A conditional mixture of neural networks for face detection, applied to locating and tracking an individual speaker

0Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.
Get full text

Abstract

We present a neural network approach to human face detection. Using a modular system, a conditional mixture of networks, we are able to detect front view faces as well as turned faces (up to 50 degrees) with excellent performances. This modular network is integrated into LISTEN, our face tracking system. It enables this system to detect and track in real-time faces in a variety of orientations, extending its previous applicability.

Cite

CITATION STYLE

APA

Feraud, R., Bernier, O., Viallet, J. E., Collobert, M., & Collobert, D. (1997). A conditional mixture of neural networks for face detection, applied to locating and tracking an individual speaker. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1296, pp. 464–471). Springer Verlag. https://doi.org/10.1007/3-540-63460-6_151

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free