We perform face tracking and pose estimation jointly within a mixed-state particle filter framework. Previous methods
often used generative appearance models and naive prior state transition. We propose to use discriminating models,
Adaboosted face detectors, to both measure observations and provide information for the proposal distribution which is
combined with detection responses and prior transition model. Due to pose continuity, faces between discrete poses can
be detected by neighboring pose-specific detectors and serve as importance samples. Thus continuous poses are obtained
instead of discrete poses. Experiments show that our method is robust to large location and pose changes, partial
occlusions and expressions.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.