Matt Turek

Matt Turek

Director of Computer Vision

Dr. Turek joined Kitware in September 2007 as a Research & Development Engineer. During his time at Kitware, Dr. Turek has worked on video activity recognition, normalcy modeling and anomaly detection, and functional recognition of scene elements. He has made significant contributions to DARPA programs, including Automated Wide-Area Activity Recognition (AWARE), Predictive Analysis for Naval Deployment Activities (PANDA), Building Labeling for Urban Environments and VIRAT.

Dr. Turek has over 10 years’ experience in imaging, computer vision, and visualization. His Ph.D. research focused on applying combinatorial optimization techniques to computer vision problems. In particular, Dr. Turek developed novel approaches for estimating motion under difficult lighting conditions; multiscale segmentation and motion estimation; and deformable multi-object tracking. Prior to completing his PhD, Dr. Turek worked on industrial imaging and medical imaging projects at GE Global Research (1999-2003) and at GE Healthcare (1995-1999).

Dr. Turek received his B.S. in Electrical Engineering from Clarkson University (1995), his M.S. in Electrical Engineering from Marquette University (1999) and his Ph.D. in Computer Science (2007) from Rensselaer Polytechnic Institute (RPI).

  1. M. Dawkins, A. Basharat, J. Becker, M. Turek, and A. Hoogs, "Deep Architecture for Small Mover Detection in Overhead Infrared Imagery," National Symposium on Sensor and Data Fusion (NSSDF), 2016.
  2. P. Tunison, M. Turek, and A. Hoogs, "Functional Scene Element modeling for ISR data," National Symposium on Sensor and Data Fusion (NSSDF), 2016.
  3. R. Mittu, J. Lin, Q. Li, Y. Gao, H. Rangwala, P. Shargo, J. Robinson, C. Rose, P. Tunison, M. Turek, S. Thomas, and P. Hanselman, "Foundations for Context-Aware Information Retrieval for Proactive Decision Support," SPIE Defense and Commercial Sensing Conference - Next Generation Analyst IV in SPIE, 2016.
  4. M. Turek et al., "Real-time, Full-frame Wide Area Motion Imagery Analytics," Military Sensing Symposium - Passive EO, 2015.
  5. A. Basharat, M. Turek, Y. Xu, C. Atkins, D. Stoup, K. Fieldhouse, P. Tunison, and A. Hoogs, "Real-time Multi-Target Tracking at 210 Megapixels/second in Wide Area Motion Imagery," IEEE Winter Conference on Applications of Computer Vision, 2014.
  6. K. Fieldhouse, M. J. Leotta, A. Basharat, R. Blue, D. Stoup, C. Atkins, L. Sherrill, B. Boeckel, P. Tunison, J. Becker, M. Dawkins, M. Woehlke, R. Collins, M. Turek, and A. Hoogs, KWIVER: An open source cross-platform video exploitation framework. IEEE, 2014, pp. 1-4.
  7. Z. H. Sun, M. Leotta, A. Hoogs, R. Blue, R. Neuroth, J. Vasquez, A. Perera, M. Turek, and E. Blasch., "Vehicle change detection from aerial imagery using detection response maps ," SPIE Defense+ Security, 2014, pp. 908906-908906.
  8. E. Swears, M. Turek, R. Collins, A. Perera, and A. Hoogs, "Automatic Activity Profile Generation from Detected Functional Regions for Video Scene Analysis," Video Analytics for Business Intelligence, Studies in Computational Intelligence, vol. 409, pp. 241-269, Jan. 2012.
  9. M. Turek et al., "Unsupervised Learning of Functional Categories in Video Scenes," European Conference on Computer Vision in Springer, 2010.
  10. S. Oh, A. Hoogs, M. Turek, and R. Collins, "Content-based Retrieval of Functional Objects in Video using Scene Context," European Conference on Computer Vision (ECCV), 2010.
  11. D. Freedman and M. Turek, "Graph cuts with many-pixel interactions: Theory and applications to shape modelling," Image and Vision Computing, vol. 28, no. 3, pp. 467-473, Mar. 2010.
  12. A. Enquobahrie, D. Gobbi, M. Turek, P. Cheng, Z. Yaniv, F. Lindseth, and K. Cleary, "Designing Tracking Software for Image-Guided Surgery Applications: IGSTK Experience," Int. Journal of Computer Assisted Radiology and Surgery. Springer, vol. 3, no. 5, pp. 395-403, Jan. 2008.
  13. M. Turek, "Combinatorial Optimization for Tracking and Low-level Computer Vision Problems,"Jul. 2007.
  14. M. Turek and D. Freedman, Multiscale Modeling and Constraints for Max-flow/Min-cut Problems in Computer Vision. 5th IEEE Computer Society Workshop on Perceptual Organization in Computer Vision, 2006.
  15. D. Freedman and M. W. Turek, "Illumination-invariant Tracking via Graph Cuts," IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2, pp. 10-17, Jan. 2005.
  16. P. R. S. Mendonça, D. R. Padfield, J. V. Miller, and M. Turek, "Bias in the Localization of Curved Edges," European Conference on Computer Vision (ECCV), vol. 2, pp. 554-565, Jan. 2004.
  17. H. Cline, C. Coulam, M. Yavuz, G. Rubin, P. Edic, T. Pan, Y. Shen, R. Avila, M. Turek, M. Iatrou, A. Loree, N. Ishaque, and R. Senzig, "Coronary Artery Angiography Using Multislice Computed Tomography Images," Circulation, vol. 102, pp. 1589, Jan. 2000.
  18. M. Turek, "Automated Segmentation and Visualization of the Left Ventricular Epicardium in Short Axis Cardiac Images Using MRI,"Aug. 1999.