Event-based Dynamic Face Detection and Tracking Based on Activity
We present the first purely event-based approach for face detection using an ATIS, a neuromorphic camera. We look for pairs of blinking eyes by comparing local activity across the input frame to a predefined range, which is defined by the number of events per second in a specific location. If within range, the signal is checked for additional constraints such as duration, synchronicity and distance between the eyes. After a valid blink is registered, we await a second blink in the same spot to initiate Gaussian trackers above the eyes. Based on their position, a bounding box around the estimated outlines of the face is drawn. The face can then be tracked until it is occluded.
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