Machine Perception Technologies developed software that quantifies human facial expressions, enabling applications such as smile analysis, driver fatigue detection, and broader facial expression analysis. Their products translate visual cues into numerical data, allowing developers to integrate emotion‑aware features into mobile and enterprise applications. For example, their SMILE app for Android detected and ranked smiles worldwide, offering a searchable map of user‑generated smile data.
Funding
Funding not disclosed
Founders
Product
Problem
Many applications lack automated, quantitative analysis of human facial expressions, making it difficult to assess emotions, driver alertness, or smile intensity at scale.
Solution
Machine Perception Technologies built software that converts facial movements into numeric metrics using machine‑learning models trained on the Facial Action Coding System. Their flagship Android app, SMILE, captures a user’s smile, assigns a score, and aggregates results on a global map. The platform also includes a driver‑fatigue module that monitors grip force on the steering wheel to infer drowsiness, and a general facial‑expression analysis tool for broader emotion detection. All components run on standard mobile hardware and output data that can be integrated into downstream analytics or user interfaces.
Target Audience
Primary customers are mobile app developers, automotive safety system providers, and enterprises seeking emotion analytics for marketing or user experience research.
Features
- Real‑time facial landmark detection and expression quantification based on FACS‑derived neural networks
- SMILE for Android app that scores smiles and visualizes rankings on a world map, sold for $0.99 on Google Play
- Driver fatigue detection using grip‑force sensing to identify decreasing alertness levels
- API for exporting numeric expression data to third‑party analytics or enterprise systems
- Lightweight mobile implementation requiring only a smartphone camera and optional sensor inputs