[Football Image and Video Analysis]
The aim of the project was to address issues such as summarizing football videos to suit the interests of users, identifying critical moments and important events, statistical analysis of the game and predicting the outcome of the football game.
Mission of the project
Nowadays, analyzing football videos using computer vision techniques has attracted increasing attention. Significant events recognition, football video summarization, football results predictions, statistics, etc. are exciting applications in this area.
On the other hand, the deep learning approaches are very successful methods for image and video analyzing that need much data. Nevertheless, to the best of our knowledge, publicly available datasets in this area are small or individual, which are not useful for such deep learning-based approaches.
To meet this gap, we collected, annotated, and prepared a public dataset, namely IAUFD , for researches in this direction. The IAUFD contains 100,000 real-world images from 33 football videos in 2,508 minutes, annotated in 10 event categories. These categories are including images which show: the goal gate, center of the field, players happiness, red card, yellow card, the ball, stadium view, the referee, penalty position, and free-kick.
