Company Filing History:
Years Active: 2025
Title: Innovations in Facial Movement Tracking by Tuochao Chen
Introduction
Tuochao Chen is an innovative inventor based in Ithaca, NY. He has made significant contributions to the field of wearable technology, particularly in tracking facial movements. His work focuses on enhancing the understanding of facial expressions through advanced systems and methods.
Latest Patents
Tuochao Chen holds a patent for wearable facial movement tracking devices. This technology provides systems and methods for tracking facial movements and reconstructing facial expressions by learning skin deformation patterns and facial features. Frontal view images of a user making a variety of facial expressions are acquired to create a data training set for use in a machine-learning process. Head-mounted or neck-mounted wearable devices are equipped with one or more camera(s) or acoustic device(s) in communication with a data processing system. The cameras capture images of contours of the user's face from either the cheekbone or the chin profile of the user. The acoustic devices transmit and receive signals to calculate a representation of the skin deformation. A data processing system uses the images, the profile of the contours, or skin deformation to track facial movement or to reconstruct facial expressions of the user based on the data training set.
Career Highlights
Tuochao Chen is affiliated with Cornell University, where he continues to push the boundaries of research in wearable technology. His work has garnered attention for its potential applications in various fields, including entertainment, healthcare, and human-computer interaction.
Collaborations
Some of his notable coworkers include Cheng Zhang and Benjamin Steeper, who contribute to the collaborative research environment at Cornell University.
Conclusion
Tuochao Chen's innovative work in wearable facial movement tracking devices represents a significant advancement in technology. His contributions are paving the way for new applications and understanding of human expressions through machine learning.