Richard Hartley (scientist) explained

Richard Hartley
Alma Mater:Australian National University
Stanford University
University of Toronto (1976, PhD)
Known For:Computer Vision, Multiple-view geometry

Richard I. Hartley is an Australian computer scientist and an Emeritus professor at the Australian National University, where he is a member of the Computer Vision group in the Research School of Computing.

Education and career

In 1971, Hartley received a BSc degree from the Australian National University followed by MSc (1972) and PhD (1976) degrees in mathematics from the University of Toronto. He also obtained an MSc degree in computer science from Stanford University in 1983.[1]

His work is primarily devoted to the fields of Artificial intelligence, Image processing, and Computer vision. He is best known for his 2000 book Multiple View Geometry in computer vision, written with Andrew Zisserman, now in its second edition (2004). According to WorldCat, the book is held in 1428 libraries.[2]

Hartley was elected a Fellow of the Australian Academy of Science in 2005[3] and awarded their Hannan Medal in 2023.[4] He was elected a Fellow of the Royal Society in 2024.[5]

Publications

Hartley has published a wide variety of articles in computer science on the topics of computer vision and optimization. The following are his most highly cited works [6]

External links

Notes and References

  1. Web site: Department of Computer Science - December 7, 2010 - Richard Hartley. Johns Hopkins Whiting School of Engineering. 30 August 2014.
  2. https://www.worldcat.org/oclc/171123855 WorldCat book entry
  3. Web site: Richard Hartley . 2023-03-14 . Australian Academy of Science . en.
  4. Web site: 2023-03-14 . Decoding dragons and devils, what triggers volcanoes, and more: Australia's stars of science . 2023-03-14 . Australian Academy of Science . en.
  5. Web site: Professor Richard Hartley FRS . 2024-05-20 . Royal Society . en.
  6. Web site: Richard Hartley.
  7. http://www.robots.ox.ac.uk/~vgg/hzbook/ Multiple View Geometry in Computer Vision