Death and football: An analysis of men's talk about emotions

This study is concerned with men's talk about emotions and with how emotion discourses function in the construction and negotiation of masculine ways of doing emotions and of consonant masculine subject positions. A sample group of 16 men, who were recruited from two social contexts in England, participated in focus groups on 'men and emotions'. Group discussions were transcribed and analysed using discourse analysis. Participants drew upon a range of discursive resources in constructing masculine emotional behaviour and negotiating masculine subject positions. They constructed men as emotional beings, but only within specific, rule-governed contexts, and cited death, a football match and a nightclub scenario as prototypical contexts for the permissible/understandable expression of grief, joy and anger, respectively. However, in the nightclub scenario, the men distanced themselves from the expression of anger as violence, whilst maintaining a masculine subject position. These discursive practices are discussed in terms of the possibilities for effecting change in men's emotional lives.

Automatic detection and classification of football players

Color segmentation of images usually requires a manual selection and classification of samples to train the system. This paper presents an automatic system that performs these tasks without the need of a long training, providing a useful tool to detect and identify figures. In real situations, it is necessary to repeat the training process if light conditions change, or if, in the same scenario, the colors of the figures and the background may have changed, being useful a fast training method. A direct application of this method is the detection and identification of football players.

Real-time GPU color-based segmentation of football players

In this paper, we propose a multi-camera application capable of processing high resolution images and extracting features based on colors patterns over graphic processing units (GPU). The goal is to work in real time under the uncontrolled environment of a sport event like a football match. Since football players are composed for diverse and complex color patterns, a Gaussian Mixture Models (GMM) is applied as segmentation paradigm, in order to analyze sport live images and video. Optimization techniques have also been applied over the C++ implementation using profiling tools focused on high performance. Time consuming tasks were implemented over NVIDIA's CUDA platform, and later restructured and enhanced, speeding up the whole process significantly. Our resulting code is around 4-11 times faster on a low cost GPU than a highly optimized C++ version on a central processing unit (CPU) over the same data. Real time has been obtained processing until 64 frames per second. An important conclusion derived from our study is the scalability of the application to the number of cores on the GPU. © 2011 Springer-Verlag.

‘Who Ate All the Pride?’:Patriotic Sentiment and English National Football Support.

The growing popularity of English national insignia in international football tournaments has been widely interpreted as evidence of the emergence of a renewed English national consciousness. However, little empirical research has considered how people in England actually understand football support in relation to national identity. Interview data collected around the time of the Euro 2000 and the 2002 World Cup tournaments fail to substantiate the presumption that support for the England football team maps onto claims to patriotic sentiment in any straightforward way. People with far-right political affiliations did generally use national football support to symbolise a general pride in English national identity. However, other people either claimed not to support the England national team precisely because of its associations with nationalism, or else bracketed the domain of football support from more general connotations of English patriotism.