Image Processing and Computer Vision for Ecology

Tuesday, August 11, 2015: 1:30 PM-3:00 PM
345, Baltimore Convention Center
Ben Weinstein, Stony Brook University
Ben Weinstein, Stony Brook University
Increasing environmental changes challenge ecologists to use new technologies to collect data with greater speed and accuracy. The cost, time, and logistics of human observation limit the scope of many studies, yet ecologists have only begun to use automated tools. Computer vision is a field of computer science that seeks to extract information from images, and can increase the efficiency and accuracy of observer studies by combining data taken from the field with automated image analysis. Diverse datasets from air-borne photographs to deep sea videos are increasingly collected, but as ecologists, our ability to manage and analyze these datasets is limited. This session will bring together researchers seeking extract ecological information from images to think broadly about the major opportunities, challenges and connections between ecologists using image data.
 A computer vision for ecology
Lucas Joppa, Microsoft
 Wildlife big data: Processing images from large scale photo surveys with eMammal
Tavis Forrester, Smithsonian Institution - National Zoological Park; William J. McShea, Smithsonian Conservation Biology Institute at the National Zoological Park; Robert Costello, Smithsonian Institution - National Museum of Natural History; Roland W. Kays, North Carolina Museum of Natural Sciences
 Unmanned aerial systems in wildlife research: Current and future applications of a transformative technology
Katie Christie, University of Alberta; Sophie L. Gilbert, University of Alaska, Fairbanks; Casey Brown, University of Alaska Fairbanks; Michael Hatfield, University of Alaska Fairbanks
 Using automated aerial imaging to estimate Arctic seal abundance: The devil is in the details
Paul Conn, NOAA; Erin E. Moreland, NOAA National Marine Mammal Lab
See more of: Ignite ESA Sessions