In this technical demonstration we show the current version of our trademark detection and recognition system that has been developed in collaboration with a sport marketing firm 1 with the aim of evaluating the visibility of advertising trademarks in broadcast sporting events. We propose a semi-automatic system for detecting and retrieving trade-mark appearances in sports videos. A human annotator supervises the results of the automatic annotation through an interface that shows the time and the position of the detected trademarks; due to this fact the aim of the system is to provide a good recall figure, so that the supervisor can safely skip the parts of the video that have been marked as not containing a trademark, thus speeding up his ...
Content-based indexing is fundamental to support and sustain the ongoing growth of broadcasted sport...
We present an athlete identification module forming part of a system for the personalization of spor...
In this paper we discuss the problem of how to discriminate moments of interest on videos or live br...
In this paper we describe a system for automatic detection and recognition of trademarks in sports v...
In this paper we describe a system for detection and retrieval of trademarks appearing in sports vid...
In this chapter we discuss the problem of detecting and recognizing the two main categories of adver...
This paper presents a system for the detection and localization of multiple instances of trademark l...
With the emergence of new content diffusion platforms, there is a growing need to detect advertising...
Object of the work – A medium which best reveals different professional athlete trademark features. ...
Abstract - We present an athlete recognition module designed for broadcast videos, forming part of a...
International audienceAutomatic semantic annotation of videos remains an openresearch problem. In th...
We present results on an extension to our approach for automatic sports video annotation. Sports vid...
Abstract. We present results on an extension to our approach for automatic sports video annotation. ...
Abstract With the rapid development of information technology and network technology and the rapid p...
Content-based indexing is fundamental to support and sustain the ongoing growth of broadcasted sport...
Content-based indexing is fundamental to support and sustain the ongoing growth of broadcasted sport...
We present an athlete identification module forming part of a system for the personalization of spor...
In this paper we discuss the problem of how to discriminate moments of interest on videos or live br...
In this paper we describe a system for automatic detection and recognition of trademarks in sports v...
In this paper we describe a system for detection and retrieval of trademarks appearing in sports vid...
In this chapter we discuss the problem of detecting and recognizing the two main categories of adver...
This paper presents a system for the detection and localization of multiple instances of trademark l...
With the emergence of new content diffusion platforms, there is a growing need to detect advertising...
Object of the work – A medium which best reveals different professional athlete trademark features. ...
Abstract - We present an athlete recognition module designed for broadcast videos, forming part of a...
International audienceAutomatic semantic annotation of videos remains an openresearch problem. In th...
We present results on an extension to our approach for automatic sports video annotation. Sports vid...
Abstract. We present results on an extension to our approach for automatic sports video annotation. ...
Abstract With the rapid development of information technology and network technology and the rapid p...
Content-based indexing is fundamental to support and sustain the ongoing growth of broadcasted sport...
Content-based indexing is fundamental to support and sustain the ongoing growth of broadcasted sport...
We present an athlete identification module forming part of a system for the personalization of spor...
In this paper we discuss the problem of how to discriminate moments of interest on videos or live br...