This paper presents an ontogenetic model of self-organization for robotic intermediary vision. Two mechanisms are under concern. First, the development of low-level local feature detectors that perform a piecewise categorization of the sensory signal. Second, the hierarchical grouping of these local features in a holistic perception. While the grouping mechanism is expressed as a classical agglomerative clustering, underlying similarity measures are not pre-given but developed from the signal statistics
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