The SoccER software suite includes also a complete event detection system entirely developed and tested on a synthetic dataset including 500 min of game, and more than 1 million events.
Event detection, for instance, in a soccer match can help obtaining the statistics of events of the match. Counting the number of free kicks, fouls, tackles, etc. in a soccer game can be done by a manpower.
The research community is interested in developing automatic systems for the detection of events in video. This is particularly important in the field of sports data analytics. This paper presents an approach for identifying major complex events in soccer videos, starting from object detection and spatial relations between objects.
Automatic Soccer Video Event Detection Based on a Deep Neural Network Combined CNN and RNN Abstract: Soccer video semantic analysis has attracted a lot of researchers in the last few years. Many methods of machine learning have been applied to this task and have achieved some positive results, but the neural network method has not yet been used to this task from now.
Use gluoncv on soccerNet data for event detection. Contribute to guangyangai/soccer_event_detection development by creating an account on GitHub.
a novel hierarchical framework for soccer (football) video event sequence detection and classiﬁcation. Unlike most existing video classiﬁcation approaches, which focus on shot detection followed by shot-clustering for classiﬁcation, the proposed scheme perform a top-down video scene classiﬁcation which avoids shot clustering. This improves
Soccer event detection: reference implementation sought. As an experiment, I'm implementing some ideas to detect soccer events, especially goals.
process of event detection in a video sequence amounts to two foundamental steps, namely (i) spatio-temporal feature extraction and (ii) example classiﬁcation. Typically, feature extraction ap-proaches rely on highly engineered handcrafted features like the SIFT, which however are not able to generalize to more challeng-ing cases.
To extract the events automatically and quickly, we define the freeze moment as the key frame in a soccer event, so that the event can be represented by the freeze moment. Once we get the freeze moments, we can find the events by intercepting the fragment of soccer videos centered on the freeze moment.