Steve A. Adeshina

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We describe a method for modelling and locating deformable objects using a combination of global and local shape models. An object is represented as a set of patches together with a geometric model of their relative positions. The geometry is modelled with a global pose and linear shape model, together with a Markov Random Field (MRF) model of local(More)
We seek to automatically establish dense correspondences across groups of images. Existing non-rigid registration methods usually involve local optimisation and thus require accurate initialisation. It is difficult to obtain such initialisation for images of complex structures, especially those with many self-similar parts. In this paper we show that(More)
The adoption of e-voting in different parts of the world has been generally problematic, with only few exceptions. Past studies also suggest that e-voting is embedded in the socio-politically context informing variations in the adoption patterns and nature of challenges faced during implementation. While few survey-based empirical studies have been carried(More)
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