Authors:
Xiaozheng Mou
and
Han Wang
Affiliation:
Nanyang Technological University, Singapore
Keyword(s):
Template Matching, Nose Tip Localization, Face Orientation Computation.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Enterprise Information Systems
;
Human and Computer Interaction
;
Human-Computer Interaction
;
Pattern Recognition
;
Robotics
;
Software Engineering
Abstract:
This paper presents an improved approach for face pose estimation based on depth data using particle swarm
optimization (PSO). In this approach, the frontal face of the system-user is first initialized and its depth image
is taken as a person-specific template. Each query face of that user is rotated and translated with respect to its
centroid using PSO to match with the template. Since the centroid of each query face always changes with the
face pose changing, a common reference point has to be defined to measure the exact transformation of the
query face. Thus, the nose tips of the optimal transformed face and the query face are localized to recompute
the transformation from the query face to the optimal transformed face that matched with the template. Using
the recomputed rotation and translation information, finally, the pose of the query face can be approximated
by the relative pose between the query face and the template face. Experiments on public database show that
the accura
cy of this new method is more than 99%, which is much higher than the best performance (< 91%)
of existing work.
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