Research Project

A Measurement Method of the Human Vision System

This project develops experimental methods, software, and test equipment for measuring central and peripheral characteristics of the human visual system for video quality assessment and perceptual video processing.

Human Visual System Psychophysics Video Quality Central Vision Peripheral Vision Measurement System

Abstract

Based on research into the limits of human vision, this project offers a method, software, and test equipment for studying and measuring characteristics of the human visual system. The experimental system forms and evaluates stimuli with controlled combinations of spatial, temporal, and colour characteristics, enabling precise measurement of human visual thresholds.


The work supports the development of new video quality metrics and adaptive video transmission methods by providing modern data on how the early human visual system processes spatial and temporal information. This is especially important because much of the existing foundational data was collected decades ago and does not reflect current display technologies or contemporary media viewing conditions.

Research Contributions

Central Vision

  • New experimental method for measuring spatial and temporal characteristics of central human vision.
  • Controlled visual stimuli with different spatial sizes and temporal modulation rates.
  • Modern display conditions for measuring visual thresholds under current media presentation environments.
  • Foundation for video quality metrics that better reflect perceived distortion and subjective quality.

Peripheral Vision

  • Measurement of temporal-frequency visibility thresholds in peripheral areas of the visual field.
  • Support for wide field-of-view displays, immersive media, and VR-based visual systems.
  • Improved understanding of peripheral perception for wide-angle video and perceptual compression.
  • Relevance to video systems where peripheral information and wide-angle perception are critical.

Experimental System

Experimental setup for measuring characteristics of the human visual system
Experimental setup for measuring human visual system characteristics using controlled visual stimuli.

Method Overview

  • Stimulus generation with controlled spatial, temporal, and colour parameters.
  • Threshold measurement for visibility of visual variations relevant to video quality.
  • Software-supported testing for repeatable psychovisual experiments.
  • Application-oriented design for video compression, quality assessment, and visual AI research.

Publications and Materials

Central Vision Measurement Method

Mozhaeva A, Vlasuyk I, Potashnikov A, Cree M, Streeter L (2021). The method and devices for research the parameters of the human visual system to video quality assessment.

View IEEE Paper

Peripheral Temporal Characteristics

Vlasuyk I, Potashnikov A, Mazin V, Mozhaeva A, Egorov D (2024). A Measurement Method and a Mathematical Model of the Human Vision System's Temporal Peripheral Characteristics.

View IEEE Paper

Adaptive Human Vision Model

Mazin V, Cree MJ, Streeter L, Nezhivleva K, Mozhaeva A (2023). Research and application of the adaptive model of the human visual system for improving the effectiveness of objective video quality metrics.

View IEEE Paper

User Interest Regions

Egorova A, Baryshev R, Mozhaeva A (2023). Methodology of researching perception identity of regions of users' interests while viewing streaming video containing various content and compression artefacts.

View IEEE Paper

Research Applications

Video and Media Technologies

  • Perceptual video quality assessment using measured characteristics of human vision.
  • Adaptive video transmission that reduces data while preserving perceived quality.
  • Video compression research informed by human spatial and temporal sensitivity.
  • Modern display evaluation under realistic viewing conditions.

Future Visual AI Systems

  • Human-inspired visual AI for more efficient processing of perceptually relevant information.
  • Wide-angle and immersive video systems using knowledge of peripheral vision.
  • Embedded vision systems operating under bandwidth and computational constraints.
  • Aerospace and robotics applications requiring real-time visual perception models.

Contact

Primary contact: amozhaeva@eit.ac.nz.