Until recently tactical analysis in elite soccer were based on observational data using
variables which discard most contextual information. Analyses of team tactics require …

Abstract Multiple Object Tracking (MOT) has gained increasing attention due to its academic
and commercial potential. Although different approaches have been proposed to tackle this …

Tracking objects in soccer videos is extremely important to gather both player and team
statistics, whether it is to estimate the total distance run, the ball possession or the team …

Deep convolutional neural networks (DCNNs) trained on a large number of images with
strong pixel-level annotations have recently significantly pushed the state-of-art in semantic …

Recent developments in video analysis of sports and computer vision techniques have
achieved significant improvements to enable a variety of critical operations. To provide …

The rapid progress in artificial intelligence (AI) and machine learning has opened
unprecedented analytics possibilities in various team and individual sports, including …

Although refinement is commonly used in visual tasks to improve pre-obtained results, it has
not been studied for Multiple Object Tracking (MOT) tasks. This could be attributed to two …

Multi-person event recognition is a challenging task, often with many people active in the
scene but only a small subset contributing to an actual event. In this paper, we propose a …

Group activity recognition plays a fundamental role in a variety of applications, eg sports
video analysis and intelligent surveillance. How to model the spatio-temporal contextual …

Identity switches caused by inter-object interactions remain a critical problem for multi-player
tracking in real-world sports video analysis. Existing approaches utilizing the appearance …