Tracking Facial Features Using Cluster of Point Distribution Models

Dimitris Metaxas (Inventor), Atul Kanaujia (Inventor)

Research output: Innovation


Invention Summary: Investigators at Rutgers have developed a technology for real time tracking of facial feature shapes and expressions on a non-linear manifold applied to pose prediction, expression recognition and eye tracking. The technology proposes a novel framework for tracking faces across large head rotations at near real time processing rate. It also provides an integration of shape registration and tracking frameworks for shapes lying on any manifold by approximating non-linearities as piece¬wise linear surfaces. Market Application: Monitoring driver alertness Homeland security applications Medical applications Games and entertainment Product placement applications in stores and customer related analysis of interest in products Advantages: Speed and accuracy. We use a dynamic analysis of the features (as opposed to static that all other methods do). The technology tracks the face across any generic movement. The frame¬work runs at real time and the tracking is robust to full head turning and for any head shape. Intellectual Property & Development Status: Patent pending; US 2008-0187174 A1
Original languageEnglish (US)
StatePublished - Jun 2013
Externally publishedYes


  • Homeland Security
  • Research Applications


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