TEXAS A&M
TEXAS A&M PARTNERS WITH MOODME TO ENHANCE FACIAL ANALYSIS
From Snapchat photo filters to Super Bowl crowd surveillance to identity verification in airports, facial analysis techniques have taken the industry by storm. With a multitude of applications, this branch of artificial intelligence is ever evolving – encompassing image tagging on social media, expression recognition, security, marketing, robotics and more.
Bridging industry and education, a team of researchers led by Dr. Zhangyang “Atlas” Wang, professor in the Department of Computer Science and Engineering at Texas A&M University, is collaborating with MoodMe to improve the algorithms used in the company’s facial analysis and recognition programs. The team focusses on re-identification of participants in video conferences to measure their emotions and attentiveness. Texas A&M develops algorithms adopting deep learning to provide unique insight into clients and staff.
“We are excited by the chance to work with a leading company like MoodMe and to make broader impacts on the field of computer vision and deep learning,” said Wang.
An international leader in facial recognition and insight, MoodMe applies deep learning to create embedded software components that provide facial insights and augmented reality face filters. “Privacy is at the center of all our work, both in research and in product engineering,” said Chandra de Keyser, CEO of MoodMe. “All the insights we gather from faces fully respect people’s privacy – no faces are stored ever, nor sent to the Cloud. With all the promises of internet giants, there is still no “one-click” to delete all our pictures or data that they have accumulated about us. The focus of our research and engineering is to reach the highest performances and precision on edge computing platforms like smartphones, embedded/internet of things, robots and desktop computers.” Read the full article on TAMU Engineering web.
