Automatic Detection of Moving Baw Baw Frogs in Camera Trap Videos

This paper presents the design and implementation of a motion detection algorithm for processing of video sequences captured by a purpose-built camera trap, removing of unwanted frames, and reducing of the size of the video sequences. The camera trap is used to create a dataset containing H.264 video sequences of the critically endangered Baw Baw Frog Philoria frosti. A motion detection method based on the optical flow Farneback algorithm is then developed to reduce the size of the video sequences by detecting the frames that contain moving frogs, keeping and storing the detected frames, and discarding the frames that do not contain moving frogs. Twenty video sequences containing a total of 13770 frames are used in this study. The frames with moving frogs are detected with sensitivity of 0.993, specificity of 0.992, and accuracy of 0.992. The original video sequences are then replaced by the newly created video sequences that are much smaller in size with an average reduction of 80.4% for the test video sequences used in this study.