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.

A list of Dr. Hoog’s publications is featured below. For a list of all computer vision publications, please see the Computer Vision Publications page.

  1. Z. Sun and A. Hoogs, "Compact image representation by binary component analysis," in Proceedings of the IEEE International Conference on Image Processing, 2017. [URL]
  2. E. Wengrowski, Z. Sun, and A. Hoogs, "Reflection correspondence for exposing photograph manipulation," in Proceedings of the IEEE International Conference on Image Processing, 2017. [URL]
  3. M. Dawkins, L. Sherrill, K. Fieldhouse, A. Hoogs, B. Richards, D. Zhang, L. Prasad, K. Williams, N. Lauffenburger, and G. Wang, "An open-source platform for underwater image and video analytics," in Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2017. Winner, Best Paper Honorable Mention. [URL]
  4. C. Long, E. Smith, A. Basharat, and A. Hoogs, "A C3D-based convolutional neural network for frame dropping detection in a single video shot," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop on Media Forensics, 2017. [URL]
  5. Z. Sun and A. Hoogs, "Object insertion and removal in images with mirror reflection," in Proceedings of the IEEE Workshop on Information Forensics and Security, 2017. [URL]
  6. K. Fieldhouse, A. Hoogs, and E. Swears, "Linking Unmanned Systems, Visible and IR Video, Computer Vision, and Humans Together for Real-Time, Squad-Level, Battlefield Situational Awareness: THreat Reconnaissance and Exploitation from Audio-video Target eXtraction (THREAT X)," in AUVSI XPONENTIAL Conference, 2017.
  7. J. Moeller, E. Smith, A. Basharat, M. Turek, A. Hoogs, and E. Blasch, "Automatic pattern of life learning in satellite images through graph kernels," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2017.
  8. C. Law, J. Parham, M. Dawkins, P. Tunison, D. Stoup, R. Blue, K. Fieldhouse, M. Turek, A. Hoogs, S. Han, A. Farafard, J. Kerekes, E. Lentilucci, M. Gartley, T. Savakis, T. Rovito, S. Thomas, and C. Stansifer, "Deep learning for object detection and object-based change detection in satellite imagery," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2017.
  9. K. Fieldhouse, A. Hoogs, and E. Swears, "Fusing Visible and Infrared (IR) Video on Mobile Robots, UAVs and Warfighters for Real-Time, Squad-Level Situational Awareness," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2017.
  10. M. Dawkins, R. Collins, and A. Hoogs, "Using Convolutional Neural Networks for Content-Based FMV Retrieval," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2017.
  11. S. Oh, M. Pandey, I. Kim, and A. Hoogs, "Image-oriented economic perspective on user behavior in multimedia social forums: An analysis on supply, consumption, and saliency," Pattern Recognition Letters, vol. 72, pp. 33-40, Mar. 2016. [URL]
  12. M. Dawkins, A. Basharat, J. Becker, M. Turek, and A. Hoogs, "Deep architecture for small mover detection in overhead infrared imagery," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2016.
  13. P. Tunison, M. Turek, and A. Hoogs, "Functional scene element modeling for ISR data," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2016.
  14. Z. Sun, J. Baumes, P. Tunison, M. Turek, and A. Hoogs, "Tattoo detection and localization using region-based deep learning," in Proceedings of the IEEE International Conference on Pattern Recognition, 2016. [URL]
  15. M. Dawkins, Z. Sun, J. Becker, A. Basharat, A. Hoogs, and M. Turek, "Track Object Type Classification Across a Range of Scales and Types of Video," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2016.
  16. 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 Proceedings of the MSS National Symposium on Passive Sensors, 2015.
  17. 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]
  18. 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 Applied Imagery Pattern Recognition Workshop, 2014. [URL]
  19. E. Swears, A. Basharat, A. Hoogs, and E. Blasch, "Probabilistic sub-GRAph Matching (PGRAM) for video and text fusion," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2014.
  20. A. Basharat, M. Turek, Yiliang 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 Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2014. [URL]
  21. E. Swears, A. Hoogs, Q. Ji, and K. Boyer, "Complex Activity Recognition Using Granger Constrained DBN (GCDBN) in Sports and Surveillance Video," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014. [URL]
  22. E. Swears, A. Hoogs, and K. Boyer, "Pyramid Coding for Functional Scene Element Recognition in Video Scenes," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2014.
  23. 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 Motion Imagery for ISR and Situational Awareness, 2014. [URL]
  24. E. Blasch, J. Nagy, A. Aved, E. Jones, W. Pottenger, A. Basharat, A. Hoogs, M. Schneider, R. Hammoud, G. Chen, D. Shen, and H. Ling, "Context aided video-to-text information fusion," in International Conference on Information Fusion, 2014.
  25. Z. 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, and Sensing Motion Imagery for ISR and Situational Awareness, 2014. [URL]
  26. Y. Xu, A. Basharat, J. Becker, and A. Hoogs, "Complex algorithm optimization through probabilistic search of its configuration tree," in Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2014. [URL]
  27. M. Dawkins, A. Perera, and A. Hoogs, "Real-time heads-up display detection in video," in Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2014. [URL]
  28. 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 Proceedings of the IEEE International Conference on Pattern Recognition, 2014. Winner, Best Industry-Related Paper Award. [URL]
  29. Y. Xu, D. Song, and A. Hoogs, "An Efficient Online Hierarchical Supervoxel Segmentation Algorithm for Time-critical Applications," in Proceedings of the British Machine Vision Conference, 2014. [URL]
  30. M. Dawkins and A. Hoogs, "Automatic image-plane aligned obstruction detection in EO and IR video," in Proceedings of the MSS National Symposium on Passive Sensors, 2014.
  31. F. Porikli, F. Bremond, S. Dockstader, J. Ferryman, A. Hoogs, B. Lovell, S. Pankanti, B. Rinner, P. Tu, and P. Venetianer, "Video surveillance: past, present, and now the future [DSP Forum]," IEEE Signal Processing Magazine, vol. 30, no. 3, pp. 190-198, May 2013. [URL]
  32. E. Swears, A. Hoogs, and R. Blue, "Recognizing Activity Based Scene Elements in Video," in Automatic Target Recognition Working Group, 2013.
  33. Y. Xu, S. Oh, and A. Hoogs, "A Minimum Error Vanishing Point Detection Approach for Uncalibrated Monocular Images of Man-Made Environments," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2013. [URL]
  34. E. Swears, A. Hoogs, and K. Boyer, "Pyramid Coding for Functional Scene Element Recognition in Video Scenes," in Proceedings of the IEEE International Conference on Computer Vision, 2013. [URL]
  35. 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 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2013. [URL]
  36. K. Reddy, N. Cuntoor, A. Perera, and A. Hoogs, "Human Action Recognition in Large-Scale Datasets Using Histogram of Spatiotemporal Gradients," in Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2012. [URL]
  37. 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]
  38. E. Swears and A. Hoogs, "Learning and recognizing complex multi-agent activities with applications to american football plays," in Proceedings of the IEEE Workshop on Applications of Computer Vision, 2012. [URL]
  39. 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]
  40. 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.
  41. S. Oh, A. Hoogs, A. Perera, N. Cuntoor, C. Chen, J. Lee, S. Mukherjee, J. 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 Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2011. [URL]
  42. E. Swears and A. Hoogs, "Complex Activity Recognition using Granger Constrained Dynamic Bayesian Network," in Learning Workshop, Fort Lauderdale Florida, 2011.
  43. 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]
  44. 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, pp. 461-488, Jul. 2010. [URL]
  45. N. Cuntoor, A. Basharat, A. Perera, and A. Hoogs, "Track Initialization in Low Frame Rate and Low Resolution Videos," in Proceedings of the IEEE International Conference on Pattern Recognition, 2010. [URL]
  46. S. Oh and A. Hoogs, "Unsupervised Learning of Activities in Video Using Scene Context," in Proceedings of the IEEE International Conference on Pattern Recognition, 2010. [URL]
  47. D. Hutchison, T. Kanade, J. Kittler, J. Kleinberg, F. Mattern, J. Mitchell, M. Naor, O. Nierstrasz, C. Pandu Rangan, B. Steffen, M. Sudan, D. Terzopoulos, D. Tygar, M. Vardi, G. Weikum, 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]
  48. E. Swears and A. Hoogs, "Functional scene element recognition for video scene analysis," in Proceedings of the IEEE Workshop on Motion and Video Computing, 2009. [URL]
  49. 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]
  50. 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]
  51. A. Hoogs and A. Perera, "Video Activity Recognition in the Real World," in National Conference on Artificial Intelligence, 2008. [URL]
  52. A. Hoogs, S. Bush, G. Brooksby, A. Perera, M. Dausch, and N. Krahnstoever, "Detecting Semantic Group Activities Using Relational Clustering," in Proceedings of the IEEE Workshop on Motion and Video Computing, 2008. [URL]
  53. E. Swears, A. Hoogs, and A. Perera, "Learning Motion Patterns in Surveillance Video using HMM Clustering," in Proceedings of the IEEE Workshop on Motion and Video Computing, 2008. [URL]
  54. F. Wheeler and A. Hoogs, "Moving Vehicle Registration and Super-Resolution," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2007. [URL]
  55. M. Chan, A. Hoogs, Z. Sun, J. Schmiederer, R. Bhotika, and G. Doretto, "Event recognition with fragmented object tracks," in Proceedings of the IEEE International Conference on Pattern Recognition, 2006. [URL]
  56. A. Perera, A. Hoogs, C. Srinivas, G. Brooksby, and W. Hu, "Evaluation of Algorithms for Tracking Multiple Objects in Video," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2006. [URL]
  57. M. Chan, A. Hoogs, R. Bhotika, A. Perera, J. Schmiederer, and G. Doretto, "Joint Recognition of Complex Events and Track Matching," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006. [URL]
  58. A. Perera, G. Brooksby, A. Hoogs, and G. Doretto, "Moving Object Segmentation using Scene Understanding," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2006. [URL]
  59. 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]
  60. Z. Sun and A. Hoogs, "Image comparison by compound disjoint information," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006. [URL]
  61. A. Perera, C. Srinivas, A. Hoogs, G. Brooksby, and Wensheng Hu, "Multi-Object Tracking Through Simultaneous Long Occlusions and Split-Merge Conditions," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006. [URL]
  62. 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]
  63. A. Hoogs, M. Chan, R. Bhotika, and J. Schmiederer, "Recognizing complex behaviors in aerial video," in Internation Conference on Interlligence Analysis, 2005.
  64. R. Kaucic, A. Perera, G. Brooksby, J. Kaufhold, and A. Hoogs, "A Unified Framework for Tracking through Occlusions and across Sensor Gaps," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2005. [URL]
  65. M. Chan, A. Hoogs, J. Schmiederer, and M. Petersen, "Detecting rare events in video using semantic primitives with HMM," in Proceedings of the IEEE International Conference on Pattern Recognition, 2004. [URL]
  66. J. Kaufhold and A. Hoogs, "Learning to segment images using region-based perceptual features," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2004. [URL]
  67. A. Perera and A. Hoogs, "Bayesian object-level change detection in grayscale imagery," in Proceedings of the IEEE International Conference on Pattern Recognition, 2004. [URL]
  68. J. Rittscher, A. Blake, A. Hoogs, and G. Stein, "Mathematical modelling of animate and intentional motion," Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 358, no. 1431, pp. 475-490, Mar. 2003. [URL]
  69. 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. [URL]
  70. 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]
  71. A. Hoogs, J. Rittscher, G. Stein, and J. Schmiederer, "Video content annotation using visual analysis and a large semantic knowledgebase," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2003. [URL]
  72. 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]
  73. A. Hoogs, R. Kaucic, and R. Collins, "Using video for recovering texture," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2001. [URL]
  74. A. Hoogs, J. Mundy, and G. Cross, "Multi-modal fusion for video understanding," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2001. [URL]
  75. A. Hoogs and J. Mundy, "Rapid data reduction and target detection in literal imagery," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2000. [URL]
  76. A. Hoogs and J. Mundy, "Information fusion for EO object detection and delineation," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2000.
  77. A. Hoogs and J. Mundy, "An integrated boundary and region approach to perceptual grouping," in Proceedings of the IEEE International Conference on Pattern Recognition, 2000. [URL]
  78. J. Mundy and A. Hoogs, "Data representations for object-level change detection in eo/ir imagery," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 1999.
  79. 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.
  80. A. Hoogs, D. Hackett, and D. Dadd, "Image Understanding at Lockheed Martin Management and Data Systems," in Proceedings of the DARPA Image Understanding Workshop, 1998.
  81. A. Hoogs, "Analysis of Learning Using Segmentation Models," in Conference on Computer Analysis of Images and Patterns, 1997.
  82. A. Hoogs, D. Hackett, and T. Barrett, "Image Understanding at Lockheed Martin Valley Forge," in Proceedings of the DARPA Image Understanding Workshop, 1997.
  83. A. Hoogs, B. Bremner, and D. Hackett, "The RADIUS Phase II Program," in Proceedings of the DARPA Image Understanding Workshop, 1997.
  84. M. Puscar and A. Hoogs, "User Interface Representations for Image Understanding," in Proceedings of the DARPA Image Understanding Workshop, 1997.
  85. A. Hoogs, "RADIUS: Imagery Understanding for Imagery Intelligence," RADIUS, Jul. 1997.
  86. A. Hoogs, "Combining Geometric and Appearance Models for Change Detection," in Proceedings of the DARPA Image Understanding Workshop, 1997.
  87. R. Cardenas and A. Hoogs, "The RADIUS Testbed Database: Temporal Queries and Optimization," in Proceedings of the SPIE Workshop on Applied Imagery and Pattern Recognition, 1996.
  88. A. Hoogs and R. Bajcsy, "Model-Based Learning of Segmentations," in Proceedings of the IEEE International Conference on Pattern Recognition, 1996.
  89. B. Kniffin and A. Hoogs, "Database Support for Exploitation Image Understanding," in Proceedings of the ARPA Image Understanding Workshop, 1996.
  90. B. Bremner, A. Hoogs, and J. Mundy, "Integration of Image Understanding Exploitation Algorithms in the RADIUS Testbed," in Proceedings of the ARPA Image Understanding Workshop, 1996.
  91. A. Hoogs, "Pose Adjustment Using a Parameter Hierarchy," in Proceedings of the ARPA Image Understanding Workshop, 1996.
  92. A. Hoogs and R. Bajcsy, "Segmentation Modeling," in Conference on Computer Analysis of Images and Patterns, 1995.
  93. B. Kniffin and A. Hoogs, "Combining Database Support for Image Understanding and Model-Supported Exploitation," in Proceedings of the SPIE Workshop on Applied Imagery and Pattern Recognition, 1995.
  94. A. Hoogs, "Object Position Refinement Using Hierarchical Search," in Proceedings of the SPIE Workshop on Applied Imagery and Pattern Recognition, 1995.
  95. A. Hoogs and R. Bajcsy, "Using Scene Context to Model Segmentations," in Workshop on Context-Based Vision, 1995.
  96. A. Hoogs and D. Hackett, "Model-Supported Exploitation as a Framework for Image Understanding," in Proceedings of the ARPA Image Understanding Workshop, 1994.
  97. R. Bajcsy and A. Hoogs, "Segmentation Characterization for Change Detection," in Proceedings of the ARPA Image Understanding Workshop, 1994.
  98. A. Hoogs and B. Kniffin, "The RADIUS Testbed Database: Issues and Design," in Proceedings of the ARPA Image Understanding Workshop, 1994.
  99. J. Mundy, R. Welty, L. Quam, T. Strat, W. Bremner, M. Horwedel, D. Hackett, and A. Hoogs, "The RADIUS Common Development Environment," in Proceedings of the DARPA Image Understanding Workshop, 1992.
  100. 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. [URL]