Seeing, sensing, and selection: modeling visual perception in complex environments

Show full item record

Redirect: RIT Scholars content from RIT Digital Media Library has moved from to RIT Scholar Works, please update your feeds & links!
Title: Seeing, sensing, and selection: modeling visual perception in complex environments
Author: Canosa, Roxanne
Abstract: The purpose of this thesis is to investigate human visual perception at the level of eye movements by describing the interaction between vision and action during natural, everyday tasks in a real-world environment. The results of the investigation provide motivation for the development of a biologically-based model of selective visual perception that relies on the relative perceptual conspicuity of certain regions within the field of view. Several experiments were designed and conducted that form the basis for the model. The experiments provide evidence that the visual system is not passive, nor is it general-purpose, but rather it is active and specific, tightly coupled to the requirements of planned behavior and action. The implication for an active and task-specific visual system is that an explicit representation of the environment can be eschewed in favor of a compact representation with large potential savings in computational efficiency. The compact representation is in the form of a topographic map of relative perceptual conspicuity values. Other recent attempts at compact scene representations have focused mainly on low-level maps that code certain salient features of the scene including color, edges, and luminance. This study has found that the low-level maps do not correlate well with subjects' fixation locations, therefore, a map of perceptual conspicuity is presented that incorporates high-level information. The high-level information is in the form of figure/ground segmentation, potential object detection, and task-specific location bias. The resulting model correlates well with the fixation densities of human viewers of natural scenes, and can be used as a pre-processing module for image understanding or intelligent surveillance applications.
Record URI:
Date: 2003-09-29

Files in this item

Files Size Format View
RCanosaThesis09-19-2003.pdf 40.49Mb PDF View/Open

The following license files are associated with this item:

This item appears in the following Collection(s)

Show full item record

Search RIT DML

Advanced Search