Ilan Kadar

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What is the order of processing in scene gist recognition? Following the seminal studies by Rosch (1978) and Tversky and Hemmenway (1983) it has been assumed that basic-level categorization is privileged over the superordinate level because the former maximizes both within-category similarity and between-category variance. However, recent research has begun(More)
Boundary detection constitutes a crucial step in many computer vision tasks. We present a learning approach for automatically constructing high-performance local boundary detectors for natural images via genetic programming (GP). Our GP system is unique in that it combines filter kernels that were inspired by models of processing in the early stages of the(More)
Boundary detection constitutes a crucial step in many computer vision tasks. We present a novel learning approach to automatically construct a boundary detector for natural images via Genetic Programming (GP). Our approach aims to use GP as a learning framework for evolving computer programs that are evaluated against human-marked boundary maps, in order to(More)
The ability to recognize visual scenes quickly and accurately is highly constructive for both biological and machine vision. In this work we study the process of scene gist recognition from a novel point of view and investigate whether prior knowledge of the perceptual relations between the different scene categories may help facilitate better computational(More)
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