In this paper, we present a new system of automatic character recognition in order to quickly and reliably identify soccer on the basis of their team number for sport’s scene understanding. First, the proposed approach extracts the number on the player’s jersey by using a chromaticity-based segmentation method. Then, the extracted character recognition is performed by template matching. Hence, the innovative combination of these two techniques leads to a more computationally efficient system for the player identification purpose than the state-of-the-art ones as demonstrated on real-world image large datasets
In this paper, a deep convolutional neural network based approach to the problem of automatically re...
Player identification is an essential and complex task in sports video analysis. Different strategie...
In this paper we present a people tracking algorithm which is able to detect and track soccer player...
This paper deals with the automatic assignment of players' identities in images of sport scenes. The...
In this paper, we present a new optical character recognition (OCR) approach which allows real-time,...
We present an athlete identification module forming part of a system for the personalization of spor...
This paper builds on a prior work for player detection, and proposes an efficient and effective meth...
In this work, an efficient, mere algorithm for detection and recognition of a soccer ball and player...
Projecte final de carrera fet en col.laboració amb Université Catholique de Louvain. Ecole Polytechn...
Color segmentation of images usually requires a manual selection and classification of samples to tr...
Identifying players in soccer videos is a challenging task, especially in overview shots. Face recog...
Athlete identification is important for sport video content analysis since users often care about th...
Detection of player identity is challenging task in sport video content analysis. In case of soccer ...
Abstract - We present an athlete recognition module designed for broadcast videos, forming part of a...
We describe the technique used to train and customize deep learning models to detect, track, and ide...
In this paper, a deep convolutional neural network based approach to the problem of automatically re...
Player identification is an essential and complex task in sports video analysis. Different strategie...
In this paper we present a people tracking algorithm which is able to detect and track soccer player...
This paper deals with the automatic assignment of players' identities in images of sport scenes. The...
In this paper, we present a new optical character recognition (OCR) approach which allows real-time,...
We present an athlete identification module forming part of a system for the personalization of spor...
This paper builds on a prior work for player detection, and proposes an efficient and effective meth...
In this work, an efficient, mere algorithm for detection and recognition of a soccer ball and player...
Projecte final de carrera fet en col.laboració amb Université Catholique de Louvain. Ecole Polytechn...
Color segmentation of images usually requires a manual selection and classification of samples to tr...
Identifying players in soccer videos is a challenging task, especially in overview shots. Face recog...
Athlete identification is important for sport video content analysis since users often care about th...
Detection of player identity is challenging task in sport video content analysis. In case of soccer ...
Abstract - We present an athlete recognition module designed for broadcast videos, forming part of a...
We describe the technique used to train and customize deep learning models to detect, track, and ide...
In this paper, a deep convolutional neural network based approach to the problem of automatically re...
Player identification is an essential and complex task in sports video analysis. Different strategie...
In this paper we present a people tracking algorithm which is able to detect and track soccer player...