| | |
Summary: Multi-View Active Shape Model with Robust Parameter Estimation
Li Zhang, Haizhou Ai
Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China
ahz@mail.tsinghua.edu.cn
Abstract
Active Shape Model is an efficient way for localizing ob-
jects with variable shapes. When ASM is extended to multi-
view cases, the parameter estimation approaches in previ-
ous works are often sensitive to the initial view, as they do
not handle the unreliability of local texture search, which
can be caused by bad initialization or cluttered background.
To overcome this problem, we propose a novel algorithm
for parameter estimation, using robust estimators to remove
outliers. By weighting dynamically, our method acts as a
model selection method, which reveals the hidden shape
and view parameters from noisy observations of local tex-
ture models. Experiments and comparisons on multi-view
face alignment are carried out to show the efficiency of our
approach.
1. Introduction
|
