LAFTER: Lips and Face Real-Time Tracker

This paper describes an active-camera real-time system for tracking, shape description, and classification of the human face and mouth using only an SGI Indy computer. The system is based on use of 2-D blob features, which are spatially-compact clusters of pixels that are similar in terms of low-level image properties. Patterns of behavior (e.g., facial expressions and head movements) can be classified in real-time using Hidden Markov Model (HMM) methods. The system has been tested on hundreds of users and has demonstrated extremely reliable and accurate performance. Typical classification accuracies are near 100%.

• Type: Conference
• Year: 1997
• Where: CVPR
• Authors: Nuria Oliver, Alex Pentland, François Bérard
• Keywords: 2-D Blob Features, Computer Vision, CVPR 1997, Low-level Image Properties, SGI Indy Computer