• Visual perception of objects, space, and motion
• Perceptual learning and development.
• Applications of perceptual learning, visual cognition, and adaptive learning to education, skill acquisition and educational technology.
• Human factors applications of perception and cognition research, e.g., perceptual and cognitive processes in aviation and driving.
Research in our laboratory centers on human perception and cognition, with an emphasis on visual perception of objects, space and motion. 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 environments, and events occurring within it. Focal points include object and surface perception from information that is fragmentary across space and time, visual perception of objects and space by moving observers, perception of shape, and interactions among object, space and motion perception.
We also study perceptual learning and its relations to other aspects of learning, expertise and cognition. Research in recent years is helping to broaden ordinary conceptions of learning and instruction that focus on declarative and procedural aspects. These are important but incomplete in that they do not include the dramatic effects of experience in any learning domain in changing the way information gets encoded (perceptual learning). As studies of expertise have revealed, domain-specific attunements of information extraction, discovery and encoding of new relational structure, and improvements in fluency of information pickup are crucial components of becoming good at anything. Our work seeks to understand these perceptual learning effects, and we also develop and test methods of training and accelerating expert information extraction and pattern recognition skills. Synergistic with this work are novel adaptive learning algorithms that improve the efficiency of learning in any domain (factual, procedural, perceptual learning, or combinations of these). These efforts in computer-based learning technology have already produced dramatic advances in learning, retention, and transfer in diverse domains, such as aviation training, mathematics and science learning, and medical learning. We also seek deep models of high-level perceptual learning that capture the abstract properties of human perception and perceptual learning.
Please visit our lab
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
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, 8:978. 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
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. & Garrigan, P.B. (2009). Perceptual learning and human expertise. Physics of Life Reviews, Vol. 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.
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
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 Dermatology, 72(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.
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 Medicine. 178, 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.