Dana H. Ballard

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Dana Harry Ballard (born 1946) is a professor of computer science currently at the University of Texas at Austin and formerly with the University of Rochester.[1]

Ballard received his Ph.D. from the University of California, Irvine. He has done research in artificial intelligence and human cognition and perception with a focus on the human visual system. In 1982, with Christopher M. Brown he authored a pioneering textbook in the field of computer vision, titled Computer Vision.[2] He also popularized the use of the generalised hough transform in computer vision in his paper "Generalizing the Hough Transform to Detect Arbitrary Shapes." [3] He is also known as a proponent of active vision techniques for computer vision systems [4] as well as approaches to understanding human vision.[5] His textbook titled "An Introduction to Natural Computation" (1997) combines introductory material on varied subjects relevant to computing in the brain, such as neural networks, reinforcement learning, and genetic learning.[6] His most recent book, "Brain Computation as Hierarchical Abstraction," describes a multilevel approach to understanding neural computation.[7]


  1. ^ Personal Website
  2. ^ D.H. Ballard, C.M. Brown, Computer Vision, Prentice Hall, 1982
  3. ^ D.H. Ballard, "Generalizing the Hough Transform to Detect Arbitrary Shapes", Pattern Recognition, Vol.13, No.2, p.111-122, 1981
  4. ^ Ballard, D.H., "Animate vision," Artificial Intelligence Journal 48, 57-86, 1991
  5. ^ Ballard, D. H. and Hayhoe, M. M.(2009) Modeling the role of task in the control of gaze, Visual Cognition, 17, 1185-1204
  6. ^ Ballard (1997). An Introduction to Natural Computation. Cambridge, Massachusetts: MIT Press. 
  7. ^ Ballard (2015). Brain Computation as Hierarchical Abstraction. Cambridge, Massachusetts: MIT Press. 

Further reading[edit]