MapSnapper: Engineering an Efficient Algorithm for Matching Images of Maps from Mobile Phones

The MapSnapper project aimed to develop a system for robust matching of low-quality images of a paper map taken from a mobile phone against a high quality digital raster representation of the same map. The paper presents a novel methodology for performing content-based image retrieval and object recognition from query images that have been degraded by noise and subjected to transformations through the imaging system. In addition the paper also provides an insight into the evaluation-driven development process that was used to incrementally improve the matching performance until the design specifications were met

To Be Human

I write in an attempt to convey the way I perceive the world and my place in it. I am not separate from the natural world but, as a human, deeply part of it. I want my readers to feel how, as much as any other species, our history and existence are part of the Earth. Sometimes in the built environment, especially large cities, I lose my connection to my roots and to my own person. In writing, I reclaim that connection and hope to restore it for my audience. Every human behavior is either conditioned or evolutionary. Either we were taught to do something, or it was a genetic advantage at some point in our history. My work explores why we act the way we do, and how that makes us who we are. I can never hope to find the answer without first exploring who my ancestors were and where I came from

A neuroanatomical examination of embodied cognition: semantic generation to action-related stimuli

The theory of embodied cognition postulates that the brain represents semantic knowledge as a function of the interaction between the body and the environment. The goal of our research was to provide a neuroanatomical examination of embodied cognition using action-related pictures and words. We used functional magnetic resonance imaging (fMRI) to examine whether there were shared and/or unique regions of activation between an ecologically valid semantic generation task and a motor task in the parietal-frontocentral network (PFN), as a function of stimulus format (pictures versus words) for two stimulus types (hand and foot). Unlike other methods for neuroimaging analyses involving subtractive logic or conjoint analyses, this method first isolates shared and unique regions of activation within-participants before generating an averaged map. The results demonstrated shared activation between the semantic generation and motor tasks, which was organized somatotopically in the PFN, as well as unique activation for the semantic generation tasks in proximity to the hand or foot motor cortex. We also found unique and shared regions of activation in the PFN as a function of stimulus format (pictures versus words). These results further elucidate embodied cognition in that they show that brain regions activated during actual motor movements were also activated when an individual verbally generates action-related semantic information. Disembodied cognition theories and limitations are also discussed

The pneumococcal alpha-glycerophosphate oxidase enhances nasopharyngeal colonization through binding to host glycoconjugates

Streptococcus pneumoniae (the pneumococcus) is a major human pathogen, causing a broad spectrum of diseases including otitis media, pneumonia, bacteraemia and meningitis. Here we examined the role of a potential pneumococcal meningitis vaccine antigen, alpha-glycerophosphate oxidase (SpGlpO), in nasopharyngeal colonization. We found that serotype 4 and serotype 6A strains deficient in SpGlpO have significantly reduced capacity to colonize the nasopharynx of mice, and were significantly defective in adherence to human nasopharyngeal carcinoma cells in vitro. We also demonstrate that intranasal immunization with recombinant SpGlpO significantly protects mice against subsequent nasal colonization by wild type serotype 4 and serotype 6A strains. Furthermore, we show that SpGlpO binds strongly to lacto/neolacto/ganglio host glycan structures containing the GlcNAcβ1-3Galβ disaccharide, suggesting that SpGlpO enhances colonization of the nasopharynx through its binding to host glycoconjugates. We propose that SpGlpO is a promising vaccine candidate against pneumococcal carriage, and warrants inclusion in a multi-component protein vaccine formulation that can provide robust, serotype-independent protection against all forms of pneumococcal disease

A multi-agent framework for developing complex software

Human Biometrics, with gait as an example, has been around as a science for several years. Applications of the gait biometric can be found in the fields of medical diagnosis, physical therapy and sports. However, it is only in recent times that its use for human iden tification has become practical for real life and real time applications due to the increase in commercially available computing power. The availability of a suitably powerful computing platform is only one aspect of building such system, there still remains the question of how to realise its software architecture. 'With out a viable solution to this problem the application and use of gait identification in a real life scenario will remain in its infancy. Such a system is complex in two respects. One is the complexity in the computations of its individual components and the other is the complexity in building the layout of these components and communications between them. Additionally there is the difficult task of efficiently maintaining such a system. If the frame work that holds the components is not flexible enough, adding new components will be an extremely expensive and difficult task. Therefore, this work focuses upon the creation of a general-purpose, multi-agent framework. As such, the primary goal of this architecture is to reduce system complexity allowing ease of maintenance and expansion, while also allowing distribution of data processing. This framework is entirely general in its application and can be used for holding any soft ware system capable of distributed execution. By using gait identification in this work as an example application, the framework demonstrates its capabilities and thus the advantages of using it.</p

Automatic recognition by gait: progress and prospects

Recognising people by their gait is a biometric of increasing interest. Recently, analysis has progressed from evaluation by few techniques on small databases with encouraging results to large databases and still with encouraging results. The potential of gait as a biometric was encouraged by the considerable amount of evidence available, especially in biomechanics and literature. This potential motivated the development of new databases, new technique and more rigorous evaluation procedures. We adumbrate some of the new techniques we have developed and their evaluation to gain insight into the potential for gait as a biometric. In particular, we consider implications for the future. Our work, as with others, continues to provide encouraging results for gait as a biometric, let alone as a human identifier, with a special regard for recognition at a distance

What image information is important in silhouette-based gait recognition

Gait recognition has recently gained significant attention, especially in vision-based automated human identification at a distance in visual surveillance and monitoring applications. Silhouette-based gait recognition is the one of the most popular methods for recognising moving shapes. This paper aims to investigate the important features in silhouette-based gait recognition from point of view of statistical analysis. It is shown that the average silhouette includes a static component of gait (head and body) as the most important image part, while dynamic component of gait (swings of legs and arms) is ignored as the least important information. At the same time ignoring dynamic part of gait can result in loss in recognition rate in some cases, and the importance of better motion estimation is underlined