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Research programs in the UCLA Human Perception Laboratory address a broad range of topics in visual perception, cognition, and learning.

News & Events

September 2019

The National Cancer Institute (NCI) of the National Institutes of Health (NIH) has awarded a 4-year grant to the UCLA Human Perception Laboratory for the project Perceptual and Adaptive Learning in Cancer Image Interpretation under the program Perception and Cognition in Cancer Image Interpretation. The goal of this project is to investigate principles and mechanisms of perceptual and adaptive learning in the learning of multiple diagnostic categories in dermatologic screening and mammography, with the ultimate aim of improving training and proficiency in cancer image interpretation.

July 2019

Lab Presentation / Publication Note: Everett Mettler presented a poster entitled The synergy of passive and active learning modes in adaptive perceptual learning at the Annual Meeting of the Cognitive Science Society in Montreal. This work was supported by NSF award NSF ECR1644916, “Advancing Theory and Application in Perceptual and Adaptive Learning to Improve Community College Mathematics”. The published proceedings citation is:

  • Mettler, E., Phillips, A., Massey, C., Burke, T., Garrigan, P., & Kellman, P. J. (2019). The synergy of passive and active learning modes in adaptive perceptual learning. In A.K. Goel, C.M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society (pp. 2351-2357). Montreal, QB: Cognitive Science Society.
    Read the proceedings paper

May 2019

Lab Presentation / Publication Note: Members of the Human Perception Lab presented papers and posters at the 2019 Annual Meeting of the Vision Sciences Society.

Everett Mettler presented a paper entitled Perceptual learning benefits from strategic scheduling of passive presentations and active, adaptive learning. This work was supported by NSF award NSF ECR1644916, “Advancing Theory and Application in Perceptual and Adaptive Learning to Improve Community College Mathematics”. The published abstract citation is:

  • Mettler, E. W., Phillips, A. S., Burke, T., Garrigan, P., Massey, C. M., & Kellman, P. J. (2019). Perceptual learning benefits from strategic scheduling of passive presentations and active, adaptive learning. Journal of Vision, 19(10), 293.
    Read the published abstract

Gennady Erlikhman and Nicholas Baker presented a poster entitled Recursive networks reveal illusory contour classification images. The published abstract citation is:

  • Kellman, P. J., Erlikhman, G., Baker, N., & Lu, H. (2019). Recursive networks reveal illusory contour classification images. Journal of Vision, 19(10), 241a.
    Read the published abstract

Nicholas Baker presented a paper entitled Constant curvature representations of contour shape. The published abstract citation is:

  • Baker, N., & Kellman, P. J. (2019). Constant curvature representations of contour shape. Journal of Vision, 19(10), 94.
    Read the published abstract

Susan Carrigan presented a poster entitled From early contour linking to perception of continuous objects: Specifying scene constraints in a two-stage model of amodal and modal completion. The published abstract citation is:

  • Carrigan, S. B., & Kellman, P. J. (2019). From early contour linking to perception of continuous objects: Specifying scene constraints in a two-stage model of amodal and modal completion. Journal of Vision (in press).

April 2019

Phil Kellman was interviewed for an episode of the Australian Broadcasting Company’s podcast The Science Show. In the episode, entitled “Challenges for AI visual recognition,” Phil Kellman and host Robyn Williams discuss our recent research on deep learning networks and shape perception, and the possible implications on pressing topics such as self-driving cars.

Read the transcript
UCLA Human Perception Lab Logo
Philip Kellman The Science Show ABC

Challenges for AI visual recognition

What happens when the driverless car approaches a stop sign sprayed with graffiti? Does the car stop?

Philip J. Kellman, Ph.D.

Philip Kellman

Distinguished Professor
Adjunct Professor of Surgery
Ph.D., University of Pennsylvania
Area Chair: Cognitive Psychology
Primary Area: Cognitive Psychology

Robyn Williams, Science Journalist and Broadcaster

Robyn Williams

Science Journalist and Broadcaster

New UCLA Logo

UCLA

University of California — Los Angeles

December 2018

Lab Publication Note: Members of the Human Perception Lab and the Computational Vision and Learning Lab published an article in PLOS Computational Biology:

Glass Polar Bear
PLOS Computational Biology/Rubylane.com
  • Baker, N., Lu, H., Erlikhman, G., & Kellman, P.J. (2018) Deep convolutional networks do not classify based on global object shape. PLOS Computational Biology, 14(12), e1006613.
    Read the full article

This work was covered by several national and international news outlets. Here is a sampling of that coverage:

August 2018

Lab Publication Note: Phil Kellman and Dr. Sally Krasne published an invited article in the journal Medical Teacher:

  • Kellman, P. J., & Krasne, S. (2018). Accelerating expertise: Perceptual and adaptive learning technology in medical learning. Medical Teacher, 40(8), 797-802.
    Read the full article

July 2018

Lab Presentation / Publication Note: Members of the Human Perception Lab presented papers and posters at the Annual Meeting of the Cognitive Science Society in Madison, WI.

Everett Mettler presented a paper entitled Enhancing adaptive learning through strategic scheduling of passive and active learning modes. This work was supported by NSF award NSF ECR1644916, “Advancing Theory and Application in Perceptual and Adaptive Learning to Improve Community College Mathematics”. The published proceedings citation is:

  • Mettler, E., Massey, C. M., Burke, T., Garrigan, P., & Kellman, P. J. (2018). Enhancing adaptive learning through strategic scheduling of passive and active learning modes. In T.T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 768-773). Austin, TX: Cognitive Science Society.
    Read the proceedings paper

Nicholas Baker presented a poster entitled Deep convolutional networks do not perceive illusory contours. The published proceedings citation is:

  • Baker, N., Kellman, P. J., Erlikhman, G., & Lu, H. (2018). Deep convolutional networks do not perceive illusory contours. In T.T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 1310-1315). Austin, TX: Cognitive Science Society.
    Read the proceedings paper

May 2018

Lab Presentation / Publication Note: Phil Kellman presented a poster at the 2018 Annual Meeting of the Vision Sciences Society, entitled The psychophysics of algebra: Mathematics perceptual learning interventions produce lasting changes in the perceptual encoding of mathematical objects. The published abstract citation is:

  • Kellman, P. J., Bufford, C. A., & Mettler, E. (2017). The psychophysics of algebra: Mathematics perceptual learning interventions produce measurable and lasting changes in the perceptual encoding of mathematical objects. Abstracts of the Psychonomic Society, 22, 27.
    Read the published abstract

April 2018

Lab Publication Note: Members of the Human Perception Lab published an article in the Journal of Experimental Psychology:

  • Baker, N. & Kellman, P.J. (2018). Abstract shape representation in human visual perception. Journal of Experimental Psychology: General, 147(9), 1295-1308.
    Read the full article
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Support

Our visual perception research has been supported by the National Eye Institute (NEI), the National Science Foundation (NSF), and the National Institute of Justice (NIJ).

Our research in perceptual learning, adaptive learning, and their applications to learning technology has been supported in recent years by the National Science Foundation (NSF), the Institute of Education Sciences (IES) at the US Department of Education, the National Institutes of Health (NIH), the US Office of Naval Research (ONR) and the National Aeronautical and Space Administration (NASA).