Face Recognition with Machine Learning in OpenCV_ Fusion of the results with the Localization Data of an Acoustic Camera for Speaker Identification

Abstract:This contribution gives an overview of face recogni-tion algorithms, their implementation and practical uses. First, a training set of different persons' faces has to be collected and used to train a face recognizer. The resulting face model can be utilized to classify people in specific individuals or unknowns. After tracking the recognized face and estimating the acoustic sound source's position, both can be combined to give detailed information about possible speakers and if they are talking or not. This leads to a precise real-time description of the situation, which can be used for further applications, e.g. for multi-channel speech enhancement by adaptive beamformers.

Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)

arXiv:1707.00835 [cs.CV]

(or arXiv:1707.00835v1 [cs.CV] for this version)

https://doi.org/10.48550/arXiv.1707.00835 Focus to learn more arXiv-issued DOI via DataCite

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