Talks and Poster Presentations (with Proceedings-Entry):

H. Eidenberger:
"Kalman Filtering for Pose-invariant Face Recognition";
Talk: IEEE International Conference on Image Processing, Atlanta, GA; 2006-10-01 - 2006-10-04; in: "IEEE ICIP Proceedings", (2006).

English abstract:
We propose a novel algorithm for the identification of faces from image samples. The algorithm uses the Kalman filter to identify significant facial traits. Kalmanfaces are compact visual models that represent the invariant proportions of face classes. We employ the Kalmanfaces approach on the UMIST database, a collection of face images that were recorded under varying camera angles. Kalmanfaces show robustness against invisible facial traits and outperform the classic Eigenfaces approach in terms of identification performance and algorithm speed. The paper discusses Kalmanfaces extraction, application, tunable parameters, experimental results and related work on Kalman filter application in face recognition.

Face Recognition, Kalman Filtering

Created from the Publication Database of the Vienna University of Technology.