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Ennio Mingolla Wins Helmholtz Prize Of The INNS
Professor Ennio Mingolla of the Department of Cognitive and Neural Systems was awarded the 2007 Helmholtz Award of the International Neural Network Society (INNS: http://www.inns.org) for his seminal research in visual perception. Professor Mingolla is one of the most distinguished vision scientists in the world who develops breakthrough biological neural models of how the brain sees and applies them to the solution of outstanding problems in computer vision and image processing. He is also a distinguished experimentalist who carries out highly respected psychophysical experiments to guide the development of his biological neural models and to test their predictions. He exemplifies the highest standards of scholarship and technical virtuosity in all of his modeling and experimental work.
Mingolla is Professor of Cognitive and Neural Systems, as well as Professor of Psychology, at Boston University. He is the Director of the CNS Vision Laboratory, an Assistant Director of the inter-university NSF Center of Excellence for Learning in Education, Science, and Technology (CELEST) at Boston University, and leader of the CELEST program in vision and recognition. He is a long-standing member of the editorial boards of the journals Neural Networks and Ecological Psychology and has been an invited speaker at numerous international conferences. He was invited to give the annual Kanizsa lecture in Trieste, Italy in 2001 and a plenary lecture at the International Conference on Theoretical Neurobiology in New Delhi, India in 2003.
Mingolla's research has included an extraordinary range of topics, including 3D shape-from-shading, shape-from-texture, perceptual grouping, surface filling-in, lightness perception, motion perception, and transparency. He has published these results in 77 research articles with a wide range of distinguished colleagues.
Mingolla's first breakthrough work in vision was published in a articles with James Todd that were published in 1983-1986 in the Journal of Experimental Psychology: Human Perception and Performance and Biological Cybernetics. This work studied 3D shape-from-shading using the then-novel method of displaying artificially rendered shapes on a computer monitor and using them to generate important parametric data in psychophysical experiments. As has always been characteristic of his empirical research, the experiments evaluated the biological validity of several mathematical models of shape-from-shading that had recently been proposed in the literature. The experiments showed that these models were deficient and needed to be replaced. The collaboration with Todd on 3D shape has continued until the present day, with the most recent contribution being a 2004 study in Psychological Science about how lightness constancy is maintained in the presence of specular highlights.
Mingolla's first work as a neural modeler of vision was published in 1985 in Psychological Review and in Perception and Psychophysics. This pair of breakthrough articles with Stephen Grossberg introduced what has remained the leading biological neural model of how the brain sees. These articles, which have both been cited approximately 250 times, introduced new perceptual concepts and neural mechanisms into the field of biological vision, notably the prediction that the units of visual perception are boundaries and surfaces that obey complementary computational laws. In particular, the articles predicted how and why perceptual grouping and surface filling-in occur. They introduced the concept of bipole cells, and predicted that they carry out perceptual grouping. This prediction has subsequently received psychophysical, anatomical, and neurophysiological support, and is now frequently used in models of perceptual grouping. Often known as the BCS/FCS model, this model has also led to influential applications by Grossberg and Mingolla in image processing. The BCS/FCS model has been used to process synthetic aperture radar, laser radar, multispectral infrared, and night vision sensor data, notably through a technology transfer with the MIT Lincoln Laboratory which hired more than 10 PhDs trained in BCS/FCS methods to further develop this model for neuromorphic technology applications. The Grossberg-Mingolla collaboration has also continued to the present day, and has included the progressive development of models of perceptual grouping, lightness perception, neon color spreading, motion perception, visual feature binding and persistence, 3D shape-from-shading, 3D shape-from-texture, a laminar circuit architecture of visual cortex, visual navigation using optic flow, visual search of multi-element displays, target tracking by smooth pursuit eye movements, and the McCollough effect. Mingolla's modeling work includes such brain areas as LGN, V1, V2, V4, MT, MST, and PPC, including nonlinear feedforward and feedback interactions among these various areas.
In parallel with these long-standing collaborations, in which Mingolla has played a key role, he has carried out important experimental and modeling projects with many other colleagues including Larry Arend, Jacob Beck, Julia Berzhanskaya, Paula Bressan, Gail Carpenter, Robert Cunningham, Paolo Gaudiano, Alexander Grunewald, Gregory Lesher, Lars Lidén, Siegfried Martens, Heiko Neumann, Farley Norman, Scott Oddo, Ogi Ogas, Christopher Pack, Luiz Pessoa, Lothar Spillmann, Lavanya Viswanathan, and Takeo Watanabe. His most recent psychophysical investigations have focused on the study of mechanisms of attentional tracking and control of eye movements for multi-target tracking, and on perception of surface gloss as a probe of how global 3D surface percepts are formed. He has been primary research advisor for 13 PhD students and 1 postdoctoral fellow, in addition to the many students whom he has mentored in the CNS Vision Laboratory.
Selected Articles:
Mingolla, E. and Todd, J.T. (1984). Computational techniques for the graphic simulation of quadric surfaces. Journal of Experimental Psychology: Human Perception and Performance, 10(5), 740-745.
Grossberg, S. and Mingolla, E. (1985). Neural dynamics of form perception: Boundary completion, illusory figures, and neon color spreading. Psychological Review, 92(2), 173-211.
Grossberg, S. and Mingolla, E. (1985). Neural dynamics of perceptual grouping: Textures, boundaries, and emergent segmentations. Perception and Psychophysics, 38(2), 141-171.
Mingolla, E. and Todd, J.T. (1986). Perception of solid shape from shading. Biological Cybernetics, 53, 137-151. Reprinted in B.K.P. Horn and M.J. Brooks (Eds.), Shape from shading. Cambridge, MA: MIT Press, 1989, pp.409-441.
Mingolla, E. (1991). Neural dynamics of motion segmentation and grouping. In R. Lippmann, J. Moody, and D.S. Touretsky (Eds.), Advances in neural information processing systems. San Diego: Morgan Kaufman.
Lesher, G.W. and Mingolla, E. (1993). The role of edges and line-ends in illusory contour formation. Vision Research, 33(16), 2253-2270.
Lesher, G.W. and Mingolla, E. (1995). Illusory contour formation. In M.A. Arbib (Ed.), Handbook of brain theory and neural networks. Cambridge, MA: MIT Press, pp.481-483.
Pessoa, L., Beck, J., and Mingolla, E. (1996). Perceived texture segregation in chromatic element-arrangement patterns: High intensity interference. Vision Research, 36(12), 1745-1760.
Pessoa, L., Mingolla, E., and Arend, L. (1996). The perception of lightness in 3-D curved objects. Perception and Psychophysics, 58(8), 1293-1305.
Bressan, P., Mingolla, E., Spillmann, L. and Watanabe, T. (1997). Neon color spreading: A review. Perception, 26(11), 1353-1366.
Grossberg, S., Mingolla, E., and Ross, W.D. (1997). Visual brain and visual perception: How does the cortex do perceptual grouping? Trends in Neurosciences, 20(3), 106-111.
Chey, J., Grossberg, S., and Mingolla, E. (1998). Neural dynamics of motion processing and speed discrimination. Vision Research, 38, 2769-2786.
Grunewald, A. and Mingolla, E. (1998). Motion aftereffect due to interocular sum of adaptation to linear motion. Vision Research, 38, 2863-2971.
Lidén, L. and Mingolla, E. (1998). Monocular occlusion cues alter the influence of terminator motion in the barber pole phenomenon. Vision Research, 38, 3883-3898.
Neumann, H., Pessoa, L., and Mingolla, E. (1998). A neural network architecture of brightness perception: Non-linear contrast detection and geometry-driven diffusion. Journal of Image and Vision Computing, 16(6), 423-446.
Pack, C. and Mingolla, E. (1998). Global induced motion and visual stability in an optic flow illusion. Vision Research, 38, 3083-3093.
Ross, W.D. and Mingolla, E. (1998). Recent progress in modeling neural mechanisms of form and color vision. Invited article for a Special Issue of the Journal of Image and Vision Computing, 16(6), 447-461.
Mingolla, E., Ross, W.D., and Grossberg, S. (1999). A neural network for enhancing boundaries and surfaces in synthetic aperture radar images. Neural Networks, 12, 499-511.
Oddo, S., Beck, J., and Mingolla, E. (1999). Texture segregation in chromatic element-arrangement patterns. Spatial Vision, 12(4), 421-459.
Grossberg, S., Mingolla, E., and Viswanathan, L. (2001) Neural dynamics of motion integration and segmentation within and across apertures. Vision Research, 41(19): 2521-53.
Mingolla, E., Todd, J.T., and Norman, J.F. (2001). Perception of lightness of glossy surfaces. In B. Rogowitz and N. Pappas (Eds.), Proceedings of SPIE: Human vision and electronic imaging VI, Vol. 4299, pp.302-311.
Neumann, H. and Mingolla, E. (2001) Computational neural models of spatial integration in perceptual grouping. In From fragments to objects: Grouping and segmentation in vision. T.F.Shipley and P.J. Kellman, Eds. Amsterdam: Elsevier, pp. 353-400.
Grossberg, S., Hwang, S., and Mingolla, E. (2002). Thalamocortical dynamics of the McCollough effect: Boundary-surface alignment through perceptual learning. Vision Research, 42, 1259-1286.
Mingolla, E. (2002). Le unitŕ della visione. Sistemi Intelligenti, Anno XIV, No. 3, 461-480 (in Italian).
Viswanathan, L. and Mingolla, E. (2002). Dynamics of attention in depth: Evidence from multi-element tracking. Perception, 31, 1415-1437.
Mingolla, E. (2003). Neural models of motion integration and segmentation. Neural Networks, 16, 939-945.
Neumann, H. and Mingolla, E. (2003). Contour and surface perception. In M.A. Arbib (Ed.), Handbook of brain theory and neural networks, II. Cambridge, MA: MIT Press, pp.271-276.
Carpenter, G.A., Martens, S., Mingolla, E., Ogas, O.J., and Sai, C. (2004) Biologically inspired approaches to automated feature extraction and target recognition. Proceedings of the 33rd Workshop on Applied Imagery Pattern Recognition -- AIPR 2004, October 13-15, Washington, DC. Piscataway, NJ: IEEE.
Todd, J.T., Norman, J.F., and Mingolla, E. (2004). Lightness constancy in the presence of specular highlights. Psychological Science, 15(1), 33-39.
Berzhanskaya J., Swaminathan G., Beck J., and Mingolla E. (2005). Remote effects of highlights on gloss perception. Perception, 34(5), 565-575.
Berzhanskaya, J., Grossberg, S., and Mingolla, E. (2007) Laminar cortical dynamics of visual form and motion interactions during coherent object motion perception. Spatial Vision, in press.
Grossberg, S., Kuhlmann, L., and Mingolla, E. (2007) A Neural Model of 3D Shape-From-Texture: Multiple-Scale Filtering, Boundary Grouping, and Surface Filling-In. Vision Research, in press.
Contact Information:
Professor Ennio Mingolla
Department of Cognitive and Neural Systems
Boston University
Boston, MA 02215
email: ennio @ cns.bu.edu
(617)-353-9485
(617)-353-7755