Emotient, Inc., emotion detection and sentiment analysis, San Diego, California, USA

[Airicist]

youtube.com/EmotientCompany

twitter.com/EmotientInc

linkedin.com/company/emotient

Co-founder - Javier Movellan

Co-founder - Marian Bartlett

Co-founder - Ian Fasel

Co-founder - Gwen Littlewort

Projects:

Emotient FACET SDK

"Apple Buys Artificial-Intelligence Startup Emotient"
Emotient technology is used to assess emotions by reading facial expressions

by Rolfe Winkler, Daisuke Wakabayashi and Elizabeth Dwoskin
January 7, 2016

Apple Inc.

[Airicist]

Josh Susskind, Senior Data Scientist, Co-Founder, Emotient - RE.WORK Deep Learning Summit 2015

Published on Feb 23, 2015

This presentation took place at the Deep Learning Summit in San Francisco on 29-30 January 2015.

'Accurate, Fast & Robust Expression Recognition using Deep Learning'
Josh Susskind, Senior Data Scientist, Co-Founder, Emotient

Previous state of the art approaches to facial expression recognition including our own relied on handcrafted feature extraction and computer vision pipelines optimized for runtime speed and accuracy on relatively small datasets. Using specialized deep learning architectures trained on much larger datasets, we have significantly improved accuracy over our previous academic and commercial efforts, even when both types of systems are trained on the same data. These efforts have led to marked improvements in robustness to head pose and expression variation, without incurring speed penalties, and without requiring the use of GPU acceleration.

Dr. Joshua Susskind is a senior data scientist at Emotient, a company focused on real-time perception of facial expressions from images and videos, where he develops algorithms and visualization techniques for understanding human behavior. In graduate school he developed the first deep nets that could recognize and generate facial expressions. He holds a PhD in Psychology and Machine Learning from the University of Toronto, where he was co-advised by Dr. Geoffrey Hinton and Dr. Adam Anderson. His academic work has been featured in high impact journals including Nature Neuroscience and Science and in top computer vision and machine learning conferences.

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Marni Bartlett, Co-Founder & Lead Scientist, Emotient - RE.WORK Deep Learning Summit 2015

Published on Feb 26, 2015

This presentation took place at the Deep Learning Summit in San Francisco on 29-30 January 2015.

'Learning Natural Facial Expressions'
Marni Bartlett, Co-Founder & Lead Scientist, Emotient

Natural facial behavior can reveal information about our internal states intentions. I will describe two recent studies of machine learning on facial expression dynamics, where multi-stage learning models outperformed human observers. The first task was to distinguish genuine from faked pain. The second was to predict when a financial offer would be rejected in an economic game. My colleagues and I began a start-up company, Emotient, in 2012 to make the facial expression software commercially available. The potential for this technology is far-reaching, across fields of healthcare, education, advertising, and retail. I will wrap up the talk by describing applications in these areas.

Marian Bartlett, Ph.D. is co-Founder and Lead Scientist at Emotient, a San Diego based start-up company for automatic facial expression analysis, and Full Research Professor at University of California, San Diego. Marian is a pioneer in the field of machine learning and computer vision for face analysis. She and her colleagues developed software that automatically detects facial expressions of the seven primary emotions, as well as individual facial muscle movements, in collaboration with Paul Ekman, a founder of the science of facial behavior. The potential for this technology is far-reaching, across fields of healthcare, education, advertising, and retail. The technology was awarded best new product from CONNECT, San Diego, in 2013, and Marian was a winner of the 2014 Women Who Mean Business Award from the San Diego Business Journal. Marian received her Ph.D. from University of California, San Diego in Cognitive Science and Psychology, and her B.A. from Middlebury College in Mathematics and Computer Science. She has authored over 80 papers in scientific journals and conference proceedings, as well as a book, Face Image Analysis by Unsupervised Learning, published by Kluwer in 2001.