challenging to recognize and position a high-speed and tiny ball accurately from an ordinary video. In this paper, we develop a deep learning network, called TrackNet, to track the tennis ball from broadcast videos in which the ball images are small, blurry, and sometimes with afterimage tracks or even invisible. The proposed heatmap-based deep learning network is trained to not only recognize the ball image from a single frame but also learn flying patterns from consecutive frames. The network is evaluated on the video of the men's singles final at the 2017 Summer Universiade, which is available on YouTube. The precision, recall, and F1 -measure reach 99.7%, 97.3%, and 98.5%, respectively. To prevent overfitting, 9 additional videos are partially labeled together with a subset from the previous dataset to implement 10-fold cross-validation, and the precision, recall, and F1 -measure are 95.3%, 75.7%, and 84.3%, respectively.
Original languageEnglish
Title of host publication16th IEEE International Workshop of Content-Aware Video Analysis (CAVA 2019) in conjunction with the 16th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS 2019)
PublisherIEEE
ISBN (Electronic)9781728109909
DOIs
StatePublished - 18 Sep 2019
Event16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019 - Taipei, Taiwan
Duration: 18 Sep 201921 Sep 2019

Publication series

Name2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019

Conference

Conference16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019
CountryTaiwan
CityTaipei
Period18/09/1921/09/19

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