A feature based face tracker using extended Kalman filtering
Independent thesis Basic level (professional degree), 20 points / 30 hpStudent thesis
A face tracker is exactly what it sounds like. It tracks a face in a video sequence. Depending on the complexity of the tracker, it could track the face as a rigid object or as a complete deformable face model with face expressions.
This report is based on the work of a real time feature based face tracker. Feature based means that you track certain features in the face, like points with special characteristics. It might be a mouth or eye corner, but theoretically it could be any point. For this tracker, the latter is of interest. Its task is to extract global parameters, i.e. rotation and translation, as well as dynamic facial parameters (expressions) for each frame. It tracks feature points using motion between frames and a textured face model (Candide). It then uses an extended Kalman filter to estimate the parameters from the tracked feature points.
Place, publisher, year, edition, pages
Institutionen för systemteknik , 2007. , 38 p.
face tracker, extended Kalman filtering, the Candide face model
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:liu:diva-8755ISRN: LiTH-ISY-EX--07/4015--SEOAI: oai:DiVA.org:liu-8755DiVA: diva2:23445
2007-02-14, Systemet, B, Linköpings Universitet, Linköping, 10:15