2015 - Distinguished Fellow of the British Machine Vision Association (BMVA)
2008 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to biometrics and computer vision.
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Biometrics, Gait and Feature extraction. His work carried out in the field of Artificial intelligence brings together such families of science as Gait, Identification, Gait analysis and Pattern recognition. His Computer vision research focuses on subjects like Artificial neural network, which are linked to Stick figure.
His study in Biometrics is interdisciplinary in nature, drawing from both Signature, Speech recognition and Field. His Gait study combines topics from a wide range of disciplines, such as Motion, Fourier transform, Process and Pattern recognition. His studies deal with areas such as Curse of dimensionality, Maxima and minima, Motion analysis, Feature vector and Invariant as well as Feature extraction.
Mark S. Nixon mainly focuses on Artificial intelligence, Computer vision, Biometrics, Pattern recognition and Gait. His research on Artificial intelligence often connects related areas such as Gait analysis. His study in Noise, Image, Motion, Feature and Edge detection falls under the purview of Computer vision.
His studies in Biometrics integrate themes in fields like Machine learning, Speech recognition and Identification. Mark S. Nixon combines subjects such as Contextual image classification and Face with his study of Pattern recognition. His Gait research integrates issues from Gait, Silhouette and Pattern recognition.
His primary scientific interests are in Artificial intelligence, Biometrics, Computer vision, Soft biometrics and Pattern recognition. His Artificial intelligence research incorporates elements of Gait and Machine learning. His research in Biometrics intersects with topics in Facial recognition system, Face and Identification.
His Computer vision research includes themes of Cluster analysis and Robustness. His Soft biometrics study combines topics from a wide range of disciplines, such as Quality, Field, Categorical variable, Set and Semantics. His work carried out in the field of Pattern recognition brings together such families of science as Focus and Feature.
Mark S. Nixon focuses on Biometrics, Artificial intelligence, Soft biometrics, Computer vision and Identification. The concepts of his Biometrics study are interwoven with issues in Gait and Facial recognition system, Face. His Gait study integrates concerns from other disciplines, such as Gait and Silhouette.
His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Pattern recognition. His studies deal with areas such as Field and Human–computer interaction as well as Computer vision. His Feature extraction study combines topics in areas such as Histogram and Data science.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Feature Extraction and Image Processing
Mark S. Nixon;Alberto S. Aguado.
Audio- and Video-Based Biometric Person Authentication
Josef Kittler;Mark S. Nixon.
WirelessHART: Applying Wireless Technology in Real-Time Industrial Process Control
Jianping Song;Song Han;A.K. Mok;Deji Chen.
real time technology and applications symposium (2008)
Automatic extraction and description of human gait models for recognition purposes
David Cunado;Mark S. Nixon;John N. Carter.
Computer Vision and Image Understanding (2003)
Human Identification Based on Gait
Mark S. Nixon;Tieniu N. Tan;Rama Chellappa.
Automated person recognition by walking and running via model-based approaches
Chew Yean Yam;Mark S Nixon;John N Carter.
Pattern Recognition (2004)
Super-resolution target identification from remotely sensed images using a Hopfield neural network
A.J. Tatem;H.G. Lewis;P.M. Atkinson;M.S. Nixon.
IEEE Transactions on Geoscience and Remote Sensing (2001)
Force field feature extraction for ear biometrics
David J. Hurley;Mark S. Nixon;John N. Carter.
Computer Vision and Image Understanding (2005)
Using Gait as a Biometric, via Phase-weighted Magnitude Spectra
David Cunado;Mark S. Nixon;John N. Carter.
AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication (1997)
On a Large Sequence-Based Human Gait Database
Jamie Shutler;Mike Grant;Mark S Nixon;John N Carter.
Profile was last updated on December 6th, 2021.
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