kellman's picture
Phil Kellman
Distinguished Professor
Adjunct Professor of Surgery
Ph.D.,
University of Pennsylvania
Area Chair:
Cognitive Psychology
Primary Area:
Cognitive Psychology
Address:
3558 FH
Phone:
(310) 825-4202, (310) 454-8115
Research and Teaching Interests:

•      Visual perception of objects, space, and motion

•      Perceptual learning and development

•      Perceptual learning, visual cognition, and adaptive learning in education, skill acquisition and educational technology

•      Human factors applications of perception and cognition research

Research in our laboratory centers on perceptual organization in vision and relations of seeing to cognition and learning. We have been described as "computational Gestalt psychologists," because we seek clear principles and models to solve classic problems described by Gestalt psychologists in the last century, centering on the importance of structure and form in perception and thinking. Our work involves psychophysical experimentation and computational modeling aimed at understanding how perceivers extract information from their environment and derive representations of objects, the layout of the environment, and events occurring within it. Some focal areas include: contour, object and surface perception from information that is fragmentary across space and time, perception of shape, and interactions among object, space and motion perception.

We also focus on perceptual learning -- how the pickup of information changes with experience. Much of our work involves the role of perceptual learning in complex, high-level tasks. We are concerned with the relations between "low level" perceptual learning and more natural, real-world tasks, understanding the conditions that facilitate learning, and modeling high-level perceptual learning.  Spanning most of our work in vision is an effort to understand the processing of abstract relations in perception and perceptual learning.

The realization that perceptual learning is heavily involved even in complex, symbolic, cognitive domains has led us to connect our work to many aspects of cognition, learning, and expertise. We believe that our research, and that of others, is leading to revised and broadened notions of what learning is. As Eleanor Gibson suggested decades ago, a profoundly important component of learning in any domain involves domain-specific changes in the pickup of information. Our work involves understanding how the discovery of new relational structure and improvements in fluency drive expertise, and we extend this work into symbolic domains, such as mathematics learning. These efforts lead to the development and testing of computer-based learning technology to accelerate expert information extraction and pattern recognition skills. Integral to some of these efforts has been the development and study of novel adaptive learning algorthms, implemented in learning technology, that improve the efficiency and durability of learning in any domain (factual, procedural, perceptual learning, or combinations). Studies related to these efforts are helping to advance the understanding of basic issues in learning and memory, such as spacing effects, and have already produced dramatic advances in learning, retention, and transfer in diverse domains, such as STEM learning, medical learning, and aviation training. 

 

Please visit our lab
kellmanlab.psych.ucla.edu

Representative Publications:

Note:  Representative publications are grouped below by topics:  Visual Perception of Objects, Contours, and Surfaces; Perceptual Learning and Development; Adaptive Learning; and Applications of Perceptual and Adaptive Learning to Learning Technology.

 

Visual Perception of Objects, Contours, and Surfaces

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. Austin, TX: Cognitive Science Society

Baker, N. & Kellman, P.J. (2018). Abstract shape representation in human visual perception. Journal of Experimental Psychology: Generaldoi: 10.1037/xge0000409. [Epub ahead of print]

Palmer, E.M. & Kellman, P.J. (2017). The aperture capture illusion. In D. Todorovic and A.G. Shapiro, Eds., Oxford Compendium of Visual Illusions, NY: Oxford University Press.

Carrigan, S.B., Palmer, E.M. & Kellman, P.J. (2016). Differentiating global and local contour completion using a dot localization paradigm, Journal of Experimental Psychology: Human Perception and Performance. 2016 Aug 8. [Epub ahead of print]

Erlikhman, G. & Kellman, P.J. (2016).  From flashes to edges to objects: Recovery of local edge fragments initiates spatiotemporal boundary formation. Frontiers in Psychology, Special issue on Perceptual Grouping—the State of the Art. 28 June 2016| http://dx.doi.org/10.3389/fpsyg.2016.00910

Erlikhman, G. & Kellman, P.J. (2015). Modeling spatiotemporal boundary formation. Vision Research, Special issue on quantitative approaches in Gestalt perception.
 pii: S0042-6989(15)00118-2. doi: 10.1016/j.visres.2015.03.016.

Erlikhman, G., Xing, Y.Z. & Kellman, P.J. (2014). Non-rigid illusory contours and global shape transformations defined by spatiotemporal boundary formation. Frontiers in Human Neuroscience, http://dx.doi.org/10.3389/fnhum.2014.00978

Ghose, T., Liu, J. & Kellman, P.J. (2014) Recovering metric properties of objects through spatiotemporal interpolation. Vision Research. DOI: 10.1016/j.visres.2014.07.015, published online 8 August 2014.

Kellman, P.J., Mnookin, J., Erlikhman, G., Garrigan, P., Ghose, T., Mettler, E., Charlton, D. & Dror, I.E. (2014). Forensic comparison and matching of fingerprints: Using quantitative image measures for estimating error rates through understanding and predicting difficulty. PLoS ONE, 9(5): e94617.

Palmer, E. & Kellman, P.J. (2014).  The aperture capture illusion: Misperceived forms in dynamic occlusion displays. Journal of Experimental Psychology: Human Perception and Performance. 40(2), 502-24.

Erlikhman, G., Xing, Y.Z. & Kellman, P.J. (2014). Non-rigid illusory contours and global shape transformations defined by spatiotemporal boundary formation. Frontiers in Human Neuroscience8:978. doi: 10.3389/fnhum.2014.00978.

Ghose, T., Liu, J., & Kellman, P. J. (2014). Recovering metric properties of objects through spatiotemporal interpolation. Vision Research, 102, 80-88.

Palmer, E.M. & Kellman, P.J. (2014).  The aperture capture illusion: Misperceived forms in dynamic occlusion displays. Journal of Experimental Psychology: Human Perception and Performance. 40(2), 502-24.

Kellman, P.J., Garrigan, P.B. & Erlikhman, G. (2013). Challenges in understanding visual shape perception and representation: Bridging subsymbolic and symbolic coding. In S. J. Dickinson & Z. Pizlo (Eds.), Shape perception in human and computer vision: An interdisciplinary perspective.  London: Springer, pp. 249-274.

Keane, B.P., Kellman, P.J., Lu, H., & Papathomas, T.V., & Silverstein, S.M. (2012). Is interpolation cognitively encapsulated? Measuring the effects of belief on Kanizsa shape discrimination and illusory contour formation. Cognition, 123, 404–418.

Garrigan, P.B. & Kellman, P.J. (2011). The role of constant curvature in 2D contour shape representations. Perception, 40(11): 1290-1308.

Kalar, D., Garrigan, P., Hilger, J., Wickens, T. & Kellman, P.J. (2010). A unified model for contour interpolation. Vision Research, 50(3), 284-299.

Kellman, P.J., Garrigan, P., Palmer, E.M. (2010). 3-D and spatiotemporal interpolation in object and surface formation. In C. W. Tyler (Ed.) Computer vision: From surfaces to objects.  London:  Chapman Hall Press.

Fantoni, C., Hilger, J., Gerbino, W. & Kellman, P. J.  (2008).  Surface interpolation and 3D relatability.  Journal of Vision, Vol. 8, No. 7, Article 29, 1-19.   

Keane, B. P., Lu, H., & Kellman, P. J. (2007). Classification images reveal spatiotemporal interpolation in illusory figures. Vision Research, 47, 3460-3475.

Kellman, P.J., Garrigan, P.B., Shipley, T.F. & Keane, B.P. (2007). Interpolation processes in object perception:  A reply to Anderson.  Psychological Review, 114(2): 488-502.

Palmer, E. M., Kellman, P. J., & Shipley, T. F. (2006). A theory of dynamic occluded and illusory object perception. Journal of Experimental Psychology: General, 135, 513–541.  (Selected for American Psychological Association Young Investigator Award – best paper published in JEP: General in 2006 by a young investigator (Evan Palmer).)

Kellman, P.J., Garrigan, P.,  & Shipley, T. F.  (2005).  Object interpolation in three dimensions. Psychological Review, Vol. 112, No. 3, 586-609.

Kellman, P.J., Guttman, S. & Wickens, T. (2001). Geometric and neural models of contour and surface interpolation in visual object perception.  In Shipley, T.F. & Kellman, P.J. (Eds.)  From fragments to objects:  Segmentation and grouping in vision.  Elsevier Press.

Shipley, T.F. & Kellman, P. J. (Eds.). (2001).  From Fragments to Objects:  Segmentation and Grouping in Vision.  Amsterdam:  Elsevier Science Press. ISBN 0-444-50506-7.

 

Perceptual Learning and Perceptual Development

Cui, L., Massey, C.M. &  Kellman, P.J. (2018). Perceptual learning in correlation estimation: The role of learning category organization. In T.T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Lerner, N., Gill, M., Scott-Parker, B. & Kellman, P.J. (2017).  Accelerating driver expertise through perceptual and adaptive learning. Report to the AAA Foundation for Traffic Safety, Westat Corp. (Available on NAS website at: https://trid.trb.org/view.aspx?id=1461088)

Arterberry, M.E. & Kellman, P.J. (2016). Development of Perception in Infancy: The Cradle of Knowledge Revisited, Oxford University Press.

Romito, B., Krasne, S., Kellman, P. & Dhillon, A. (2016). The impact of a perceptual and adaptive learning module on transoesophageal echocardiography interpretation by anaesthesiology residents. British Journal of Anaesthesia117 (4): 477-481.

Unuma, H., Hasegawa, H. , & Kellman, P.J. (2016). Perceptual learning facilitates precise mental representations of fractions. The Journal of Kawamura Gakuen Women's University. 27(1), 35-49.

Massey, C.M., Kregor, J.D. & Kellman, P.J. (2016). Implementing mathematics learning software successfully in urban schools: Lessons for research and practice. American Educational Research Association (AERA) Online Paper Repository. http://www.aera.net/Publications/Online-Paper-Repository/AERA-Online-Paper-Repository/Owner/444889

Carolyn A. Bufford, C.A., Thai, K.P., Ho, J., Xiong, C., Hines, C. & Kellman, P.J. (2016). Perceptual learning of abstract musical patterns: Recognizing composer style. Proceedings of the 14th International Conference on Music Perception and Cognition.

Thai, K.P., Krasne, S. & Kellman, P.J. (2015). Adaptive perceptual learning in electrocardiography: The synergy of passive and active classification. In Noelle, D. C., Dale, R., Warlaumont, A. S., Yoshimi, J., Matlock, T., Jennings, C. D., & Maglio, P. P. (Eds.) Proceedings of the 37th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society, 2350-2355.

Alibali, M., Kalish, C., Rogers, T.T., Sloutsky, V., Massey, C.M., Kellman, P.J., McClelland, J.L., & Mickey, K.W. (2015). Connecting learning, memory, and representation in math education. In Noelle, D. C., Dale, R., Warlaumont, A. S., Yoshimi, J., Matlock, T., Jennings, C. D., & Maglio, P. P. (Eds.) Proceedings of the 37th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society, 19-20.

Krasne, S., Rimoin, L., Altieri, L., Craft, N. & Kellman, P.  (2015). Training pattern recognition of skin lesion morphology, configuration and distribution. Journal of the American Academy of Dermatology72(3):489-95. doi: 10.1016/j.jaad.2014.11.016. Epub 2015 Jan 13.

Bufford, C.A., Mettler, E., Geller, E.H. & Kellman, P.J. (2014). The psychophysics of algebra expertise: Mathematics perceptual learning interventions produce durable encoding changes. In P. Bello, M. Guarini, M. McShane & B. Scassellati, (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Kellman, P.J. & Massey, C. M. (2013). Perceptual learning, cognition, and expertise. In Ross, B. (Ed.). Psychology of Learning and Motivation, Volume 58, Academic Press, Elsevier, Inc.

Thai, K., Mettler, E., & Kellman, P. J. (2011). Basic information processing effects from perceptual learning in complex, real-world domains. In L. Carlson, C. Holscher, & T Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 555-560). Boston, MA: Cognitive Science Society.

Kellman, P.J., Massey, C.M & Son, J. (2010). Perceptual learning modules in mathematics: Enhancing students' pattern recognition, structure extraction, and fluency.  Topics in Cognitive Science (Special Issue on Perceptual Learning), Vol. 2, Issue 2, 285-305.

Massey, C.M., Kellman, P.J., Roth, Z. & Burke, T.  (2010). Perceptual learning and adaptive learning technology:  Developing new approaches to mathematics learning in the classroom. In Stein, N.L. (Ed.), Developmental and learning sciences go to school: Implications for education. NY: Taylor & Francis.

Kellman, P.J., Massey, C.M., Roth, Z., Burke, T., Zucker, J., Saw, A., Aguero, K.E. & Wise, J.A. (2008). Perceptual learning and the technology of expertise: Studies in fraction learning and algebra. Learning Technologies and Cognition: Special issue of Pragmatics & Cognition16:2, 356–405.

Kellman, P.J. & Garrigan, P.B. (2009).  Perceptual learning and human expertise.  Physics of Life ReviewsVol. 6, No. 2, 53-84.

Garrigan, P.B. & Kellman, P.J. (2008). Perceptual learning depends on perceptual constancy. Proceedings of the National Academy of Sciences (USA), Vol. 105, No. 6, 2248-2253.

Kellman, P.J.  (2002).  Perceptual learning.  In R. Gallistel (Ed.), Stevens' handbook of experimental psychology, third edition, Vol. 3 (Learning, motivation and emotion), John Wiley & Sons. 

Kellman, P.J., Burke, T. & Hummel, J.  (1999). Modeling perceptual learning of abstract invariants.  In Hahn, M. & Stoness, S.C. (Eds.). Proceedings of the Twenty-First Annual Conference of the Cognitive Science Society, Mahwah, NJ:  Lawrence Erlbaum Associates, 264-269.

Kellman, P.J. & Arterberry, M.A. (2006). Infant visual perception.  In R. Siegler and D. Kuhn (Eds.), Handbook of Child Psychology, Sixth Edition, Volume 2:  Cognition, Perception, and Language.  New York: Wiley.

Kellman, P.J. & Arterberry, M.  (1998). The Cradle of Knowledge: Perceptual Development in Infancy.  Cambridge, MA:  MIT Press. ISBN 0-262-11232-9.

Kellman, P.J. and Banks, M.S. (1997).  Infant visual perception.  In R. Siegler and D. Kuhn (Eds.), Handbook of Child Psychology, Fifth Edition, Volume 2:  Cognition, Perception, and Language.  New York: Wiley, 103-146.

Kellman, P.J. (1996).  The origins of object perception. In Gelman, R. & Au, T. (Eds.), Handbook of Perception and Cognition, Volume 8:  Perceptual and Cognitive Development, Academic Press.

Kellman, P.J. (1995).  Ontogeny of visual space and motion perception.  In Epstein, W. & Rogers, S. (Eds.), Handbook of Perception and Cognition, Volume 5:  Perception of Space and Motion, Academic Press.

Kellman, P. J. (1992).  Kinematic foundations of perceptual development.  In Granrud, C. (Ed.), Development of Perception: The 1989 Carnegie-Mellon Symposium on Cognition, Hillsdale, NJ:  Erlbaum.

Kellman, P. J. & Short, K. R. (1987).  Development of three-dimensional form perception.  Journal of Experimental Psychology: Human Perception & Performance, 13(4), 545-557.

Kellman, P. J. Gleitman, H. & Spelke, E. S. (1987).  Object and observer motion in the perception of objects by infants.  Journal of Experimental Psychology: Human Perception & Performance, 13(4), 586-593.

Kellman, P. J. (1984).  Perception of three-dimensional form by human infants. Perception & Psychophysics,  36(4), 353-358.

Kellman, P. J. & Spelke, E. S. (1983).  Perception of partly occluded objects in infancy.  Cognitive Psychology, 15, 483-524.

 

Adaptive Learning

Mettler, E., Massey, C.M., 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. Austin, TX: Cognitive Science Society.

Mettler, E.M., Massey, C.M. & Kellman, P.J.  (2016). A comparison of adaptive and fixed schedules of practice. Journal of Experimental Psychology: General, 145(7): 897-917.

Mettler, E.M. & Kellman, P.J. (2014). Adaptive response-time-based sequencing in perceptual learning. Vision Research, 99: 111-123.

Mettler, E., Massey, C. & Kellman, P. (2011). Improving adaptive learning technology through the use of response times. In L. Carlson, C. Holscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Boston, MA: Cognitive Science Society, 2532-2537.

Kellman, P. (2006). System and method for adaptive learning; US Patent 7052277. http://www.google.com/patents/US7052277

 

Applications of Perceptual and Adaptive Learning to Learning Technology

Kellman, P. J., & Krasne, S. (in press). Perceptual and adaptive learning technology in medical learning. Medical Teacher.

Romito, B., Krasne, S., Kellman, P. & Dhillon, A. (2016). The impact of a perceptual and adaptive learning module on transoesophageal echocardiography interpretation by anaesthesiology residents. British Journal of Anaesthesia117 (4): 477-481.

Unuma, H., Hasegawa, H. , & Kellman, P.J. (2016). Perceptual learning facilitates precise mental representations of fractions. The Journal of Kawamura Gakuen Women's University. 27(1), 35-49.

Lerner, N., Gill, M., Scott-Parker, B. & Kellman, P.J. (2016).  Accelerating driver expertise through perceptual and adaptive learning. Report to the AAA Foundation for Traffic Safety, Westat Corp. (Available on NAS website at: https://trid.trb.org/view.aspx?id=1461088)

Massey, C.M., Kregor, J.D. & Kellman, P.J. (2016). Implementing mathematics learning software successfully in urban schools: Lessons for research and practice. American Educational Research Association (AERA) Online Paper Repository. http://www.aera.net/Publications/Online-Paper-Repository/AERA-Online-Paper-Repository/Owner/444889

Carolyn A. Bufford, C.A., Thai, K.P., Ho, J., Xiong, C., Hines, C. & Kellman, P.J. (2016). Perceptual learning of abstract musical patterns: Recognizing composer style. Proceedings of the 14th International Conference on Music Perception and Cognition.

Rimoin, L., Altieri, L., Craft, N., Krasne, S. & Kellman, P.J. (2015). Training pattern recognition of skin lesion morphology, configuration, and distribution. Journal of the American Academy of Dermatology72(3):489-95. doi: 10.1016/j.jaad.2014.11.016. Epub 2015 Jan 13.

Thai, K.P., Krasne, S. & Kellman, P.J. (2015). Adaptive perceptual learning in electrocardiography: The synergy of passive and active classification. In Noelle, D. C., Dale, R., Warlaumont, A. S., Yoshimi, J., Matlock, T., Jennings, C. D., & Maglio, P. P. (Eds.) Proceedings of the 37th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society, 2350-2355.

Bufford, C.A., Mettler, E., Geller, E.H. & Kellman, P.J. (2014). The psychophysics of algebra expertise: Mathematics perceptual learning interventions produce durable encoding changes. In P. Bello, M. Guarini, M. McShane & B. Scassellati, (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Krasne, S., Hillman, J. D., Kellman, P. J. & Drake, T. A. (2013). Applying perceptual and adaptive learning techniques for teaching introductory histopathology.  Journal of Pathology Informatics, 4, 34-41.

Kellman, P. J. (2013). Adaptive and perceptual learning technologies in medical education and training. Military Medicine178, 10: 98-106.

Kellman, P.J., Massey, C.M & Son, J. (2010). Perceptual learning modules in mathematics: Enhancing students' pattern recognition, structure extraction, and fluency.  Topics in Cognitive Science (Special Issue on Perceptual Learning), Vol. 2, Issue 2, 285-305.

Massey, C.M., Kellman, P.J., Roth, Z. & Burke, T.  (2010). Perceptual learning and adaptive learning technology:  Developing new approaches to mathematics learning in the classroom. In Stein, N.L. (Ed.), Developmental and learning sciences go to school: Implications for education. NY: Taylor & Francis.

Kellman, P.J., Massey, C.M., Roth, Z., Burke, T., Zucker, J., Saw, A., Aguero, K.E. & Wise, J.A. (2008). Perceptual learning and the technology of expertise: Studies in fraction learning and algebra. Learning Technologies and Cognition: Special issue of Pragmatics & Cognition, 16:2 (2008), 356–405.

Kellman, P.J., Palmer, E.M., Clausner, T. (2003). System and method for representation of aircraft altitude using spatial size and other natural perceptual cues; US Patent 20030151630. http://www.google.com/patents/US20030151630

Kellman, P.J., Stratechuk, T. & Hampton, S. (1999).  Training pilots’ pattern recognition skills: Perceptual learning modules (PLMs) in instrument flight training.  In Wiggins, M. (Ed.)  Proceedings of the 2nd Annual Embry-Riddle Aeronautical University Flight Instructor Conference, Daytona Beach, FL:  Embry-Riddle University Press.

Kellman, P.J. & Kaiser, M.K. (1994). Perceptual learning modules in flight training.  Proceedings of the 38th Annual Meeting of the Human Factors and Ergonomics Society, 1183-1187.