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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
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Face database proposed by the National Institute of Standards
and Technology(NIST)
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Face recognition technology (FERET)
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Face recognition vendor test (FRVT)
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Face recognition grand challenge (FRGC)
Structure and the acquisition environment of the proposed
KinectFaceDB
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Database Structure
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Acquisition Environment
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Acquisition Process
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PostProcessing
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FACIAL LANDMARKING & EVALUTION SOLUTION
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Database Structure
Nine facial variations
 Six anchor on the face
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BenchMark Evalution Solution
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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
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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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