FaceGest

Elevator Pitch: FaceGest revolutionizes privacy and functionality in emotion detection and facial recognition. Our cutting-edge, non-visual technology captures even the most subtle expressions accurately without ever compromising user privacy, making it perfect for a wide range of applications from healthcare to gaming. Say goodbye to privacy concerns and occlusion limitations with FaceGest, where your expressions are your own.

Concept

A privacy-focused facial recognition and emotion tracking platform using non-visual inertial measurement units (IMUs).

Objective

To provide a secure and non-intrusive method for facial motion capture and emotion detection for use in various industries while ensuring privacy and overcoming limitations like occlusions.

Solution

Utilizing ultra-compact, specially designed micro-IMUs and a novel IMU-ARKit dataset, FaceGest captures accurate facial expressions and motions. This technology is applied to detect nuanced emotional states and gestures without relying on visual data, thus ensuring user privacy.

Revenue Model

Subscription-based access for businesses, with tiered pricing depending on usage volume and the level of customization required. Additional revenue from licensing the technology to hardware manufacturers.

Target Market

Healthcare for patient mood monitoring, gaming and VR for more immersive experiences, security for identity verification without compromising privacy, and telecommunication for enhanced video call experiences.

Expansion Plan

Initially target the healthcare and gaming industries, followed by expansion into security solutions and telecommunication enhancements. Future iterations could include consumer products for everyday technology interaction.

Potential Challenges

Technical challenges in achieving high accuracy with IMUs, ensuring comfortable and practical designs for long-term wear, widespread market adoption beyond niche applications.

Customer Problem

Existing facial recognition and emotion detection infringe on privacy and struggle with obstacles like occlusions, creating a demand for non-visual, privacy-preserving solutions.

Regulatory and Ethical Issues

Compliance with global privacy laws and regulations, ensuring data security, and establishing clear usage guidelines to prevent misuse.

Disruptiveness

FaceGest disrupts traditional visual-based facial recognition technologies by offering a fully private, non-visual alternative that can work in any lighting condition and does not require direct line of sight.