PeopleofSuperintelligence

Researcher

Paul J. Besl

Also known as Paul Besl, Paul Joseph Besl

Besl is a retired computer vision researcher whose 1992 paper with Neil McKay presented the iterative closest point (ICP) algorithm for registering three-dimensional shapes. He wrote a University of Michigan dissertation on range images in 1986, and Springer published his book Surfaces in Range Image Understanding in 1988. In 1992, he and McKay filed a General Motors patent application for an apparatus that registers measured surface data to a mathematical model, and US patent 5,715,166 was granted in 1998. A 1995 paper with Sapidis described building polynomial surfaces from dense range images, and a patent application filed in 2004 names him among the inventors of a system for compressing, streaming and rendering 3D color image data. He is retired, and the 1992 registration paper has more than 31,000 citations.

Timeline

  1. 1986

    Michigan dissertation on range images

    He writes the University of Michigan dissertation "Surfaces in early range image understanding" in 1986.

  2. 1988

    Book on range image understanding

    Springer publishes his book Surfaces in Range Image Understanding in 1988. The book sets out to develop a theoretical framework and algorithms for understanding range images with computers, together with a software implementation.

  3. 1992

    The iterative closest point method

    In 1992, he and Neil McKay publish "A Method for Registration of 3-D Shapes" in IEEE Transactions on Pattern Analysis and Machine Intelligence. The iterative closest point (ICP) algorithm, introduced by Besl and McKay and by Chen and Medioni, is one of the widely used algorithms for aligning three-dimensional models.

  4. 1992–1998

    Patent on registering 3-D shapes

    In 1992, he and McKay file a General Motors patent application for an apparatus that registers measured surface data points to a mathematical model of a surface. US patent 5,715,166 is granted in 1998.

  5. 1995

    Polynomial surfaces from range images

    In 1995, he and co-author Sapidis publish "Direct construction of polynomial surfaces from dense range images through region growing" in ACM Transactions on Graphics.

  6. 2002–2004

    Patent on streaming 3D color data

    He, Dan Arnold, Yongjian Zhai and Anu Rastogi are named as inventors on a US patent application filed in 2004, with a 2002 priority date, for processing, compressing, streaming and interactively rendering 3D color image data.

  7. As of October 2026

    Retired computer vision researcher

    He is retired. The 1992 paper on registering 3-D shapes that he wrote with McKay has more than 31,000 citations.

  1. Universities had a net outflow of 2,068 moves in AI careersIncludes University of Michigan. Our estimates of career flows and median h-index across universities and companies in AI, including the role of joint appointments and earlier academic jobs.
  2. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of Michigan. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  3. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes University of Michigan. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.
  4. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Michigan. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.

Sources and credits

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  1. Details for: Surfaces in range image understanding / › Koha online catalog katalog.bibliothek.kit.edu. Checked 22 October 2026.
  2. Surfaces in Range Image Understanding - Paul J. Besl - Google Books books.google.com. Checked 22 October 2026.
  3. Iterative closest point - Wikipedia en.wikipedia.org. Checked 22 October 2026.
  4. US5715166A - Apparatus for the registration of three-dimensional shapes - Google Patents patents.google.com. Checked 22 October 2026.
  5. Paul Besl - Google Scholar scholar.google.com. Checked 22 October 2026.
  6. US20040217956A1 - Method and system for processing, compressing, streaming, and interactive rendering of 3D color image data - Google Patents patents.google.com. Checked 22 October 2026.