Jehanzeb Mirza, Leonid Karlinsky, et al.
NeurIPS 2023
Tracking the face of a computer user as he looks at various parts of the screen is a fundamental tool for a variety of perceptual user interface applications. The authors have developed a simple but surprisingly robust tracking algorithm based on template matching and applied it successfully. This paper describes extensions to that algorithm, which improves performance at large facial rotation angles. The method is based on pre-distorting the single training template using 2D image transformations to simulate 3D facial rotations. The method avoids many of the problems associated with using a complex 3D head model. It is robust to variations in the environment and well-suited to use in practical applications in typical computing environments. © 2000 IEEE.
Jehanzeb Mirza, Leonid Karlinsky, et al.
NeurIPS 2023
Hagen Soltau, Lidia Mangu, et al.
ASRU 2011
Diganta Misra, Muawiz Chaudhary, et al.
CVPRW 2024
Hans-Werner Fink, Heinz Schmid, et al.
Journal of the Optical Society of America A: Optics and Image Science, and Vision