EU

Meet the Team

Scott McCloskey, Ph.D.

Director of Computational Imaging

Company Leadership
Computer Vision

Kitware Minneapolis
Minneapolis, MN

Ph.D. in Computer Science
McGill University

M.S. in Computer Science
Rochester Institute of Technology

B.S. in Computer Science and Mathematics
University of Wisconsin

Dr. Scott McCloskey serves as an assistant director of the Computer Vision Team. Prior to joining Kitware, Dr. McCloskey was a technical fellow at Honeywell, where he served as the principal investigator (PI) on a number of commercial and contract-funded projects in computer vision and computational imaging. A theme of this work was the application of computational imaging techniques to a diverse set of sensing problems, including biometric (iris) image capture, barcode scanning, and media forensics. His government-funded work served customers, including DARPA, IARPA, and DoD agencies, which have since been incorporated into the Defense Forensics and Biometrics Agency (DFBA). Scott’s commercial work addressed problems in visual surveillance, biometrics, barcode scanning, and visual metrology. This last topic launched Honeywell’s AutoCube 8200 product, a structured light 3D camera whose associated software accurately measures parcels for postal and logistics customers. Scott’s work at Honeywell resulted in 40+ patents, in addition to the technical publications listed below.

Dr. McCloskey remains actively involved with technical conferences in the computer vision and computational imaging communities. He has served as general chair, program chair, and area chair for the IEEE Winter Conference on the Applications of Computer Vision (WACV); as the industrial relations chair, corporate relations chair, and area chair for the premier computer vision conferences including the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) and International Conference on Computer Vision (ICCV).  He was the workshops chair for the International Joint Conference on Biometrics (IJCB) and has been a reviewer for several other high-profile conferences, including the European Conference on Computer Vision (ECCV) and the Association for the Advancement of Artificial Intelligence (AAAI). He has also served as a reviewer for journals including IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), International Journal of Computer Vision (IJCV), Machine Vision and Applications (MVA), IEEE Transactions on Information Forensics and Security (TIFS), and served on a National Science Foundation review panel.

Dr. McCloskey received his Ph.D. in Computer Science from McGill University in 2008, his M.S. in computer science from the Rochester Institute of Technology in 2002, and his B.S. in computer science and mathematics from the University of Wisconsin – Madison in 1998.  Between his undergraduate and Ph.D., and in parallel with the completion of his M.S., Scott worked in the research laboratory at Eastman Kodak in Rochester, New York.  While at Kodak, he completed the Image Science Career Development program and contributed to computer vision projects in compression, remote sensing, and film scanning.

He has several research publications in the premier peer-reviewed conferences and journals. A list of his publications is provided below and on Google Scholar profile. 

Publications

  1. F. Yellin, S. McCloskey, C. Hill, E. Smith, and B. Clipp, "Concurrent Band Selection and Traversability Estimation from Long-Wave Hyperspectral Imagery in Off-Road Settings," in 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024. [URL]
  2. A. Mankowski, P. Gurram, J. Crall, S. McCloskey, and A. Hoogs, "Transformers for Small Object Detection and Tracking in OPIR Imagery," in Proceedings of the National Security Sensor and Data Fusion Committee, 2023.
  3. S. McCloskey, B. RichardWebster, R. Collins, and A. Hoogs, "Subject Identification up to 1km: Performer Perspective on the IARPA BRIAR Program," in Proceedings of the National Security Sensor and Data Fusion Committee (NSSDF), 2023.
  4. D. Davila, D. Du, B. Lewis, C. Funk, J. Van Pelt, R. Collins, K. Corona, M. Brown, S. McCloskey, A. Hoogs, and B. Clipp, "MEVID: Multi-view Extended Videos with Identities for Video Person Re-Identification," in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023. [URL]
  5. F. Yellin, E. Smith, M. Albright, and S. McCloskey, "Resolution Transfer for Object Detection from Satellite Imagery," in 2022 26th International Conference on Pattern Recognition (ICPR), 2022. [URL]
  6. S. McCloskey, "Computational Imaging," in Multimedia Forensics. Springer Singapore, 2022, pp. 41-62. [URL]
  7. W. Scheirer, R. VidalMata, S. Banerjee, B. RichardWebster, M. Albright, P. Davalos, S. McCloskey, B. Miller, A. Tambo, S. Ghosh, S. Nagesh, Y. Yuan, Y. Hu, J. Wu, W. Yang, X. Zhang, J. Liu, Z. Wang, H. Chen, T. Huang, W. Chin, Y. Li, M. Lababidi, and C. Otto, "Bridging the Gap Between Computational Photography and Visual Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1-1, 2020. [URL]
  8. S. McCloskey and M. Albright, "Detecting GAN-Generated Imagery Using Saturation Cues," in 2019 IEEE International Conference on Image Processing, 2019.
  9. N. Li, S. McCloskey, and J. Yu, "Jittered Exposures for Light Field Super-Resolution," in 2019 IEEE International Conference on Image Processing (ICIP), 2019.
  10. M. Albright and S. McCloskey, "Source generator attribution via inversion," CVPR Workshop on Media Forensics, pp. 96-103, May 2019.
  11. A. Tambo, M. Albright, and S. Mccloskey, "Low-and semantic-level cues for forensic splice detection," in 2019 IEEE Winter Conference on Applications of Computer Vision, 2019.
  12. C. Chen, S. McCloskey, and J. Yu, "Analyzing Modern Camera Response Functions," in 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 2019.
  13. J. Stanton, K. Hirakawa, and S. McCloskey, "Detecting Image Forgery Based On Color Phenomenology," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019.
  14. S. McCloskey and M. Albright, "Detecting gan-generated imagery using color cues," arXiv preprint arXiv:1812.08247, Dec. 2018.
  15. C. Chen, S. McCloskey, and J. Yu, "Focus manipulation detection via photometric histogram analysis," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018.
  16. N. Li, S. McCloskey, and J. Yu, "Jittered exposures for image super-resolution," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018.
  17. S. McCloskey and S. Venkatesha, "Temporally Coded Illumination for Rolling Shutter Motion De-blurring," in 2017 IEEE Winter Conference on Applications of Computer Vision, 2017.
  18. C. Chen, S. McCloskey, and J. Yu, "Image splicing detection via camera response function analysis," in Proceedings of the IEEE conference on computer vision and pattern recognition, 2017.
  19. S. McCloskey and B. Miller, "Fast, high dynamic range light field processing for pattern recognition," in 2016 IEEE International Conference on Computational Photography, 2016.
  20. S. McCloskey, "Application-driven computational imaging," in Micro-and Nanotechnology Sensors, Systems, and Applications VIII, 2016.
  21. B. Miller and S. McCloskey, "Metric Feature Indexing for Interactive Multimedia Search," in 2016 13th Conference on Computer and Robot Vision, 2016.
  22. S. McCloskey and S. Venkatesha, "Computational cameras for moving iris recognition," in Biometric and Surveillance Technology for Human and Activity Identification XII, 2015.
  23. S. McCloskey, S. Venkatesha, K. Muldoon, and R. Eckman, "A Low-Noise Fluttering Shutter Camera Handling Accelerated Motion," in 2015 IEEE Winter Conference on Applications of Computer Vision, 2015.
  24. X. Guo, H. Lin, Z. Yu, and S. McCloskey, "Barcode imaging using a light field camera," in European Conference on Computer Vision, 2014.
  25. S. McCloskey, "Improved motion invariant deblurring through motion estimation," in European Conference on Computer Vision, 2014.
  26. S. McCloskey, "11 Coded exposure motion deblurring for recognition," Motion Deblurring: Algorithms and Systems, pp. 222, May 2014.
  27. S. McCloskey and J. Liu, "Metadata-Weighted Score Fusion for Multimedia Event Detection," in 2014 Canadian Conference on Computer and Robot Vision, 2014.
  28. S. McCloskey, K. Muldoon, and S. Venkatesha, "Motion aware motion invariance," in 2014 IEEE International Conference on Computational Photography, 2014.
  29. R. Lloyd and S. McCloskey, "Recognition of 3D package shapes for single camera metrology," in IEEE Winter Conference on Applications of Computer Vision, 2014.
  30. C. Xiong, S. McCloskey, S. Hsieh, and J. Corso, "Latent domains modeling for visual domain adaptation," in Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014.
  31. S. Oh, S. Mccloskey, I. Kim, A. Vahdat, K. Cannons, H. Hajimirsadeghi, G. Mori, A. Perera, M. Pandey, and J. Corso, "Multimedia event detection with multimodal feature fusion and temporal concept localization," Machine vision and applications, vol. 25, no. 1, pp. 49-69, Jan. 2014.
  32. S. McCloskey, "Masking light fields to remove partial occlusion," in 2014 22nd International Conference on Pattern Recognition, 2014.
  33. S. Oh, A. Perera, I. Kim, M. Pandey, K. Cannons, H. Hajimirsadeghi, A. Vahdat, G. Mori, B. Miller, S. McCloskey, Y. Cheng, Z. Huang, C. Lee, C. Xu, R. Kumar, W. Chen, J. Corso, L. Fei-Fei, D. Koller, V. Ramanathan, K. Tang, A. Joulin, and A. Alahi, "Trecvid 2013 genie: Multimedia event detection and recounting," Parade, vol. 1, no. 26.0, pp. 51.7, Nov. 2013.
  34. S. McCloskey, "Velocity-dependent shutter sequences for motion deblurring," in European Conference on Computer Vision, 2012.
  35. J. Liu, S. McCloskey, and Y. Liu, "Local expert forest of score fusion for video event classification," in European Conference on Computer Vision, 2012.
  36. S. McCloskey and P. Davalos, "Activity detection in the wild using video metadata," in Proceedings of the 21st International Conference on Pattern Recognition, 2012.
  37. J. Liu, S. McCloskey, and Y. Liu, "Training data recycling for multi-level learning," in Proceedings of the 21st International Conference on Pattern Recognition, 2012.
  38. S. McCloskey, Y. Ding, and J. Yu, "Design and estimation of coded exposure point spread functions," IEEE transactions on pattern analysis and machine intelligence, vol. 34, no. 10, pp. 2071-2077, May 2012.
  39. A. Perera, S. Oh, M. P, T. Ma, A. Hoogs, A. Vahdat, K. Cannons, G. Mori, S. Mccloskey, B. Miller, S. Venkatesh, P. Davalos, P. Das, C. Xu, J. Corso, R. Srihari, I. Kim, Y. Cheng, Z. Huang, C. Lee, K. Tang, L. Fei-fei, and D. Koller, "TRECVID 2012 GENIE: multimedia event detection and recounting," in NIST TRECVID Workshop, 2012.
  40. S. McCloskey, "Temporally coded flash illumination for motion deblurring," in 2011 International Conference on Computer Vision, 2011.
  41. W. Xu and S. McCloskey, "2D Barcode localization and motion deblurring using a flutter shutter camera," in 2011 IEEE Workshop on Applications of Computer Vision (WACV), 2011.
  42. S. McCloskey, K. Muldoon, and S. Venkatesha, "Motion invariance and custom blur from lens motion," in 2011 IEEE International Conference on Computational Photography (ICCP), 2011.
  43. A. Perera, S. Oh, M. Leotta, I. Kim, B. Byun, C. Lee, S. McCloskey, B. Miller, Z. Huang, A. Vahdat, W. Yang, G. Mori, K. Tang, D. Koller, L. Fei-Fei, K. Li, G. Chen, J. Corso, Y. Fu, R. Srihari, Y. Fu, and R. Srihari, "GENIE TRECVID 2011 Multimedia Event Detection : Late-Fusion Approaches to Combine Multiple Audio-Visual features," in NIST TRECVID Workshop, 2011.
  44. S. McCloskey, W. Au, and J. Jelinek, "Iris capture from moving subjects using a fluttering shutter," in 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), 2010.
  45. Y. Ding, S. McCloskey, and J. Yu, "Analysis of motion blur with a flutter shutter camera for non-linear motion," in European Conference on Computer Vision, 2010.
  46. S. McCloskey, M. Langer, and K. Siddiqi, "Removal of partial occlusion from single images," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 3, pp. 647-654, Oct. 2010.
  47. S. McCloskey, M. Langer, and K. Siddiqi, "Removing partial occlusion from blurred thin occluders," in 2010 20th International Conference on Pattern Recognition, 2010.
  48. A. Kembhavi, B. Siddiquie, R. Miezianko, S. McCloskey, and L. Davis, "Incremental multiple kernel learning for object recognition," in 2009 IEEE 12th International Conference on Computer Vision, 2009.
  49. S. McCloskey and M. Langer, "Planar orientation from blur gradients in a single image," in 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009.
  50. A. Kembhavi, B. Siddiquie, R. Miezianko, S. McCloskey, and L. Davis, "Scene it or not? incremental multiple kernel learning for object detection," in Proceedings of the International Conference on Computer Vision, 2009.
  51. S. McCloskey, "Confidence weighting for sensor fingerprinting," in 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008.
  52. S. McCloskey, M. Langer, and K. Siddiqi, "Automated removal of partial occlusion blur," in Asian Conference on Computer Vision, 2007.
  53. S. McCloskey, M. Langer, and K. Siddiqi, "Evolving measurement regions for depth from defocus," in Asian Conference on Computer Vision, 2007.
  54. S. McCloskey, M. Langer, and K. Siddiqi, "The Reverse Projection Correlation Principle for Depth from Defocus," in Third International Symposium on 3D Data Processing, Visualization, and Transmission, 2006.
  55. S. McCloskey, M. Langer, and K. Siddiqi, "Seeing around occluding objects," in 18th International Conference on Pattern Recognition, 2006.
  56. S. McCloskey, "Hiding information in images: an overview of watermarking," Cryptography Research Paper, pp. 9-11, 2000.

Bibliography generated 2024-08-30-11:00:05 (7201)

Recent Posts by Scott McCloskey

See More
International Conference on Computational Photography (ICCP) 2024
International Conference on Computational Photography (ICCP)…
June 24, 2024  •   By Brandon Adamczyk and…
Computer Vision and Pattern Recognition Conference 2024. June 17-21.
Computer Vision and Pattern Recognition Conference 2024
May 21, 2024  •   By Anthony Hoogs, Scott…
SPIE, Defense, Commercial Sensing
SPIE Defense + Commercial Sensing 2024
April 18, 2024  •   By Anthony Hoogs, Scott…