Data from: MotionMeerkat: integrating motion video detection and ecological monitoring

1. Human observation is expensive and limits the breadth of data
collection. For this reason, remotely placed video cameras are
increasingly used to monitor animals. One drawback of field-based video
recordings is extensive review time. Computer vision can mitigate this
cost and enhance data collection by extracting biological information from
images with minimal time investment. 2. MotionMeerkat is a new standalone
program that identifies motion events from a video stream. After running a
video, the user reviews a folder of candidate motion frames for the target
organism. This tool reduces the time needed to review videos and
accommodates a variety of inputs. 3. I tested MotionMeerkat using
hummingbird-plant videos recorded in a tropical montane forest. To
validate the optimal parameter set for finding motion events, I counted
hummingbirds observed from direct video review compared to events found in
images returned from MotionMeerkat. To show the generality of the
approach, MotionMeerkat was tested on a set of terrestrial and underwater
videos. To assess the performance of the background subtraction for
further image analysis, I hand counted the number of frames with target
organisms and compared them to the MotionMeerkat output. 4. MotionMeerkat
was highly successful in finding motion events and often reduced the
number of frames needed to capture hummingbird visitation by over 90%.
Both background approaches effectively found a variety of organisms in
ecological videos. I provide general recommendations for parameter
settings and extending this approach in the future.