In this paper, a deep convolutional neural network based approach to the problem of automatically recognizing jersey numbers from soccer videos is presented. Two different jersey number vector encoding schemes are presented and compared to each other. The first treats every number as a separate class, while the second one treats each digit as a class. Additionally, the semi-automatic process for the annotation of a jersey number dataset consisting of 8281 jersey numbers is described. The best recognition rate of 0.83 was achieved by the proposed approach with data augmentation and without using dropout, compared to 0.4 for a more traditional histogram of oriented gradients (HOG) and support vector machine (SVM) based approach
In this work, we present a deep recurrent convolutional neural network approachto solve the problem ...
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona...
Deep learning approaches have successfully been applied to several image recognition tasks, such as ...
Player identification is an essential and complex task in sports video analysis. Different strategie...
Detection of player identity is challenging task in sport video content analysis. In case of soccer ...
Athlete identification is important for sport video content analysis since users often care about th...
Identifying players in soccer videos is a challenging task, especially in overview shots. Face recog...
SoccerNet is a large-scale video dataset for video undestanding in soccer. The dataset has been use...
We describe the technique used to train and customize deep learning models to detect, track, and ide...
Internet shopping has spread wide and into social networking. Someone may want to buy a shirt, acces...
The semantic understanding and the suitable definition of any video content become an attracting sea...
This paper deals with the automatic assignment of players' identities in images of sport scenes. The...
This paper builds on a prior work for player detection, and proposes an efficient and effective meth...
In this paper, we present an algorithm for automatically detecting events in soccer videos using 3D ...
This research investigates the use of deep convolutional neural networks for racing bib number recog...
In this work, we present a deep recurrent convolutional neural network approachto solve the problem ...
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona...
Deep learning approaches have successfully been applied to several image recognition tasks, such as ...
Player identification is an essential and complex task in sports video analysis. Different strategie...
Detection of player identity is challenging task in sport video content analysis. In case of soccer ...
Athlete identification is important for sport video content analysis since users often care about th...
Identifying players in soccer videos is a challenging task, especially in overview shots. Face recog...
SoccerNet is a large-scale video dataset for video undestanding in soccer. The dataset has been use...
We describe the technique used to train and customize deep learning models to detect, track, and ide...
Internet shopping has spread wide and into social networking. Someone may want to buy a shirt, acces...
The semantic understanding and the suitable definition of any video content become an attracting sea...
This paper deals with the automatic assignment of players' identities in images of sport scenes. The...
This paper builds on a prior work for player detection, and proposes an efficient and effective meth...
In this paper, we present an algorithm for automatically detecting events in soccer videos using 3D ...
This research investigates the use of deep convolutional neural networks for racing bib number recog...
In this work, we present a deep recurrent convolutional neural network approachto solve the problem ...
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona...
Deep learning approaches have successfully been applied to several image recognition tasks, such as ...