Frequency features and GMM-UBM approach for gait-based person identification using smartphone inertial signals

Anguita, 2013, A public domain dataset for human activity recognition using smartphones Ailisto, 2005, Identifying people from gait pattern with accelerometers, 5779, 7 Angulo, 2011, Exploring touch-screen biometrics for user identification on smart phones, 375, 130e43 Barnich, 2009, Frontal-view gait recognition by intra- and inter-frame rectangle size distribution, Pattern Recogn. Lett., 30, 893, 10.1016/j.patrec.2009.03.014 Bashir, 2010, Gait recognition without subject cooperation, Pattern Recogn. Lett., 31, 2052, 10.1016/j.patrec.2010.05.027 Ben, 2012, Dual-ellipse fitting approach for robust gait periodicity detection, Neurocomputing, 79, 173, 10.1016/j.neucom.2011.10.009 Ben, 2013, Kernel coupled distance metric learning for gait recognition and face recognition, Neurocomputing, 120, 577, 10.1016/j.neucom.2013.04.012 Boulgouris, 2005, Gait recognition: a challenging signal processing technology for biometric identification, Signal Process. Mag., IEEE, 22, 78, 10.1109/MSP.2005.1550191 Bours, 2010, Eigensteps: a giant leap for gait recognition, 1 Chattopadhyay, 2015, Frontal gait recognition from occluded scenes, Pattern Recogn. Lett., 63, 9, 10.1016/j.patrec.2015.06.004 Derawi, 2010, Improved cycle detection for accelerometer based gait authentication, 312 Derawi, 2010, Unobtrusive user-authentication on mobile phones using biometric gait recognition, 306 Derawi, 2013, Gait and activity recognition using commercial phones, Comput. Secur., 39, 137, 10.1016/j.cose.2013.07.004 Destephe, 2013, Emotional gait generation method based on emotion mental model - preliminary experiment with happiness and sadness Du, 2015, A hypothesis independent subpixel target detector for hyperspectral Images, Signal Process., 110, 244, 10.1016/j.sigpro.2014.08.018 Fawcett, 2006, An introduction to ROC analysis, Pattern Recogn. Lett., 27, 861, 10.1016/j.patrec.2005.10.010 Frank, 2010, Activity and gait recognition with time-delay embeddings Gafurov, 2006, Gait recognition using acceleration from mems Gafurov, 2008 Holien, 2008 Johansson, 1973, Visual perception of biological motion and a model for its analysis, Atten., Percept. Psychophys., 14, 201, 10.3758/BF03212378 Karg, 2010, Recognition of affect based on gait patterns, IEEE Trans. Syst., Man, Cybern.-Part B: Cybern, 40, 1050, 10.1109/TSMCB.2010.2044040 Khan, 2010, Human activity recognition via an accelerometer enabled- smartphone using kernel discriminant analysis, 1 Kwapisz, 2010, Cell phone-based biometric identification, 1 Lee, 2013, Gait recognition via optimally interpolated deformable contours, Pattern Recogn. Lett., 34, 663, 10.1016/j.patrec.2013.01.013 Liu, 2011, Joint subspace learning for view-invariant gait recognition, IEEE Signal Process. Lett., 18, 431, 10.1109/LSP.2011.2157143 Lu, 2007, Gait recognition for human identification based on ICA and fuzzy SVM through multiple views fusion, Pattern Recogn. Lett., 28, 2401, 10.1016/j.patrec.2007.08.004 Lu, 2010, Uncorrelated discriminant simplex analysis for view-invariant gait signal computing, Pattern Recogn. Lett., 31, 382, 10.1016/j.patrec.2009.11.006 Lu, 2014, Human identity and gender recognition from gait sequences with arbitrary walking directions, IEEE Trans. Inf. Forens. Secur., 9, 41, 10.1109/TIFS.2013.2291969 Lu, 2013, Ordinary preserving manifold analysis for human age and head pose estimation, IEEE Trans. Hum. Mach. Syst., 43, 249, 10.1109/TSMCC.2012.2192727 Lu, 2010, Gait-based human age estimation, IEEE Trans. Inf. Forens. Secur. (T-IFS), 5, 760 Mannini, 2010, Machine learning methods for classifying human physical activity from on-body accelerometers, Sensors, 10, 1154, 10.3390/s100201154 Matsumoto, 2002, Impact of artificial “gummy” fingers on fingerprint systems, 4677, 275 Milovanovic, 2013, Walking in colors: human gait recognition using kinect and CBIR, IEEE Multim., 20, 28, 10.1109/MMUL.2013.16 Mjaaland, 2011, Walk the walk: attacking gait biometrics by imitation, 361 Murray, 1973, Gait as a total pattern of movement, Am. J. Phys. Med., 46, 290e333 Nickel, 2011, Scenario test for accelerometer-based biometric gait recognition Nixon, 2006, Automatic recognition by Gait, Proc. IEEE, 94, 2013, 10.1109/JPROC.2006.886018 Qinghan, 2007, Technology review - biometrics-technology, application, challenge, and computational intelligence solutions, Comput. Intell. Mag., IEEE, 2, 5, 10.1109/MCI.2007.353415 Reyes-Ortiz, 2013, Human activity and motion disorder recognition: towards smarter interactive cognitive environments Reynolds, 2000, Speaker verification using adapted gaussian mixture models, Digital Signal Process., 10, 19, 10.1006/dspr.1999.0361 San-Segundo, 2016, Frequency extraction from smartphone inertial signals for human activity segmentation, Signal Process., 120, 359, 10.1016/j.sigpro.2015.09.029 Sarkar, 2005, The human ID gait challenge problem: data sets, performance, and analysis, IEEE Trans. Pattern Anal. Mach. Intell., 27, 162, 10.1109/TPAMI.2005.39 Shotton, 2011, Real-time human pose recognition in parts from single depth images, 1297 Vinh, 2011, Semi-markov conditional random fields for accelerometer-based activity recognition, Appl. Intell., 35, 226, 10.1007/s10489-010-0216-5 Yang, 2008, Using acceleration measurements for activity recognition: an effective learning algorithm for constructing neural classifiers, Pattern Recogn. Lett., 29, 2213, 10.1016/j.patrec.2008.08.002 Young, 2006 Zhang, 2015, A sparse and discriminative tensor to vector projection for human gait feature representation, Signal Process., 106, 245, 10.1016/j.sigpro.2014.08.005