Peter Tu image

Peter Tu

PhD, Engineering Science (Oxford University) BS, Systems Design Engineering (University of Waterloo)

In 1990 Dr. Tu joined Sony Research in Tokyo Japan, where he developed a number of computer vision algorithms for man-machine interfaces. While at Oxford University, his research was devoted to the development of computer vision methods for the automatic analysis of seismic imagery.

In 1997 Dr. Tu became a senior research scientist working at GE Research. In partnership with Lockheed Martin, he developed a set of latent fingerprint matching algorithms for the FBI Automatic Fingerprint Identification System (AFIS). Dr. Tu has also developed optical methods for the precise measurement of 3D parts in a manufacturing setting.

Dr. Tu was the principal investigator for the FBI ReFace project, which is tasked with developing an automatic system for face reconstruction from skeletal remains. In 2006, he was the principal investigator for the National Institute of Justice’s 3D Face Enhancer Program. This work was focused on improving face recognition from poor quality surveillance video.

In 2008, Dr Tu led the GE video analytics team that participated in the DHS STIDP demonstration program - the goal of STIDP is to establish an effective defense against suicide bomber attacks.

Dr Tu is the principal investigator for the DARPA-sponsored effort associated with group level behavior recognition at a distance. Currently Dr. Tu is GE’s Chief Scientist for Artificial Intelligence at GE Research. He has helped to develop a large number analytic capabilities including: person detection from fixed and moving platforms, crowd segmentation, multi-view tracking, person reacquisition, face modeling, face expression analysis, face recognition at a distance, face verification from photo IDs and articulated motion analysis. Dr Tu has over 50 peer reviewed publications and has filed more than 50 U.S. patents.

Never before have I been a part of such a dedicated, collaborative effort, spanning such a large portion of the company. It’s truly an amazing time to be working on next-generation materials.

Joseph Vinciquerra, GE Research
Publications
  1. Yang, Y., Chang, M.C., Tu, P. and Lyu, S., 2015, September. Seeing as it happens: Real time 3D video event visualization. In 2015 IEEE International Conference on Image Processing (ICIP) (pp. 2875-2879). IEEE.
  2. Tu, P., Chang, M.C. and Gao, T., 2016, December. Crowd analytics via one shot learning and agent based inference. In 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP) (pp. 1181-1185). IEEE.
  3. Chen, J., Chang, M.C., Tian, T.P., Yu, T. and Tu, P., 2015, September. Bridging computer vision and social science: a multi-camera vision system for social interaction training analysis. In Image Processing (ICIP), 2015 IEEE International Conference on (pp. 823-826). IEEE.
  4. Chen, J., Chang, M.C. and Tu, P., 2015, May. A live video analytic system for affect analysis in public space. In Automatic Face and Gesture Recognition (FG), 2015 11th IEEE International Conference and Workshops on (Vol. 1, pp. 1-1). IEEE.
  5. Chen, J., Liu, X., Tu, P. and Aragones, A., 2012, September. Person-specific expression recognition with transfer learning. In 2012 19th IEEE International Conference on Image Processing (pp. 2621-2624). IEEE.
  6. Chen, J., Liu, X., Tu, P. and Aragones, A., 2013. Learning person-specific models for facial expression and action unit recognition. Pattern Recognition Letters, 34(15), pp.1964-1970.
  7. Chen, J., Chang, M.C. and Tu, P., 2015, May. A live video analytic system for affect analysis in public space. In 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG) (Vol. 1, pp. 1-1). IEEE.
  8. Tu, P., Sebastian, T., Doretto, G., Krahnstoever, N., Rittscher, J. and Yu, T., 2008, October. Unified crowd segmentation. In European conference on computer vision (pp. 691-704). Springer, Berlin, Heidelberg.
  9. Tu, P., Yu, T., Gao, D., Nevatia, R., Lee, S.C., Kim, H., Rhee, P.K. and Baek, J.H., 2012, January. A systems level approach to perimeter protection. In 2012 IEEE Workshop on the Applications of Computer Vision (WACV) (pp. 257-262). IEEE.
  10. Tu, P., Chen, J., Chang, M.C., Yu, T., Tian, T.P., Rubin, G., Hockett, J. and Logan-Terry, A., 2015. Cross-cultural training analysis via social science and computer vision methods. Procedia Manufacturing, 3, pp.4068-4075.

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