Anthony Hoogs

Anthony Hoogs

Senior Director of Computer Vision

Dr. Hoogs leads Kitware’s Computer Vision group, which he founded when he joined Kitware in 2007. For more than two decades, he has supervised and performed research in various areas of computer vision including: event, activity and behavior recognition; motion pattern learning and anomaly detection; tracking; visual semantics; image segmentation; object recognition; and content-based retrieval. He has led dozens of projects, sponsored by commercial companies and government entities including DARPA, AFRL, ONR, I-ARPA and NGA, that range from basic, academic research to developing advanced prototypes and demonstrations installed at operational facilities, with a combined value exceeding $60M.

Dr. Hoogs supervises the Kitware Computer Vision group and provides strategic direction in this area. He has been the overall Principal Investigator on large DARPA programs including Media Forensics, Squad-X Core technologies, the Persistent Stare Exploitation and Analysis System and the Video and Image Retrieval and Analysis Toolkit. On these and similar efforts he was responsible for overseeing collaborations with more than 25 universities and 10 commercial subcontractors. At GE Global Research (1998-2007), Dr. Hoogs led a team of researchers in video and imagery analysis on projects sponsored by the US Government, Lockheed Martin and NBC Universal. His government-sponsored projects there included Video Analysis and Content Extraction (I-ARPA) and Dynamic Database (DARPA).

Dr. Hoogs received a Ph.D. in Computer and Information Science from the University of Pennsylvania in 1998; an M.S. from the University of Illinois at Urbana-Champaign in 1991; and a B.A. magna cum laude from Amherst College in 1989. He has published more than 80 papers in computer vision, pattern recognition, artificial intelligence and remote sensing. His academic service includes: General Co-Chair for the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017; General Co-Chair for the IEEE Winter conference on Applications of Computer Vision (WACV) 2016 and 2018; Area Chair for CVPR (2009, 2010, 2012, 2018); Workshops Co-Chair for CVPR (2012); Corporate Relations Chair for CVPR (2009, 2010) and the International Conference on Computer Vision (2013); program Co-Chair for WACV (2009, 2011); co-chair of the IEEE Workshop on Activity Recognition (2011) at CVPR; organizer and co-chair of the IEEE Workshop on Perceptual Organization in Computer Vision (2004) at CVPR; organizer and co-chaired of the IEEE International Workshop on Semantic Knowledge in Computer Vision (2005) at ICCV; member of the Computer Vision Foundation Advisory Board and Industrial Advisory Board; member of the Steering Committee for WACV. He regularly serves on program committees for the primary computer vision and AI conferences and workshops (ICCV, CVPR, ECCV, WACV, AVSS, AAAI) and is a reviewer for premier journals in computer vision.

He has served on technical panels for NSF and DARPA, including DARPA Information Science and Technology (ISAT) panels in 2007, 2009 and 2013 and has recently started a 3-year term as an ISAT member. In 2014 he served as an organizer of the National Academies National Research Council Workshop on Robust Methods for the Analysis of Images and Videos for Fisheries Stock Assessment, sponsored by NOAA, then joined the NOAA Automated Imagery Analysis Strategic Initiative Steering Committee.

  1. M. Dawkins, L. Sherrill, K. Fieldhouse, A. Hoogs, D. Zhang, L. Prasad, and B. Richards, "An open-source platform for underwatch image and video analytics," in IEEE Winter Conference on Applications of Computer Vision, 2017.
  2. M. Dawkins, A. Basharat, J. Becker, M. Turek, and A. Hoogs, "Deep architecture for small mover detection in overhead infrared imagery," in National Symposium on Sensor and Data Fusion (NSSDF), 2016.
  3. P. Tunison, M. Turek, and A. Hoogs, "Functional scene element modeling for isr data," in National Symposium on Sensor and Data Fusion (NSSDF), 2016.
  4. A. Hoogs et al., "An end-to-end system for content-based video retrieval using behavior, actions, and appearance with interactive query refinement," in 12th IEEE International Conference on Advanced Video and Signal-based Surveillance, Karlsruhe, Germany, 2015.
  5. M. Turek, A. Basharat, K. Fieldhouse, P. Tunison, D. Stoup, C. Atkins, and A. Hoogs, "Real-time, full-frame wide area motion imagery analytics," in Military Sensing Symposium - Passive EO, 2015.
  6. 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," in IEEE Winter Conference on Applications of Computer Vision, 2014.
  7. E. Swears, A. Hoogs, Q. Ji, and K. Boyer, "Complex activity recognition using granger constrained dbn (gcdbn) in sports and surveillance video," in IEEE Computer Vision and Pattern Recognition Columbus Oh., 2014.
  8. E. Swears, A. Hoogs, and k. Boyer, "Pyramid coding for functional scene element recognition in video scenes," in CVPR Workshop on Scene Understanding, 2014.
  9. E. Swears, A. Basharat, A. Hoogs, and E. Blasch, "Probabilistic sub-graph matching (pgram) for video and text fusion," in MSS National Symposium on Sensor and Data Fusion (NSSDF), 2014.
  10. 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," p. 1–4, Jan. 2014.
  11. M. Dawkins, A. Perera, and A. Hoogs, "Real-time heads-up display detection in video," in IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), 2014.
  12. M. Dawkins and A. Hoogs, "Automatic image-plane aligned obstruction detection in eo and ir video," in MSS Passive Sensors, 2014.
  13. M. Dawkins, Z. Sun, A. Basharat, A. Perera, and A. Hoogs, "Tracking nautical objects in real-time via layered saliency detection," in SPIE Defense, Security, and Sensing (DSS), 2014.
  14. S. Oh, M. Pandey, I. Kim, A. Hoogs, and J. Baumes, "Personalized economy of images in social forums: an analysis on supply, consumption, and saliency," in International Conference on Pattern Recognition, 2014.
  15. Y. Xu, A. Basharat, J. Becker, and A. Hoogs, "Complex algorithm optimization through probabilistic search of its configuration tree," in IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), 2014.
  16. Y. Xu, D. Song, and A. Hoogs, "An efficient online hierarchical supervoxel segmentation algorithm for time-critical applications," in British Machine Vision Conference (BMVC), 2014.
  17. 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," in SPIE Defense+ Security, 2014, p. 908906–908906.
  18. E. Swears, A. Hoogs, and K. Boyer, "Pyramid coding for functional scene element recognition in video scenes," in IEEE International Conference on Computer Vision, 2013.
  19. E. Swears, A. Hoogs, and R. Blue, "Recognizing activity based scene elements in video," in Automatic Target Recognition Working Group, 2013.
  20. Y. Xu, S. Oh, and A. Hoogs, "A minimum error vanishing point detection approach for uncalibrated monocular images of man-made environments," in IEEE Conference on Computer Vision and Pattern Recognition, 2013.
  21. Y. Xu, S. Oh, F. Yang, Z. Jiang, N. Cuntoor, A. Hoogs, and L. Davis, "System and algorithms on detection of objects embedded in perspective geometry using monocular cameras," in International Conference on Advanced Video and Signal-Based Surveillance, 2013.
  22. A. G. Perera, S. Oh, M. Pandey, T. Ma, A. Hoogs, A. Vahdat, K. Cannons, H. Hajimirsadeghi, 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, F. Li, and D. Koller, "Trecvid 2012 genie: multimedia event detection and recounting," in TRECVID Workshop, 2012.
  23. E. Swears and A. Hoogs, "Learning and recognizing complex multi-agent activities with applications to american football plays," in Workshop on the Applications of Computer Vision , 2012.
  24. 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, p. 241–269, Jan. 2012.
  25. K. K. Reddy, N. Cuntoor, A. Perera, and A. Hoogs, "Human action recognition in large-scale datasets using histogram of spatiotemporal gradients," in IEEE International Conference on Advanced Video and Signal-Based Surveillance, 2012.
  26. N. Cuntoor, R. Collins, and A. Hoogs, "Human-robot teamwork using activity recognition and human instruction," in IEEE Intl. Conf. Intelligent Robots and Systems (IROS), 2012.
  27. E. Swears and A. Hoogs, "Complex activity recognition using granger constrained dynamic bayesian network," in Learning Workshop, Fort Lauderdale Florida, 2011.
  28. S. Oh, A. Hoogs, A. Perera, N. Cuntoor, C. chen, J. Lee, S. Mukherjee, J. K. Aggarwal, H. Lee, L. Davis, E. Swears, X. Wang, Q. Ji, K. Reddy, M. Shah, C. Vondrick, H. Pirsiavash, D. Ramanan, J. Yuen, A. Torralba, B. Song, A. Fong, A. Roy-Chowdhury, and M. Desai, "A large-scale benchmark dataset for event recognition in surveillance video," in IEEE Computer Vision and Pattern Recognition (CVPR), 2011, p. 3153–3160.
  29. M. Turek, A. Hoogs, and R. Collins, "Unsupervised learning of functional categories in video scenes," in European Conference on Computer Vision (ECCV), 2010.
  30. N. Cuntoor, A. Basharat, A. Perera, and A. Hoogs, "Track initialization in low frame rate and low resolution videos," in International Conference on Pattern Recognition (ICPR), 2010.
  31. S. Oh and A. Hoogs, "Unsupervised learning of activities in video using scene context," in International Conference on Pattern Recognition (ICPR), 2010.
  32. S. Oh, A. Hoogs, M. Turek, and R. Collins, "Content-based retrieval of functional objects in video using scene context," in European Conference on Computer Vision (ECCV), 2010.
  33. Z. Sun and A. Hoogs, "Image comparison by compound disjoint information with applications to perceptual visual quality assessment, image registration and tracking," International Journal of Computer Vision, vol. 88, no. 3, p. 461–488, Jul. 2010.
  34. E. Swears and A. Hoogs, "Functional scene element recognition for video scene analysis," in Workshop on Motion and Video Computing, 2009.
  35. A. G. A. Perera, R. Collins, and A. Hoogs, "Evaluation of compression schemes for wide area video," in Applied Imagery and Pattern Recognition Workshop (ICPR), 2008.
  36. A. Hoogs et al., "Detecting semantic group activities using relational clustering," in Workshop on Motion and Video Computing, 2008.
  37. E. Swears, A. Hoogs, and A. G. A. Perera, "Learning motion patterns in surveillance video using hmm clustering," in Workshop on Motion and Video Computing, 2008.
  38. A. Hoogs and A. G. Perera, "Video activity recognition in the real world," in National Conference on Artificial Intelligence, 2008, p. 1551–1554.
  39. 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, p. 199–217, May 2008.
  40. F. W. Wheeler and A. Hoogs, "Moving vehicle registration and super-resolution," in Applied Imagery and Pattern Recognition Workshop, 2007.
  41. A. G. Perera, A. Hoogs, C. Srinivas, G. Brooksby, and W. Hu, "Evaluation of algorithms for tracking multiple objects in video," in Workshop on Applied Imagery and Pattern Recognition, 2006.
  42. A. G. Perera, C. Srinivas, A. Hoogs, G. Brooksby, and W. Hu, "Multi-object tracking through simultaneous long occlusions and split-merge conditions," in Conference on Computer Vision and Pattern Recognition, 2006, p. 666–673.
  43. A. Hoogs and R. Collins, "Object boundary detection in images using a semantic ontology," in National Conference on Artificial Intelligence, 2006, p. 956–957.
  44. A. Perera, G. Brooksby, A. Hoogs, and G. Doretto, "Moving object segmentation using scene understanding," in Workshop on Perceptual Organization in Computer Vision, 2006.
  45. Z. Sun and A. Hoogs, "Image comparison by compound disjointed information," in IEEE Conference on Computer Vision and Pattern Recognition, 2006, p. 857–862 .
  46. J. Kaufhold, R. Collins, A. Hoogs, and P. Rondot, "Recognition and segmentation of scene content using region-based classification," in 18th International Conference on Pattern Recognition, 2006.
  47. M. T. Chan, A. Hoogs, R. Bhotika, A. G. Perera, J. Schmiederer, and G. Doretto, "Joint recognition of complex events and track matching," in Conference on Computer Vision and Pattern Recognition, 2006, p. 1615–1622.
  48. M. T. Chan, A. Hoogs, Z. Sun, J. Schmiederer, R. Bhotika, and G. Doretto, "Event recognition with fragmented object tracks," in IEEE International Conference on Pattern Recognition, 2006, p. 412–416.
  49. A. Hoogs et al., "Recognizing complex behaviors in aerial video," in International Conference on Intelligence Analysis, 2005.
  50. R. Kaucic, A. G. Perera, G. Brooksby, J. P. Kaufhold, and A. Hoogs, "A unified framework for tracking through occlusions and across sensor gaps," in Conference on Computer Vision and Pattern Recognition, 2005, p. 990–997.
  51. A. G. Perera and A. Hoogs, "Bayesian object-level change detection in grayscale imagery," in 17th International Conference on Pattern Recognition, 2004, p. 71–75.
  52. J. P. Kaufhold and A. Hoogs, "Learning to segment images using region-based perceptual features," in Conference on Computer Vision and Pattern Recognition, 2004, p. 954–961.
  53. M. T. Chan, A. Hoogs, J. Schmiederer, and M. Petersen, "Detecting rare events in video using semantic primitives with hmm," in 17th International Conference on Pattern Recognition, 2004, p. 150–154.
  54. A. Hoogs et al., "A common set of perceptual observables for grouping, figure-ground discrimination and texture classification," Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 25, p. 458–474, Apr. 2003.
  55. G. Stein, J. Rittscher, and A. Hoogs, "Enabling video annotation using a semantic database extended with visual knowledge," in International Conference on Multimedia and Expo, 2003.
  56. J. Rittscher, A. Blake, A. Hoogs, and G. Stein, "Mathematical modeling of animate and intentional motion," Philosophical Transactions of the Royal Society of London: Biological Sciences, vol. 1431, no. 358, p. 475–490, Feb. 2003.
  57. A. Hoogs et al., "Video content annotation using visual analysis and large semantic knowledgebase," in Conference on Computer Vision and Pattern Recognition, 2003, p. 327–334.
  58. A. Hoogs et al., "Classification of 3d macro texture using perceptual observables," in International Conference on Pattern Recognition, 2002, p. 113–117.
  59. A. Hoogs et al., "Using video for recovering texture," in Workshop on Applied Imagery and Pattern Recognition, 2001.
  60. A. Hoogs et al., "Multi-modal fusion for video understanding," in Workshop on Applied Imagery and Pattern Recognition, 2001, p. 103–108.
  61. A. Hoogs and J. Mundy, "Information fusion for eo object detection and delineation," in National Symposium on Sensor and Data Fusion, 2000.
  62. A. Hoogs and J. L. Mundy, "An integrated boundary and region approach to perceptual grouping," in International Conference on Pattern Recognition, 2000, p. 284–290.
  63. A. Hoogs and J. L. Mundy, "Rapid data reduction and target detection in literal imagery," in Workshop on Applied Imagery and Pattern Recognition, 2000, p. 129–135.
  64. A. Hoogs and J. Mundy, "Segmentation and geometry: an integrated representation," in Workshop on the Integration of Appearance and Geometric Methods in Object Recognition, 1999.
  65. J. Mundy and A. Hoogs, "Data representations for object-level change detection in eo/ir imagery," in National Symposium on Sensor and Data Fusion, 1999.
  66. A. Hoogs et al., "Image understanding at lockheed martin management and data systems," in DARPA Image Understanding Workshop, 1998, p. 703–718.
  67. A. Hoogs, "Radius: imagery understanding for imagery intelligence," RADIUS, Jul. 1997.
  68. A. Hoogs, "Combining geometric and appearance models for change detection," in DARPA Image Understanding Workshop, 1997, p. 565–576.
  69. A. Hoogs et al., "The radius phase ii program," in DARPA Image Understanding Workshop, 1997, p. 381–400.
  70. A. Hoogs et al., "Image understanding at lockheed martin valley forge," in DARPA Image Understanding Workshop, 1997, p. 455–464.
  71. M. Puscar and A. Hoogs, "User interface representations for image understanding," in DARPA Image Understanding Workshop, 1997, p. 607–614.
  72. A. Hoogs, "Analysis of learning using segmentation models," in Conference on Computer Analysis of Images and Patterns, 1997, p. 645–652.
  73. A. Hoogs, "Pose adjustment using a parameter hierarchy," in ARPA Image Understanding Workshop, 1996, p. 857–865.
  74. A. Hoogs and R. Bajcsy, "Model-based learning of segmentations," in International Conference on Pattern Recognition, 1996, p. 494–499.
  75. B. Bremner, A. Hoogs, and J. Mundy, "Integration of image understanding exploitation algorithms in the radius testbed," in ARPA Image Understanding Workshop, 1996, p. 255–268.
  76. B. Kniffin and A. Hoogs, "Database support for exploitation image understanding," in ARPA Image Understanding Workshop, 1996, p. 421–428.
  77. R. Cardenas and A. Hoogs, "The radius testbed database: temporal queries and optimization," in SPIE Workshop on Applied Imagery and Pattern Recognition, 1996.
  78. A. Hoogs, "Object position refinement using hierarchical search," in SPIE Workshop on Applied Imagery and Pattern Recognition, 1995, p. 152–162.
  79. A. Hoogs and R. Bajcsy, "Using scene context to model segmentations," in Workshop on Context-Based Vision, 1995, p. 50–61.
  80. B. Kniffin and A. Hoogs, "Combining database support for image understanding and model-supported exploitation," in SPIE Workshop on Applied Imagery and Pattern Recognition, 1995, p. 146–152.
  81. A. Hoogs and R. Bajcsy, "Segmentation modeling," in Conference on Computer Analysis of Images and Patterns, 1995, p. 808–813.
  82. A. Hoogs and B. Kniffin, "The radius testbed database: issues and design," in ARPA Image Understanding Workshop, 1994, p. 269–276.
  83. A. Hoogs and D. Hackett, "Model-supported exploitation as a framework for image understanding," in ARPA Image Understanding Workshop, 1994, p. 265–268.
  84. R. Bajcsy and A. Hoogs, "Segmentation characterization for change detection," in ARPA Image Understanding Workshop, 1994, p. 1555–1562.
  85. J. Mundy, R. Welty, L. Quam, T. Strat, W. Bremner, M. Horwedel, D. Hackett, and A. Hoogs, "The radius common development environment," in DARPA Image Understanding Workshop, 1992.
  86. J. Ponce, A. Hoogs, and D. Kriegman, "On using cad models to compute the pose of curved 3d objects," CVGIP: Image Understanding, vol. 55, no. 2, p. 184–197, Jan. 1992.
  87. J. Ponce, A. Hoogs, and D. Kriegman, "On using cad models to compute the pose of curved 3d objects," in Workshop on Directions in Automated CAD-Based Vision, 1991.