2nd Workshop on
Automated Analysis of Video Data for Wildlife Surveillance
10th March 2016, Lake Placid, New York, USA
Participating Institutions
Dr. Richards completed his PhD in Zoology at the University of Hawaii in 2011, where he studied the ecology and patterns in habitat preference of large-bodied reef fish. In 1998 Ben joined the NOAA Florida Keys National Marine Sanctuary (FKNMS) to assist with the development of the FKNMS Research and Monitoring Plan and Final Environmental Impact Statement. In 2004 Ben moved to the Coral Reef Ecosystem Division of the NOAA Pacific Islands Fisheries Science Center (PIFSC) in Honolulu, modeling the distribution of Pacific reef fish abundance and biomass associated with various natural and anthropogenic environmental factors. Input data for these studies predominantly resulted from diver-based visual surveys. Inter-observer variation and the paucity of data from below diver depths pushed his research toward the use of camera-based technologies for optical sampling. Since moving to the PIFSC Stock Assessment Division in 2010, his research has focused on the use of advanced fishery-independent sampling technologies, including optical camera systems, to assess species-specific, size-structured abundance for Hawaii bottomfish assemblages. The volume of data produced by these camera systems has quickly overwhelmed the capabilities of human analysts. His research focus has thus expanded to include the development of automated classification algorithms to produce species-specific, size-structured abundance estimates from underwater optical surveillance video of reef and bottomfish.
Ben currently serves as a member of the National Marine Fisheries Service Advanced Sampling Technology Working Group and is chair of the NMFS Strategic Initiative on Automated Image Analysis. His research currently focuses on the distribution of marine resources along gradients of natural and anthropogenic factors and how advanced sampling technologies and automated analysis tools can provide enhanced data for stock assessment and ecosystem-based management.
Dr. Hoogs joined Kitware in August 2007 and founded the Computer Vision group. 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 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.
At Kitware, Dr. Hoogs supervises the Computer Vision group and leads business development efforts in this area. Recently he was the overall Principal Investigator on large DARPA programs including the Video and Image Retrieval and Analysis Toolkit (VIRAT) and the Persistent Stare Exploitation and Analysis System (PerSEAS), with responsibility for overseeing more than twelve universities and nine commercial subcontractors. He has initiated and led more than two dozen contracts in video and motion analysis with a combined value of tens of millions of dollars. 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 60 papers in computer vision, pattern recognition, artificial intelligence and remote sensing. His academic service includes: Area Chair for IEEE Conference on Computer Vision and Pattern Recognition (2009, 2010, 2012); Corporate Relations Chair for CVPR (2009, 2010) and the IEEE International Conference on Computer Vision (2013); Program Co-Chair for the IEEE Workshop on Applications in Computer Vision (2009, 2011); Steering Committee member for WACV; organizer and co-chair of the IEEE Workshop on Perceptual Organization in Computer Vision (2004); organizer and co-chaired of the IEEE International Workshop on Semantic Knowledge in Computer Vision (2005). He has served on technical panels for NSF and DARPA, including DARPA Information Science and Technology (ISAT) panels in 2007, 2009 and 2013. He regularly serves on program committees for the primary computer vision conferences and workshops (ICCV, CVPR, ECCV, WACV, AVSS) and is a reviewer for premier journals in computer vision and artificial intelligence (PAMI, IJCV, CVIU, MVA, TIP, TMM, AIJ).
Dr. Kriegman received a B.S.E. degree in Electrical Engineering and Computer Science from Princeton University in 1983, and an M.S. degree in 1984 and Ph.D. in 1990 in Electrical Engineering from Stanford University. Since 2002, David Kriegman has been a Professor of Computer Science and Engineering in the Jacobs School of Engineering at the University of California, San Diego. Prior to joining UCSD, he was an Assistant and Associate Professor of Electrical Engineering and Computer Science at Yale University (1990-1998) and an Associate Professor with the Computer Science Department and Beckman Institute at the University of Illinois at Urbana-Champaign (1998-2002). Kriegman was founding CEO and presently serves as Chief Scientist of Taaz, Inc, the leader in photorealistic virtual try on.
Dr. Kriegman's research is in computer vision with particular application to face recognition, robotics, computer graphics, microscopy, and coral reef ecology. Kriegman was chosen for an NSF Young Investigator Award, and has received best paper awards at the 1996 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), the 1998 European Conference on Computer Vision, and the 2007 International Conference on Computer Vision (Marr Prize, runner up) as well as the 2003 Paper of the Year Award from the Journal of Structural Biology. He has served as Program Co-chair of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) in 2000 and General Co-chair of CVPR 2005. He has been an Associate Editor, Associate Editor-in-Chief, and the Editor-in-Chief (2005-2008) of the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). In 20113, he became a member of the NOAA NMFS Automated Image Analysis Strategic Initiative committee, and on the planning committee of the 2014 NRC Workshop on Robust Methods for the analysis of images and videos for fisheries stock assessment.
Dr. Jules Jaffe, University of California San Diego
Dr. Serge Belongie, Cornell University
Dr. Magrit Betke, Boston University
Dr. Alexandra Branzan Albu, University of Victoria
Dr. Elizabeth Clarke, NOAA Fisheries Northwest Fisheries Science Center
Dr. Rob Fisher, University of Edinburgh
Dr. Deborah Hart, NOAA Northeast Fisheries Science Center
Dr. David Jacobs, University of Maryland
Dr. Michael Piacentino, SRI International
Dr. Lakshman Prasad, Los Alamos National Laboratory
Dr. Dezhen Song, Texas A&M University
Dr. Concetto Spampinato, University of Catania
William Michaels, NOAA Fisheries Office of Science and Technology
In Conjunction with the IEEE Winter Conference on Applications of Computer Vision