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A KINECT DATABASE FOR FACE
RECOGNITION
Rui Min ; Kose, N. ; Dugelay, J.-L.
Systems, Man, and Cybernetics: Systems,
IEEE Transactions on (Volume:44 , Issue:
11 ), Page(s) : 1534 – 1548,November 2014
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Chairman: Hung-Chi Yang
Presenter : Hoe Jing Tey
Advisor :
Dr. Yen – Ting Chen
Date :
2014.12.10
INTRODUCTION
Face database proposed by the National Institute of Standards
and Technology(NIST)
Face recognition technology (FERET)
Face recognition vendor test (FRVT)
Face recognition grand challenge (FRGC)
Structure and the acquisition environment of the proposed
KinectFaceDB
Database Structure
Acquisition Environment
Acquisition Process
PostProcessing
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FACIAL LANDMARKING & EVALUTION SOLUTION
Database Structure
Nine facial variations
Six anchor on the face
BenchMark Evalution Solution
PCA(Principal Component Analysis)
LBP(Local Binary Patterns)
SIFT(Scale-Invariant Feature Transform)
LGBP(Local Gabor Binary Pattern)
ICP (iterative closest point)
TPS(thin-plate spline)
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CONCLUSION
Complete multimodal (including well-aligned 2-D, 2.5-D,
and 3-Dface data)
KinectFaceDB supplies a standard medium to fill the gap
between traditional face recognition and the emerging
Kinect technology.
Design of new algorithms and new facial descriptors for the
low-quality 3-D data
How to efficiently combine different data modalities (RGB,
depth,and 3-D) so as to maximize the exploitation of the
Kinect
Future work(revisit the literature on 3-D and 2-D + 3-D
face recognition algorithms)
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