<XML><RECORDS><RECORD><REFERENCE_TYPE>3</REFERENCE_TYPE><REFNUM>7876</REFNUM><AUTHORS><AUTHOR>Balasuriya,L.S.</AUTHOR><AUTHOR>Siebert,J.P.</AUTHOR></AUTHORS><YEAR>2005</YEAR><TITLE>A Biologically Inspired Computational Vision Front-end based on a Self-Organised Pseudo-Randomly Tessellated Artificial Retina</TITLE><PLACE_PUBLISHED>International Joint Conference on Neural Networks 2005, Montreal</PLACE_PUBLISHED><PUBLISHER>IEEE</PUBLISHER><LABEL>Balasuriya:2005:7876</LABEL><ABSTRACT>This paper considers the construction of a biologically inspired front-end for computer vision based on an artificial retina ‘pyramid’ with a self-organised pseudo-randomly tessellated receptive field tessellation. The organisation of photoreceptors and receptive fields in biological retinae locally resembles a hexagonal mosaic, whereas globally these are organised with a very densely tessellated central foveal region which seamlessly merges into an increasingly sparsely tessellated periphery. In contrast, conventional computer vision approaches use a rectilinear sampling tessellation which samples the whole field of view with uniform density. Scale-space interest points which are suitable for higher level attention and reasoning tasks are efficiently extracted by our vision front-end by performing hierarchical feature extraction on the pseudo-randomly spaced visual information. All operations were conducted on a geometrically irregular foveated representation (data structure for visual information) which is radically different to the uniform rectilinear arrays used in conventional computer vision.</ABSTRACT></RECORD></RECORDS></XML>