DMCA
Motion Integration and Segmentation Lee Stone, NASA ARC IHH
BibTeX
@MISC{Mulligan_motionintegration,
author = {Jeff Mulligan and Arc Ihh and Guillaume Masson and Centre Recherche and Neurosciences Cognitives and Daniel Mestre and Centre Recherche and Neurosciences Cognitives},
title = {Motion Integration and Segmentation Lee Stone, NASA ARC IHH},
year = {}
}
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Abstract
Over the last two decades much has been learned about human ability to detect and discriminate information within local patches of image motion. Indeed, a model consisting of spatio-temporal motion energy detectors is an excellent descriptor of both human low-level motion perception and visual processing within the primary visual cortex of the primate brain. This simple quasilinear view however does not adequately describe human performance in motion tasks which require either global integration across the image or segmentation of multiple overlapping motions presented simultaneously, yet these two abilities are essential components of many real-world aerospace tasks. The overall goal of this project is to measure human performance in motion integration and segmentation tasks and to develop and test computational models of human performance. The specific aim is to examine the mechanisms (abilities and limitations) of the human brain 1) to perform the global spatio-temporal integration used to estimate object direction, and 2) to use speed cues to segment images into discrete objects. Most current models of human motion processing use a first stage of local motion-energy sensors and various spatio-temporal integration rules to derive a global object-velocity signal. Drs. Beutter, Mulligan, & Stone have shown that none of the current dominant models could account
Keyphrases
motion integration segmentation lee stone nasa arc ihh human performance local patch speed cue overall goal primate brain computational model object direction human ability segmentation task global object-velocity signal human motion processing use human brain primary visual cortex global spatio-temporal integration essential component describe human performance spatio-temporal motion energy detector visual processing motion task image motion excellent descriptor human low-level motion perception global integration various spatio-temporal integration rule many real-world aerospace task current dominant model current model specific aim local motion-energy sensor segment image simple quasilinear view first stage discrete object
