Learn More
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)
This paper addresses the problem of scene categorization while arguing that better and more accurate results can be obtained by endowing the computational process with perceptual relations between scene categories. We first describe a psychophysical paradigm that probes human scene categorization, extracts perceptual relations between scene categories, and(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)
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)
Novel, targets-to-sensors' geometry-based performance measure, bootstrap estimation algorithm and feature-aided association are described for the passive multisensor multitarget data association, position and velocity measurement estimation and coupled unconstrained association/tracking problem. The approach reduces computational complexity and ghost(More)
  • 1