Graduate School and Research Center in Digital Sciences

Kinect vs lytro in RGB-D face recognition

Chiesa, Valeria; Dugelay, Jean-Luc

Cyberworlds 2018, International Conference, 3-5 October 2018, Singapore

Light field cameras are becoming increasingly popular thanks to higher capabilities with respect to regular cameras in capturing information of a scene. Even though the principle associated with structured light sensors is quite different from the technology behind light field cameras, data provided by these technologies are similar in terms of depth map. With the aim of comparing the potential of Kinect and Lytro sensors on face recognition, two experiments are conducted on separate but publically available datasets and validated on a database acquired simultaneously with Lytro Illum camera and Kinect V1 sensor. The results obtained on RGB and depth maps are integrated with an experiment based on fusion at score level. The introduction of depth information in the RGB data is found more effective than standard bi dimensional imaging, especially in case of occlusions.


Title:Kinect vs lytro in RGB-D face recognition
Department:Digital Security
Eurecom ref:5710
Copyright: © ACM, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Cyberworlds 2018, International Conference, 3-5 October 2018, Singapore
Bibtex: @inproceedings{EURECOM+5710, year = {2018}, title = {{K}inect vs lytro in {RGB}-{D} face recognition}, author = {{C}hiesa, {V}aleria and {D}ugelay, {J}ean-{L}uc}, booktitle = {{C}yberworlds 2018, {I}nternational {C}onference, 3-5 {O}ctober 2018, {S}ingapore}, address = {{S}ingapore, {SINGAPORE}}, month = {10}, url = {} }
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