computer science

John Canny

John Canny is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand John Canny rather than just read about it. In short: John F. Canny (born in 1958) is an Australian computer scientist, and Paul E Jacobs and Stacy Jacobs Distinguished Professor of Engineering in the Computer Science Department of the University of California, Berkeley.

Key takeaways

John Canny belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect John Canny to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of John Canny from memory before moving on to harder problems.

Reference excerpt

John F. Canny (born in 1958) is an Australian computer scientist, and Paul E Jacobs and Stacy Jacobs Distinguished Professor of Engineering in the Computer Science Department of the University of California, Berkeley. He has made significant contributions in various areas of computer science and mathematics, including artificial intelligence, robotics, computer graphics, human-computer interaction, computer security, computational algebra, and computational geometry.

Biography John Canny received his B.Sc. in computer science and theoretical physics from the University of Adelaide in South Australia, 1979, a B.E. (Hons) in electrical engineering, University of Adelaide, 1980, a M.S. and Ph.D. from the Massachusetts Institute of Technology, 1983 and 1987, respectively. In 1987, he joined the faculty of Electrical Engineering and Computer Sciences at UC Berkeley. In 1987, he received the Machtey Award and the ACM Doctoral Dissertation Award. In 1999, he was the co-chair of the Annual Symposium on Computational Geometry. In 2002, he received the American Association for Artificial Intelligence Classic Paper Award for the most influential paper from the 1983 National Conference on Artificial Intelligence. As the author of "A Variational Approach to Edge Detection" and the creator of the widely used Canny edge detector, he was honored for seminal contributions in the areas of robotics and machine perception.

See also Canny edge detector Existential theory of the reals Kinodynamic planning

Publications Canny has published several books, papers and articles. A selection:

1986. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, 1986, pp. 679–698. 1988. The Complexity of Robot Motion Planning. The ACM Distinguished Dissertation Series, Cambridge, MA: The MIT Press, 1988. 1993. "An opportunistic global path planner". With M. C. Lin. In: Algorithmica vol. 10, no. 2–4, pp. 102–120, Aug. 1993. 2007. "MultiView: Improving trust in group video conferencing through spatial faithfulness" (Best Paper Prize). With D. T. Nguyen In: Proc. 2007 SIGCHI Conf. on Human Factors in Computing Systems (CHI '07), New York, NY: The Association for Computing Machinery, Inc., 2007, pp. 1465–1474.

References

External links John F. Canny Homepage at UC Berkeley

Illustrations

Worked examples

Example 1 — a first encounter with John Canny

Start with the simplest possible case. Write down what John Canny claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to John Canny before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about John Canny ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of John Canny

In research: John Canny appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses John Canny in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: John Canny is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1953 births, Australian computer scientists, Living people, so understanding it makes those chapters shorter.
In everyday life: Look for John Canny outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study John Canny in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what John Canny means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain John Canny out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is John Canny in simple terms?

Why does John Canny matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study John Canny?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on John Canny.