NSERC’s Awards Database
Award Details

Human sensitivity and use of natural image statistics

Research Details
Competition Year: 2011 Fiscal Year: 2012-2013
Project Lead Name: Johnson, Aaron Institution: Concordia University
Department: Psychology Province: Québec
Award Amount: $24,000 Installment: 2 - 5
Program: Discovery Grants Program - Individual Selection Committee: Biological Systems and Functions
Research Subject: Sensory systems -- visual Area of Application: Psychology
Co-Researchers: No Co-Researcher Partners: No Partners
Award Summary

Humans live in a visually complex and dynamic environment, yet we are capable of perceiving and processing information from our surroundings, make perceptual judgments, and create a behavioural response in a few short milliseconds. The aim of my research is to better understand how the brain can accomplish this. The environment and daily tasks that humans must perform have shaped the design and functioning of our visual system. Therefore, by studying the visual sources of information within our world, we can investigate the function and design of human vision. My research focuses on scene perception, our ability to rapidly recognize a scene. Specifically, how the visual information within a scene, such as texture and colour, is used in the recognition of natural scenes (photographs of the real world, as opposed to synthetic images). By manipulating the visual properties of scenes (e.g. brightness, colour, texture), I aim to investigate the sensitivity of humans to such manipulations, and discover which features are humans most sensitive to, and which we are least sensitive to. This research will verify if findings from studies using synthetic computer-generated images, which are traditionally used to study vision, can be applied to more complex images such as scenes. I will also investigate if these manipulations within the scene properties can affect daily visual tasks such as search and scene recognition that humans must perform with the visual features. This will allow us to investigate which visual features of an image are important in scene recognition, and when they used. The knowledge obtained by this research will expand our understanding of the human visual system, and help advance our understanding of the human mind, from how we extract the visual information within a scene to how we perform everyday vision tasks. The findings will also be useful for many practical applications, such as detecting image manipulations (forgery) in digital photographs, improving human interface design, improving instrument panel design for cars and aircraft, and helping to locate camouflaged objects in photographs.