Matti Pietikäinen (academic)

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,[1] and Scientific Director of Infotech Oulu.[2]

Matti Kalevi Pietikäinen
NationalityFinnish
Citizenship Finland
Alma materUniversity of Oulu
Known forfundamental contributions to texture analysis and facial image analysis
AwardsIEEE Fellow
IAPR Fellow
Pentti Kaitera Prize
Koenderink Prize
King-Sun Fu Prize
Highly Cited Researcher
Scientific career
FieldsComputer vision,
Pattern recognition
InstitutionsUniversity of Oulu,
Center for Machine Vision and Signal Analysis
Doctoral advisorAzriel Rosenfeld

Biography

Pietikäinen received the Doctor of Science in Technology degree from University of Oulu, Finland, in 1982. From 1980 to 1981 and from 1984 to 1985 he was with the Computer Vision Laboratory at the University of Maryland, working with a pioneer of the computer image analysis, Professor Azriel Rosenfeld. After the first visit, he established computer vision research at University of Oulu.[3]

He has authored over 350 refereed scientific publications, which have been frequently cited.[4] He has made pioneering contributions to local binary patterns (LBP) methodology, texture-based image and video analysis, and facial image analysis.

He was Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Pattern Recognition, IEEE Transactions on Forensics and Security, and Image and Vision Computing journals. Currently he serves as Associate Editor of IEEE Transactions on Biometrics, Behavior and Identity Science, and Guest Editor for special issues of IEEE TPAMI and International Journal of Computer Vision.

In 2011, he was named an IEEE Fellow for his contributions to texture and facial image analysis for machine vision.[5] Already in 1994, he received the IAPR Fellow nomination for contributions to machine vision and its applications in industry and service to the IAPR.[6] In 2018, he received the IAPR's King-Sun Fu Prize for fundamental contributions to texture analysis and facial image analysis.[7] He was named a Highly Cited Researcher by Clarivate Analytics in 2018.[8]

Selected publications
  • Ojala, T.; Pietikäinen, M.; Harwood, D. (1996). "A comparative study of texture measures with classification based on feature distributions". Pattern Recognition. 29 (1): 51–59. doi:10.1016/0031-3203(95)00067-4.
  • Sauvola, J.; Pietikäinen, M. (2000). "Adaptive document image binarization". Pattern Recognition. 33 (2): 225–236. doi:10.1016/S0031-3203(99)00055-2. hdl:10338.dmlcz/145819.
  • Ojala, T.; Pietikäinen, M.; Mäenpää, T. (2002). "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns". IEEE Transactions on Pattern Analysis and Machine Intelligence. 24 (7): 971–987. CiteSeerX 10.1.1.157.1576. doi:10.1109/tpami.2002.1017623.
  • Heikkilä, M.; Pietikäinen, M. (2006). "A texture-based method for modeling the background and detecting moving objects". IEEE Transactions on Pattern Analysis and Machine Intelligence. 28 (4): 657–662. CiteSeerX 10.1.1.404.508. doi:10.1109/TPAMI.2006.68. PMID 16566514.
  • Ahonen, T.; Hadid, A.; Pietikäinen, M. (2006). "Face description with local binary patterns: Application to face recognition". IEEE Transactions on Pattern Analysis and Machine Intelligence. 28 (12): 2037–2041. doi:10.1109/tpami.2006.244. PMID 17108377.
  • Zhao, G.; Pietikäinen, M. (2007). "Dynamic texture recognition using local binary patterns with an application to facial expressions". IEEE Transactions on Pattern Analysis and Machine Intelligence. 29 (6): 915–928. CiteSeerX 10.1.1.714.2104. doi:10.1109/tpami.2007.1110. PMID 17431293.
  • Heikkilä, M.; Pietikäinen, M.; Schmid, C. (2009). "Description of interest regions with local binary patterns". Pattern Recognition. 42 (3): 425–436. CiteSeerX 10.1.1.323.7119. doi:10.1016/j.patcog.2008.08.014.
  • Pietikäinen, M.; Hadid, A.; Zhao, G.; Ahonen, T. (2011). Computer vision using local binary patterns. Springer.
  • Määttä, J.; Hadid, A.; Pietikäinen, M. (2011). Face spoofing detection from single images using micro-texture analysis. Proc. International Joint Conference on Biometrics (IJCB). pp. 1–7.
  • Pfister, T.; Li, X.; Zhao, G.; Pietikäinen, M. (2011). Recognising spontaneous facial micro-expressions. Proc. IEEE International Conference on Computer Vision (ICCV). pp. 1449–1456.
  • Zhou, Z.; Hong, X.; Zhao, G.; Pietikäinen, M. (2014). "A compact representation of visual speech data using latent variables". IEEE Transactions on Pattern Analysis and Machine Intelligence. 36 (1): 181–187.
  • Li, X.; Chen, J.; Zhao, G.; Pietikäinen, M. (2014). Remote heart rate measurement from face videos under realistic situations. Proc. IEEE Conference on Pattern Recognition and Computer Vision (CVPR). pp. 4265–4271.
  • Liu, L.; Lao, S.; Fieguth, P.; Guo, Y.; Wang, X.; Pietikäinen, M. (2016). "Median robust extended local binary pattern for texture classification". IEEE Transactions on Image Processing. 25 (3): 1368–1381. doi:10.1109/TIP.2016.2522378. PMID 26829791.
  • Liu, L.; Fieguth, P.; Guo, Y.; Wang, X.; Pietikäinen, M. (2017). "Local binary features for texture classification: Taxonomy and experimental study". Pattern Recognition. 62: 135–160. doi:10.1016/j.patcog.2016.08.032.
  • Liu, L.; Chen, J.; Fieguth, P.; Zhao, G.; Chellappa, R.; Pietikäinen, M. (2019). "From BoW to CNN: Two decades of texture representation for texture classification". International Journal of Computer Vision. 127 (1): 74–109. arXiv:1801.10324. doi:10.1007/s11263-018-1125-z.
  • Liu, L.; Ouyang, W.; Wang, X.; Fieguth, P.; Chen, J.; Liu, X.; Pietikäinen, M. (2020). "Deep learning for generic object detection: A Survey". International Journal of Computer Vision. 128 (2): 261–318.
gollark: Nim bootstrapping continues to use 100% of the 1/4 of a CPU this instance gets.
gollark: Maybe I should have used one of the ARM instances.
gollark: It has MUCH economy somehow also.
gollark: The important thing to know about the UK is that it's like a monoid, in that it's often bad.
gollark: * image macrons

References
  1. "Center for Machine Vision and Signal Analysis". www.oulu.fi.
  2. "Infotech Oulu". www.oulu.fi.
  3. "CMV/25thAnniversaryBook - Center for Machine Vision and Signal Analysis". www.oulu.fi/cmvs.
  4. "Matti Pietikäinen - Google Scholar Citations". scholar.google.fi.
  5. IEEE Fellow Class of 2012 Archived 2013-09-23 at the Wayback Machine
  6. "IAPR - IAPR Fellows". www.iapr.org.
  7. "IAPR - King-Sun Fu Prize". www.iapr.org.
  8. "Highly Cited Researchers". hcr.clarivate.com. Archived from the original on 2019-02-20. Retrieved 2018-12-14.
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