Event-Based Face Detection and Tracking Using the Dynamics of Eye Blinks.

ABSTRACT: We present the first purely event-based method for face detection using the high temporal resolution properties of an event-based camera to detect the presence of a face in a scene using eye blinks. Eye blinks are a unique and stable natural dynamic temporal signature of human faces across population that can be fully captured by event-based sensors. We show that eye blinks have a unique temporal signature over time that can be easily detected by correlating the acquired local activity with a generic temporal model of eye blinks that has been generated from a wide population of users. In a second stage once a face has been located it becomes possible to apply a probabilistic framework to track its spatial location for each incoming event while using eye blinks to correct for drift and trac

SUBMITTER: Lenz G 

PROVIDER: S-EPMC7397845 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature