Mobile Applications Based on Smart Wearable Devices

Ubiquity of wearable devices sparked a new set of mobile computing applications that leverage the prolific information of sensors. I will focus on two main research questions: face recognition on smart glass and gait recognition on smart watch. Face recognition is one of the most popular research problems on various platforms. New research issues arise when it comes to resource constrained devices, such as smart glasses, due to the overwhelming computation and energy requirements of the accurate face recognition methods. Biometric gait recognition refers to verifying or identifying persons by their walking style, and it provides a unobtrusive way to authenticate the user and unlock the smart watches.

[1]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[2]  Kirsi Helkala,et al.  Biometric Gait Authentication Using Accelerometer Sensor , 2006, J. Comput..

[3]  Christoph Busch,et al.  Unobtrusive User-Authentication on Mobile Phones Using Biometric Gait Recognition , 2010, 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[4]  Heikki Ailisto,et al.  Unobtrusive Multimodal Biometrics for Ensuring Privacy and Information Security with Personal Devices , 2006, Pervasive.

[5]  Mikko Lindholm,et al.  Identifying people from gait pattern with accelerometers , 2005, SPIE Defense + Commercial Sensing.

[6]  Jie Yang,et al.  Smartphone based user verification leveraging gait recognition for mobile healthcare systems , 2013, 2013 IEEE International Conference on Sensing, Communications and Networking (SECON).

[7]  Wen Hu,et al.  Face recognition on smartphones via optimised Sparse Representation Classification , 2014, IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks.

[8]  Allen Y. Yang,et al.  Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[10]  Einar Snekkenes,et al.  Robustness of Biometric Gait Authentication Against Impersonation Attack , 2006, OTM Workshops.

[11]  Matti Pietikäinen,et al.  Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.