Carnegie Mellon University

Michael Tarr

Michael Tarr

Department Head, Psychology

Bio

My research focuses on the how the primate brain turns 2D retinal images into the perception of objects and scenes. I am interested in:

  • Face, Object, and Scene Perception
  • Perceptual Expertise and Learning
  • Visual Categorization and Semantics
  • Computational and Artificial Vision Systems
  • Novel Imaging Methods, Including Real-time, Adaptive fMRI

Publications

PubMed List of Publications

Tarr, M. J., & Aminoff, E. M. (2016). Can Big Data Help Us Understand Human Vision? In M. Jones (Ed.), Big Data in Cognitive Science. Taylor & Francis: Psychology Press. 

Aminoff, E. M., Toneva, M., Shrivastava, A., Chen, X., Misra, I., Gupta, A., & Tarr, M. J. (2015). Applying artificial vision models to human scene understanding. Front. Comput. Neurosci., 9. doi:10.3389/fncom.2015.00008

Leeds, D. D., Pyles, J. A., & Tarr, M. J. (2014). Exploration of complex visual feature spaces for object perception. Front. Comput. Neurosci., 8(106). doi: 10.3389/fncom.2014.00106

Yang, Y., Tarr, M. J., & Kass, R. E. (2014). Estimating learning effects: A short-time Fourier transform regression model for MEG source localization. In Springer Lecture Notes on Artificial Intelligence: MLINI 2014: Machine learning and interpretation in neuroimaging.

Leeds, D. D., Seibert, D. A., Pyles, J. A., & Tarr, M. J. (2013). Comparing visual representations across human fMRI and computational vision. J. of Vision. 13(13). doi: 10.1167/13.13.25

Pyles, J. A., Verstynen, T. D., Schneider, W., & Tarr, M. J. (2013). Explicating the face perception network with white-matter connectivity. PLoS ONE, 8(4): e61611. doi:10.1371/journal.pone.0061611 

Nestor, A., Vettel, J. M., & Tarr, M. J. (2012). Internal representations for face detection: An application of noise-based image classification to BOLD responses. Human Brain Mapping, n/a. doi:10.1002/hbm.22128

Lebrecht, S., Bar, M., Barrett, L. F., & Tarr, M. J. (2012). Micro-Valences: Affective valence in "neutral" everyday objects. Frontiers in Perception Science, 3(107). doi:10.3389/fpsyg.2012.00107