Built-in face recognition for smart photo sharing in mobile devices

This paper presents a smart photo sharing application for mobile devices based on an efficient yet powerful face recognition engine. The system allows registering subjects either from live video (mobile camera) or from still images, linking the obtained biometric information to the already existing phone contacts. The photo sharing application allows the user to select images which will be automatically processed with the built-in face recognition module based on Local Binary Patterns: already registered contacts will be identified, so that the current picture can be sent to them in a smart, user-friendly manner. The application also allows to tag unknown subjects and store (or update) their biometric profiles. All the processing is done in the mobile device. The current application runs on Android O.S., having been tested in two mobile platforms: HTC Desire and Samsung Galaxy Tab. The computational burden for each of the processing modules is provided in both devices, demonstrating the feasibility of the proposed approach for mobile platforms.

[1]  Kwontaeg Choi,et al.  Realtime training on mobile devices for face recognition applications , 2011, Pattern Recognit..

[2]  Adrian Holzer,et al.  Mobile application market: A developer's perspective , 2011, Telematics Informatics.

[3]  Ilias Maglogiannis,et al.  A Fast Mobile Face Recognition System for Android OS Based on Eigenfaces Decomposition , 2010, AIAI.

[4]  Shibnath Mukherjee Deloitte A Secure Face Recognition System for Mobile-devices without The Need of Decryption , 2008 .

[5]  Alice Caplier,et al.  Illumination-robust face recognition using retina modeling , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[6]  Kiyoung Moon,et al.  Real-Time Face Verification for Mobile Platforms , 2008, ISVC.

[7]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[8]  Anant Agarwal,et al.  Handheld Face Identification Technology in a Pervasive Computing Environment , 2002 .

[9]  Wen Gao,et al.  Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[10]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Alex Park,et al.  MULTI-MODAL FACE AND SPEAKER IDENTIFICATION ON A HANDHELD DEVICE , 2003 .

[12]  Yaniv Taigman,et al.  Descriptor Based Methods in the Wild , 2008 .

[13]  Sébastien Marcel,et al.  MOBIO: MOBILE BIOMETRIC FACE AND SPEAKER AUTHENTICATION , 2010 .