Lyndon Smith (academic)

Last updated
Lyndon Smith
Lyndon Smith academic (cropped).jpg
Smith in 2020
Born
Lyndon Neal Smith

(1964-12-26) 26 December 1964 (age 59)
Alma mater University of Wales (BSc)
Cranfield Institute of Technology (MSc)
University of the West of England (PhD)
Scientific career
Fields Computer simulation
Machine vision
Thesis A knowledge based system for powder metallurgy technology (1997)
Doctoral advisor Sagar Midha
Website Lyndon Smith

Lyndon Neal Smith (born 26 December 1964) is an English academic who is Professor in Computer Simulation and Machine Vision at the School of Engineering at the University of the West of England. He is also Director of the Centre for Machine Vision at the Bristol Robotics Laboratory.

Contents

Early life

Smith was born in Stroud, Gloucestershire, on 26 December 1964 to Lionel Alfred Smith and Dorothy Smith. He received a Bachelor of Science (BSc) from the University of Wales in 1986, a Master of Science (MSc) from the Cranfield Institute of Technology in 1988, and a Doctor of Philosophy (PhD) from the University of the West of England in 1997. [1] His PhD thesis was entitled A knowledge based system for powder metallurgy technology. [2] He completed a secondment at the Pennsylvania State University which lasted for a year. [3]

Career

Smith is Professor in Computer Simulation and Machine Vision at the School of Engineering at the University of the West of England. [4] He is also Director of the Centre for Machine Vision at the Bristol Robotics Laboratory. [5]

He has developed a technique for the simulation of the packing densities of particles with irregular morphologies. [6]

He helped develop 3D face recognition technology which he said was "on the verge of becoming really big" in 2017. [7] [8]

Smith has been involved in plans to replace turnstiles on the London Underground with a facial recognition system. [9] He said that facial recognition technology under development could replace train tickets, and have applications in stores, train stations and banks. [10]

Personal life

Smith lives in Wedmore, Somerset. [11]

Selected publications

Books

Related Research Articles

Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images into descriptions of the world that make sense to thought processes and can elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory.

Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. While some core ideas in the field may be traced as far back as to early philosophical inquiries into emotion, the more modern branch of computer science originated with Rosalind Picard's 1995 paper on affective computing and her book Affective Computing published by MIT Press. One of the motivations for the research is the ability to give machines emotional intelligence, including to simulate empathy. The machine should interpret the emotional state of humans and adapt its behavior to them, giving an appropriate response to those emotions.

<span class="mw-page-title-main">Gesture recognition</span> Topic in computer science and language technology

Gesture recognition is an area of research and development in computer science and language technology concerned with the recognition and interpretation of human gestures. A subdiscipline of computer vision, it employs mathematical algorithms to interpret gestures.

<span class="mw-page-title-main">Three-dimensional face recognition</span> Mode of facial recognition

Three-dimensional face recognition is a modality of facial recognition methods in which the three-dimensional geometry of the human face is used. It has been shown that 3D face recognition methods can achieve significantly higher accuracy than their 2D counterparts, rivaling fingerprint recognition.

Facial motion capture is the process of electronically converting the movements of a person's face into a digital database using cameras or laser scanners. This database may then be used to produce computer graphics (CG), computer animation for movies, games, or real-time avatars. Because the motion of CG characters is derived from the movements of real people, it results in a more realistic and nuanced computer character animation than if the animation were created manually.

<span class="mw-page-title-main">MakeHuman</span>

MakeHuman is a free and open source 3D computer graphics middleware designed for the prototyping of photorealistic humanoids. It is developed by a community of programmers, artists, and academics interested in 3D character modeling.

<span class="mw-page-title-main">Visual odometry</span> Determining the position and orientation of a robot by analyzing associated camera images

In robotics and computer vision, visual odometry is the process of determining the position and orientation of a robot by analyzing the associated camera images. It has been used in a wide variety of robotic applications, such as on the Mars Exploration Rovers.

Informatics is the study of computational systems. According to the ACM Europe Council and Informatics Europe, informatics is synonymous with computer science and computing as a profession, in which the central notion is transformation of information. In some cases, the term "informatics" may also be used with different meanings, e.g. in the context of social computing, or in context of library science.

<span class="mw-page-title-main">Christopher R. Johnson</span> American computer scientist

Christopher Ray Johnson is an American computer scientist. He is a distinguished professor of computer science at the University of Utah, and founding director of the Scientific Computing and Imaging Institute (SCI). His research interests are in the areas of scientific computing and scientific visualization.

<span class="mw-page-title-main">Multilinear subspace learning</span> Approach to dimensionality reduction

Multilinear subspace learning is an approach for disentangling the causal factor of data formation and performing dimensionality reduction. The Dimensionality reduction can be performed on a data tensor that contains a collection of observations have been vectorized, or observations that are treated as matrices and concatenated into a data tensor. Here are some examples of data tensors whose observations are vectorized or whose observations are matrices concatenated into data tensor images (2D/3D), video sequences (3D/4D), and hyperspectral cubes (3D/4D).

Maria Petrou FREng was a Greek-born British scientist who specialised in the fields of artificial intelligence and machine vision. She developed a number of novel image recognition techniques, taught at Surrey University and Imperial College London, and was a prolific author of scientific articles.

Matti Kalevi Pietikäinen is a computer scientist. He is currently Professor (emer.) in the Center for Machine Vision and Signal Analysis, University of Oulu, Finland. His research interests are in texture-based computer vision, face analysis, affective computing, biometrics, and vision-based perceptual interfaces. He was Director of the Center for Machine Vision Research, and Scientific Director of Infotech Oulu.

<span class="mw-page-title-main">C3D Toolkit</span> Geometric modelling kernel

C3D Toolkit is a proprietary cross-platform geometric modeling kit software developed by Russian by C3D Labs. It's written in C++. It can be licensed by other companies for use in their 3D computer graphics software products. The most widely known software in which C3D Toolkit is typically used are computer aided design (CAD), computer-aided manufacturing (CAM), and computer-aided engineering (CAE) systems.

Emotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. Use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context. To date, the most work has been conducted on automating the recognition of facial expressions from video, spoken expressions from audio, written expressions from text, and physiology as measured by wearables.

Egocentric vision or first-person vision is a sub-field of computer vision that entails analyzing images and videos captured by a wearable camera, which is typically worn on the head or on the chest and naturally approximates the visual field of the camera wearer. Consequently, visual data capture the part of the scene on which the user focuses to carry out the task at hand and offer a valuable perspective to understand the user's activities and their context in a naturalistic setting.

<span class="mw-page-title-main">Michael J. Black</span> American-born computer scientist

Michael J. Black is an American-born computer scientist working in Tübingen, Germany. He is a founding director at the Max Planck Institute for Intelligent Systems where he leads the Perceiving Systems Department in research focused on computer vision, machine learning, and computer graphics. He is also an Honorary Professor at the University of Tübingen.

Xiaoming Liu is a Chinese-American computer scientist and an academic. He is a Professor in the Department of Computer Science and Engineering, MSU Foundation Professor as well as Anil K. and Nandita Jain Endowed Professor of Engineering at Michigan State University.

Gérard G. Medioni is a computer scientist, author, academic and inventor. He is a vice president and distinguished scientist at Amazon and serves as emeritus professor of Computer Science at the University of Southern California.

References

  1. Who's Who in Science and Engineering: 2002-2003. Marquis Who's Who; 6th edition. 2001. p. 906. ISBN   0837957605.
  2. "A knowledge based system for powder metallurgy technology". British Library EthOS. Retrieved 14 October 2023.
  3. Farooq, A. R.; Smith, M. L.; Smith, L. N.; Midha, P. S. (2005). "Dynamic photometric stereo for on line quality control of ceramic tiles". Computers in Industry. 56 (8–9): 918–934. doi:10.1016/j.compind.2005.05.017 . Retrieved 23 June 2020.
  4. "Professor Lyndon Smith". UWE Bristol. Retrieved 23 June 2020.
  5. "Members of the Centre for Machine Vision (CMV)". UWE Bristol. 5 October 2023. Retrieved 14 October 2023.
  6. Smith, L. N.; Midha, P. S. (1997). "Computer simulation of morphology and packing behaviour of irregular particles, for predicting apparent powder densities". Computational Materials Science. 7 (4): 377–383. doi:10.1016/S0927-0256(97)00003-7 . Retrieved 5 August 2020.
  7. "3D facial recognition technology on the brink of commercial breakthrough". Mercia. 26 June 2017. Retrieved 23 June 2020.
  8. "UWE leads the way in 3D facial recognition tech". bristol247.com. 19 June 2017. Retrieved 23 June 2020.
  9. "You are your password: The world of biometrics". CNN. 12 February 2018. Retrieved 23 June 2020.
  10. Baggaley, Kate (14 September 2017). "How Facial Recognition Systems Will Reshape Your Daily Life". NBC News. Retrieved 23 June 2020.
  11. "FREE DOWNLOAD !! Wedmore Professor – Latest Book Now Available". The Isle of Wedmore. 1 December 2020. Retrieved 14 October 2023.