Detecting Planar Surface Using a Light-Field Camera with Application to Distinguishing Real Scenes From Printed Photos

We propose a novel approach for detecting printed photos from natural scenes using a light-field camera. Our approach exploits the extra information captured by a light-field camera and the multiple views of scene in order to infer a compact feature vector from the variance in the distribution of the depth of the scene. We then use this feature for robust detection of printed photos. Our algorithm can be used in person-based authentication applications to avoid intruding the system using a facial photo. Our experiments show that the energy of the gradients of points in the epipolar domain is highly discriminative and can be used to distinguish printed photos from original scenes.


Published in:
2014 Ieee International Conference On Acoustics, Speech And Signal Processing (Icassp), 4588-4592
Presented at:
2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Florence, Italy, May 4-9, 2014
Year:
2014
Publisher:
New York, Ieee
ISSN:
1520-6149
ISBN:
978-1-4799-2893-4
Keywords:
Laboratories:




 Record created 2014-03-17, last modified 2018-03-17

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