ThermalTracker-3D: A thermal stereo vision system for quanitfying bird and bat activity at offshore wind energy sites. Matzner, S.; Warfel, T.; and Hull, R. Ecological Informatics, 2020.
ThermalTracker-3D: A thermal stereo vision system for quanitfying bird and bat activity at offshore wind energy sites [link]Website  abstract   bibtex   
We present a new, efficient method for extracting three-dimensional animal motion trajectories from thermal stereo video data. Understanding animal behavior in the wild or other unconstrained environments is often based on animal movements. The technology described here is for understanding how bird and bat behavior is affected by the presence of wind turbines, specifically offshore wind turbines which are challenging to monitor. There is a need for both baseline data prior to wind farm construction and post-construction data when the turbines are operating. Thermal cameras were chosen because they are equally effective both night and day. In previous work, we developed a method for generating two-dimensional images of animal motion using thermal video from a single camera. The motion track image is formed by combining a sequence of video frames into a single composite image that shows the entire flight trajectory. Here we demonstrate that the composite motion track images from a stereo pair of thermal cameras can be used directly to generate three-dimensional tracks in real time without the need for an explicit tracking algorithm. The method was evaluated using an unmanned aerial system (UAS) equipped with GPS. The UAS flew both straight and curving trajectories at distances between 50 and 325 m from the camera system. The ThermalTracker-3D estimated positions were within ±10 m of the GPS-derived positions in the x and y (flight height) dimensions, and within ±20 m in the z (range) dimension for 90% of the data points.The range estimates were within the bounds of the achievable accuracy of the cameras and camera arrangement used. The results demonstrate the practical usefulness of the method for assessing collision risk to seabirds at proposed offshore wind energy sites and for quantifying avoidance behavior at operating offshore wind farms.
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 title = {ThermalTracker-3D: A thermal stereo vision system for quanitfying bird and bat activity at offshore wind energy sites},
 type = {article},
 year = {2020},
 identifiers = {[object Object]},
 keywords = {Collision risk,Offshore wind,Seabirds,Stereo vision,Thermal imaging},
 pages = {101069},
 websites = {http://www.sciencedirect.com/science/article/pii/S1574954120300194},
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 abstract = {We present a new, efficient method for extracting three-dimensional animal motion trajectories from thermal stereo video data. Understanding animal behavior in the wild or other unconstrained environments is often based on animal movements. The technology described here is for understanding how bird and bat behavior is affected by the presence of wind turbines, specifically offshore wind turbines which are challenging to monitor. There is a need for both baseline data prior to wind farm construction and post-construction data when the turbines are operating. Thermal cameras were chosen because they are equally effective both night and day. In previous work, we developed a method for generating two-dimensional images of animal motion using thermal video from a single camera. The motion track image is formed by combining a sequence of video frames into a single composite image that shows the entire flight trajectory. Here we demonstrate that the composite motion track images from a stereo pair of thermal cameras can be used directly to generate three-dimensional tracks in real time without the need for an explicit tracking algorithm. The method was evaluated using an unmanned aerial system (UAS) equipped with GPS. The UAS flew both straight and curving trajectories at distances between 50 and 325 m from the camera system. The ThermalTracker-3D estimated positions were within ±10 m of the GPS-derived positions in the x and y (flight height) dimensions, and within ±20 m in the z (range) dimension for 90% of the data points.The range estimates were within the bounds of the achievable accuracy of the cameras and camera arrangement used. The results demonstrate the practical usefulness of the method for assessing collision risk to seabirds at proposed offshore wind energy sites and for quantifying avoidance behavior at operating offshore wind farms.},
 bibtype = {article},
 author = {Matzner, Shari and Warfel, Thomas and Hull, Ryan},
 journal = {Ecological Informatics}
}
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