Automatic bird species detection using periodicity of salient extremities

To assist nature observation, we develop an automatic bird species filtering method that takes videos from cameras with unknown parameters as input, and outputs likelihood of candidate species. The method recognizes the time series of salient extremities, which is the inter-wing tip distance, performs frequency analysis on periodicity, and provides a species prediction metric using likelihood ratios. To analyze the feasibility of the proposed method, we derive the probability that the salient extremity can be recognized in image for an arbitrary camera perspective.We also prove that the periodicity of the IWTD in the image is the same as the wingbeat frequency in the 3D space regardless of camera parameters with the exception of ignorable degenerated cases. Experiment results validate our analysis and show that the algorithm is very robust to segmentation error and data loss up to 30%.