The 'Unhomely' White Women of Antillean Writing

While the field known as ‘Whiteness Studies’ has been thriving in Anglophone criticism and theory for over 25 years, it is almost unknown in France. This is partly due to epistemological and political differences, but also to demographic factors — in contrast with the post-plantation culture of the US, for example, whites in Martinique and Guadeloupe are a tiny minority of small island populations. Yet ‘whiteness’ remains a phantasized and a fetishized state in the Antillean imaginary, and is strongly inflected by gender. This article sketches the emergence of ‘white’ femininity during slavery, then examines its representation in the work of a number of major Antillean writers (Condé, Placoly, Confiant, Chamoiseau). In their work, a cluster of recurring images and leitmotifs convey the idealization or, more commonly, the pathologization, of the white woman; these images resonate strongly with Bhabha’s ‘unhomely’, and convey the disturbing imbrication of sex and race in Antillean history.

ArchiBabel: Tracing the Writing Architecture Project in Architectural Education

Though much recent scholarship has investigated the potential of writing in creative practice (including visual arts, drama, even choreography), there are few models in the literature which discuss writing in the context of architectural education. The paper presented here aims to address this dearth of pedagogical research, analysing the cross-disciplinary Writing Architecture Project based in the undergraduate course of the School of Architecture at QUB. Over the course of four years, teaching staff, in partnership with the university's Learning Development Service, technicians and specialist librarians, have addressed an unfortunately persistent struggle for both architecture students and professionals alike to research and construct argument in written form. The paper examines the current problem as identified in the literature before analysing the efficacy of the variety of teaching methods used in the Writing Architecture Project, with conclusions about the project’s success and continuing challenges.

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.