Qualifications: MSc PhD Cant

About John

John Perrone's expertise is in the field of Vision Science.

Research Interests

1) Modelling aspects of human self motion estimation. Ongoing research project which involves development and computer simulation of putative physiological motion processing in areas MT and MST of primate visual cortex.

2) Testing people's ability to estimate their heading direction and to extract depth information from image motion.

Please visit these links for more information about John's research:
Overview
Human Visual Navigation 2-D Motion Sensors Slant Perception Visual Aspects of Water Quality

Recent Publications

• Garnett, A., & Perrone, J. (2018). Curvilinear motion perception during visually simulated head turns in stereoscopic 3D virtual reality. In Journal of Vision Vol. 18. Association for Research in Vision and Ophthalmology. doi:10.1167/18.10.46

• Perrone, J. A. (2018). Visual–vestibular estimation of the body's curvilinear motion through the world: A computational model. Journal of Vision, 18(4), 1-32. doi:10.1167/18.4.1

• Perrone, J. (2018). Non-isotropic heading errors while moving along curved paths: Another reason to look where we are going?. In Journal of Vision Vol. 18. Association for Research in Vision and Ophthalmology. doi:10.1167/18.10.1064

• Perrone, J. A., Cree, M. J., Hedayati, M., & Corlett, D. (2018). Testing a biologically-based system for extracting depth from brief monocular 2-D video sequences. In 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ) (pp. 6 pages). Conference held in Auckland, New Zealand: IEEE. doi:10.1109/IVCNZ.2018.8634781 Open Access version: https://hdl.handle.net/10289/12324

View all research publications by John Perrone