Title
A robust composite metric for head pose tracking using an accurate face model
Abstract
We present a method for full-motion recovery of the head pose from a monocular video input based on an accurate head model and textures. We build our face model using a distribution of high resolution 3D face scans. The cost of computations makes us select parts of this full model. To address the difficult task of initializing the model position and tracking its motion, we use a composite metric using face texture samples from three different face databases, following a positive face detection. The algorithm is subsequently able to track the head in a wide pose range with great accuracy. We also provide test video sequences with an independent accurate ground truth (with estimated RMS error of 0.1 degrees).
Year
DOI
Venue
2011
10.1109/FG.2011.5771332
FG
Keywords
Field
DocType
face detection,video signal processing,face recognition,video sequences,motion tracking,composite metric,image resolution,visual databases,robust composite metric,head pose tracking,image sequences,high resolution 3d face scans,accurate face model,face databases,face texture,high resolution,face,shape,computer model,ground truth,computational modeling,solid modeling,three dimensional,tracking
Facial recognition system,Computer vision,Pattern recognition,Computer science,Ground truth,Solid modeling,Artificial intelligence,Initialization,Face detection,Image resolution,Match moving,Computation
Conference
ISBN
Citations 
PageRank 
978-1-4244-9140-7
3
0.38
References 
Authors
15
4
Name
Order
Citations
PageRank
Philippe Phothisane1101.90
Erwan Bigorgne2213.89
Laurent Collot330.38
Lionel Prevost440226.21