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Tracking objects that move fast with respect to their size is challenging because it necessitates large field of views often incompatible with the required spatial and temporal resolutions. Here, we present a novel computer vision system that overcomes this tradeoff by employing a camera with dynamic region-of-interest (ROI) capabilities, combined with an efficient predictive approach. We apply this method to extract the wing kinematics of tethered flying fruit flies in real time. At each frame, only the pixels immediately surrounding the wing are exposed, and the wing position is extracted. It is then fed to an extended Kalman filter that extracts four key parameters of the measurement time-course and, therefore, provides real-time feedback of wing motion. Using this approach, we are able to sample the wing position of both wings at 7 kHz in a 2500 pixel ROI. Our methods promise new applications that can be implemented in general purpose digital hardware for high performance tracking and process control in a broad range of applications in technology and science.