Roddy Collins, Ph.D.

Principal Engineer

Computer Vision

Kitware New York
Clifton Park, NY

10 Years Service at Kitware

Ph.D. in Computer Science
Rensselaer Polytechnic Institute

M.S. in Computer Science
Rensselaer Polytechnic Institute

B.S. in Computer Science
University of Virginia

Roddy Collins

Roddy Collins, Ph.D., is a principal engineer on Kitware’s Computer Vision (CV) Team located in Clifton Park, New York. For over 20 years, he has collaborated in research programs across various areas of computer vision. These areas include activity detection, dataset development, object-level change detection, applications of scene content analysis to object tracking, object segmentation via semantic ontologies, motion pattern learning and anomaly detection, and optical metrology. In addition to his funded projects, Roddy developed and maintains the evaluation and metrics systems for the CV Team.

Since joining Kitware, Roddy served as principal investigator for the Intelligence Advanced Research Projects Activity (IARPA) Deep Intermodal Video Analytics (DIVA) program, Defense Advanced Research Projects Agency (DARPA) Probabilistic Programming for Advancing Machine Learning (PPAML) and Explainable AI (XAI) programs, and Air Force Research Laboratory (AFRL) Hierarchical Dynamic Exploitation of FMV (full-motion video), or HiDEF, program. He was also a lead architect of the DARPA Video and Image Retrieval and Analysis Tool (VIRAT) system. Roddy has also contributed to numerous other projects for DARPA, IARPA, the Army Research Laboratory (ARL), the Combat Capabilities Development Command (DEVCOM), and AFRL.

Roddy has co-authored papers that have been published in the IEEE Transactions on Pattern Analysis and Machine Intelligence and the International Journal of Computer Vision. His conference publications include papers at the Association for the Advancement of Artificial Intelligence Conference (AAAI), Winter Conference Applications of Computer Vision (WACV), Advanced Video and Signal Based Surveillance (AVSS), and the International Conference on Pattern Recognition (ICPR). He has also reviewed papers for AAAI, Computer Vision and Pattern Recognition (CVPR), Communication Networks and Services Research (CNSR), and Machine Vision Applications (ICMVA).

Before joining Kitware in 2007, Roddy worked at the Visualization and Computer Vision Lab at the General Electric Co. Global Research Center. At GE, he earned two patents while working on projects in optical metrology, object-level change detection and object tracking, and watermarking in digital media.

Roddy received his Ph.D. in computer science from Rensselaer Polytechnic Institute. During this time, he researched reformulating the debugging process to show how semantic constraints can be evaluated in a reference implementation of a target semantic domain that can, in turn, be coupled to diverse, independently-developed target programs. He was also a member of the Computer Science Department’s system administration team. Roddy received his master’s degree in computer science from Rensselaer Polytechnic Institute and his bachelor’s degree in computer science from the University of Virginia.

Publications

  1. 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.
  2. 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]
  3. B. Ravichandran, R. Collins, K. Fieldhouse, K. Corona, and A. Hoogs, "From Leaderboard To Operations: DIVA Transition Experiences," in 2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), 2022. [URL]
  4. B. Hu, P. Tunison, B. Vasu, N. Menon, R. Collins, and A. Hoogs, "XAITK: The explainable AI toolkit," Applied AI Letters, Oct. 2021. [URL]
  5. B. Vasu, B. Hu, B. Dong, R. Collins, and A. Hoogs, "Explainable, interactive content‐based image retrieval," Applied AI Letters, Nov. 2021. [URL]
  6. K. Corona, K. Osterdahl, R. Collins, and A. Hoogs, "MEVA: A Large-Scale Multiview, Multimodal Video Dataset for Activity Detection," in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2021. [URL]
  7. B. Vasu, J. Barnett, R. Collins, and A. Hoogs, "Explainability for Content-Based Image Retrieval," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2019.
  8. B. Dong, R. Collins, and A. Hoogs, "Explainability for Content-Based Image Retrieval," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop on Explainable Artificial Intelligence (AI), 2019.
  9. D. Chittajallu, B. Dong, P. Tunison, R. Collins, K. Wells, J. Fleshman, G. Sankaranarayanan, S. Schwaitzberg, L. Cavuoto, and A. Enquobahrie, "XAI-CBIR: Explainable AI System for Content based Retrieval of Video Frames from Minimally Invasive Surgery Videos," in 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 2019. [URL]
  10. C. Long, R. Collins, E. Swears, and A. Hoogs, "Deep Neural Networks In Fully Connected CRF For Image Labeling With Social Network Metadata," in Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV), 2019.
  11. R. Collins, K. Osterdahl, A. Shringi, K. Corona, R. Meth, and A. Hoogs, "Data, Algorithms, and Framework for Automated Analytics of Surveillance Camera Networks," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2018. [URL]
  12. R. Porter, A. Basharat, R. Collins, M. Turek, and A. Hoogs, "Training and evaluating object detection pipelines with connected components," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2016. [URL]
  13. A. Hoogs, A. Perera, R. Collins, A. Basharat, K. Fieldhouse, C. Atkins, L. Sherrill, B. Boeckel, R. Blue, M. Woehlke, C. Greco, Z. Sun, E. Swears, N. Cuntoor, J. Luck, B. Drew, D. Hanson, D. Rowley, J. Kopaz, T. Rude, D. Keefe, A. Srivastava, S. Khanwalkar, A. Kumar, C. Chen, J. Aggarwal, L. Davis, Y. Yacoob, A. Jain, D. Liu, S. Chang, B. Song, A. Roy-Chowdhury, K. Sullivan, J. Tesic, S. Chandrasekaran, B. Manjunath, X. Wang, Q. Ji, K. Reddy, J. Liu, M. Shah, K. Chang, T. Chen, and M. Desai, "An end-to-end system for content-based video retrieval using behavior, actions, and appearance with interactive query refinement," in Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2015. [URL]
  14. K. Fieldhouse, M. 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," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2014. [URL]
  15. N. Cuntoor, R. Collins, and A. Hoogs, "Human-robot teamwork using activity recognition and human instruction," in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012. [URL]
  16. E. Swears, M. Turek, R. Collins, A. Perera, and A. Hoogs, "Automatic activity profile generation from detected functional regions for video scene analysis," in Video Analytics for Business Intelligence. Springer, 2012, pp. 241-269. [URL]
  17. M. Turek, A. Hoogs, and R. Collins, "Unsupervised Learning of Functional Categories in Video Scenes," in Proceedings of the European Conference on Computer Vision, 2010. [URL]
  18. S. Oh, A. Hoogs, M. Turek, and R. Collins, "Content-Based Retrieval of Functional Objects in Video Using Scene Context," in Proceedings of the European Conference on Computer Vision, 2010. [URL]
  19. A. Perera, R. Collins, and A. Hoogs, "Evaluation of compression schemes for wide area video," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2008. [URL]
  20. K. Barnard, Q. Fan, R. Swaminathan, A. Hoogs, R. Collins, P. Rondot, and J. Kaufhold, "Evaluation of localized semantics: data, methodology, and experiments," International Journal of Computer Vision, vol. 77, no. 1, pp. 199-217, May 2008. [URL]
  21. E. Blasch, H. Ling, D. Shen, G. Chen, R. Hammound, A. Basharat, R. Collins, A. Aved, and J. Nagy, "Video-to-text information fusion evaluation for level 5 user refinement," in 2015 18th International Conference on Information Fusion (Fusion), 2006.
  22. J. Kaufhold, R. Collins, A. Hoogs, and P. Rondot, "Recognition and Segmentation of Scene Content using Region-Based Classification," in Proceedings of the IEEE International Conference on Pattern Recognition, 2006. [URL]
  23. N. Krahnstoever, P. Tu, T. Sebastien, A. Perera, and R. Collins, "Multi-View Detection and Tracking of Travelers and Luggage in Mass Transit Environments," in IEEE Workshop on Performance Evaluation for Tracking and Surveillance, 2006.
  24. A. Hoogs and R. Collins, "Object Boundary Detection in Images using a Semantic Ontology," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2006. [URL]
  25. R. Collins, "Restoring Semantic Context: A Domain-Aware Debugger," Ph.D. dissertation, Rensselaer Polytechnic Institute, 2004.
  26. A. Hoogs, R. Collins, R. Kaucic, and J. Mundy, "A common set of perceptual observables for grouping, figure-ground discrimination, and texture classification," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 4, pp. 458-474, Apr. 2003. [URL]
  27. A. Hoogs, R. Collins, and R. Kaucic, "Classification of 3D macro texture using perceptual observables," in Proceedings of the IEEE International Conference on Pattern Recognition, 2002. [URL]
  28. A. Hoogs, R. Kaucic, and R. Collins, "Using video for recovering texture," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2001. [URL]

Bibliography generated 2023-11-04-15:30:04 (6367)