<XML><RECORDS><RECORD><REFERENCE_TYPE>0</REFERENCE_TYPE><REFNUM>8139</REFNUM><AUTHORS><AUTHOR>Balasuriya,L.S.</AUTHOR><AUTHOR>Siebert,J.P.</AUTHOR></AUTHORS><YEAR>2006</YEAR><TITLE>Hierarchical Feature Extraction using a Self-organised Retinal Receptive Field Sampling Tessellation</TITLE><PLACE_PUBLISHED>Neural Information Processing - Letters & Reviews</PLACE_PUBLISHED><PUBLISHER>N/A</PUBLISHER><LABEL>Balasuriya:2006:8139</LABEL><KEYWORDS><KEYWORD>Space-variant vision</KEYWORD></KEYWORDS<ABSTRACT>This paper examines the problem of hierarchical processing of visual information extracted with a layer of pseudo-randomly tessellated retinal receptive fields. Afferents from the retinal neural layer were processed by a cortical neuron layer resulting in a hierarchy of feature extraction operations similar to that found in biological vision systems. The retinal tessellation was obtained by self-organisation such that retinal neuron receptive field locations were allocated across the system’s field-of-view in a space-variant manner. The retinal tessellation seamlessly merged from a central dense uniform fovea region to a sparser space-variant surrounding periphery. The neural system therefore extracted high acuity visual information from the central foveal region and progressively coarser information from a space-variant increasingly coarse periphery. The paper addresses the issues of i) generating a retinal tessellation with a uniform fovea that seamlessly merges into a space-variant periphery, ii) sampling visual information contained in a digital image with pseudo-randomly positioned retinal neuron receptive fields, iii) performing hierarchical feature extraction on pseudo-randomly spaced visual information, iv) multi-resolution feature extraction using self-organised retinae, v) the targeting of the space-variant machinery by generating saccades based on bottom-up attention.</ABSTRACT></RECORD></RECORDS></XML>