A semi-automatic system of web videos annotation and retrieval: application to events detection in soccer domain Online publication date: Wed, 06-Jul-2022
by Lamia Fatiha Kazi Tani; Abdelghani Ghomari; Mohammed Yassine Kazi Tani
International Journal of Computer Aided Engineering and Technology (IJCAET), Vol. 16, No. 4, 2022
Abstract: Annotations and retrieval of soccer videos on the web is a challenging task that concerns human lives including sports. In this paper, we propose a novel approach based on deep learning and ontology formalism to detect objects and to recognise events in soccer videos. To overcome the semantic gap between low and high level semantic annotation of videos, we use a deep neural network to extract low-level features through a complete method called mask R-CNN based ResNet-101 architecture as a backbone. Then, we create and populate soccer ontology in accordance to the output predictions of the mask R-CNN. We then create a smart system able to learn how to detect objects and to infer events in soccer videos. To validate our approach, we experimented on 40 soccer videos of FIFA World Cup 2018 downloaded from YouTube and we compare the obtained results with those of the state of the art.
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