1. Gomez-Barrero, M., Rathgeb, C., Li, G., Ramachandra, R.,
Galbally, J. and Busch, C., "Multi-biometric template protection
based on bloom filters", Information Fusion, Vol. 42, No. 1,
(2018), 37-50.
2. Pisani, P.H., Poh, N., de Carvalho, A.C. and Lorena, A.C., "Score
normalization applied to adaptive biometric systems", Computers
& Security, Vol. 70, No. 1, (2017), 565-580.
3. Wang, S.-L. and Liew, A.W.-C., "Physiological and behavioral
lip biometrics: A comprehensive study of their discriminative
power", Pattern Recognition, Vol. 45, No. 9, (2012), 3328-3335.
4. Saeed, U., "Eye movements during scene understanding for
biometric identification", Pattern Recognition Letters, Vol. 82,
No. 1, (2016), 190-195.
5. Bailey, K.O., Okolica, J.S. and Peterson, G.L., "User
identification and authentication using multi-modal behavioral
biometrics", Computers & Security, Vol. 43, No. 1, (2014), 7789.
6. Chu, Z., Gianvecchio, S., Koehl, A., Wang, H. and Jajodia, S.,
"Blog or block: Detecting blog bots through behavioral
biometrics", Computer Networks, Vol. 57, No. 3, (2013), 634646.
7. Mai, A. and Commuri, S., "Intelligent control of a prosthetic ankle
joint using gait recognition", Control Engineering Practice, Vol.
49, No. 2, (2016), 1-13.
8. Ngo, T.T., Makihara, Y., Nagahara, H., Mukaigawa, Y. and Yagi,
Y., "Similar gait action recognition using an inertial sensor",
Pattern Recognition, Vol. 48, No. 4, (2015), 1289-1301.
9. Birch, I., Raymond, L., Christou, A., Fernando, M.A., Harrison,
N. and Paul, F., "The identification of individuals by
observational gait analysis using closed circuit television
footage", Science & Justice, Vol. 53, No. 3, (2013), 339-342.
10. Chattopadhyay, P., Roy, A., Sural, S. and Mukhopadhyay, J.,
"Pose depth volume extraction from rgb-d streams for frontal gait
recognition", Journal of Visual Communication and Image
Representation, Vol. 25, No. 1, (2014), 53-63.
11. Ma, G., Wu, L. and Wang, Y., "A general subspace ensemble
learning framework via totally-corrective boosting and tensorbased
and local patch-based extensions for gait recognition",
Pattern Recognition, Vol. 66, No. 1, (2017), 280-294.
12. Khalesi, N., Khosravi, N., Ranjbar, A., Godarzi, Z. and Karimi,
A., "The effectiveness of earmuffs on the physiologic and
behavioral stability in preterm infants", International journal of
pediatric otorhinolaryngology, Vol. 98, No. 1, (2017), 43-47.
13. Adams, Z.W., McClure, E.A., Gray, K.M., Danielson, C.K.,
Treiber, F.A. and Ruggiero, K.J., "Mobile devices for the remote
acquisition of physiological and behavioral biomarkers in
psychiatric clinical research", Journal of psychiatric research,
Vol. 85, No. 1, (2017), 1-14.
14. Luo, J., Tang, J., Tjahjadi, T. and Xiao, X., "Robust arbitrary view
gait recognition based on parametric 3d human body
reconstruction and virtual posture synthesis", Pattern
Recognition, Vol. 60, No. 1, (2016), 361-377.
15. Zhao, X., Jiang, Y., Stathaki, T. and Zhang, H., "Gait recognition
method for arbitrary straight walking paths using appearance
conversion machine", Neurocomputing, Vol. 173, No. 1, (2016),
530-540.
16. Zeng, W. and Wang, C., "Gait recognition across different
walking speeds via deterministic learning", Neurocomputing,
Vol. 152, No. 1, (2015), 139-150.
17. Arora, P., Srivastava, S., Arora, K. and Bareja, S., "Improved gait
recognition using gradient histogram gaussian image", Procedia
Computer Science, Vol. 58, No. 1, (2015), 408-413.
18. Lu, W., Zong, W., Xing, W. and Bao, E., "Gait recognition based
on joint distribution of motion angles", Journal of Visual
Languages & Computing, Vol. 25, No. 6, (2014), 754-763.
19. Ben, X., Meng, W., Yan, R. and Wang, K., "Kernel coupled
distance metric learning for gait recognition and face
recognition", Neurocomputing, Vol. 120, No. 1, (2013), 577-589.
20. Xuan, Y., Zhao, Z., Fang, Z., Sun, F., Xu, Z., Du, L. and Wu, S.,
"Gait cycle recognition based on wireless inertial sensor
network", IERI Procedia, Vol. 4, No. 1, (2013), 44-52.
21. Sunwoo, M.K., Cho, K.H., Hong, J.Y., Lee, J.E., Sohn, Y.H. and
Lee, P.H., "Thalamic volume and related visual recognition are
associated with freezing of gait in non-demented patients with
parkinson's disease", Parkinsonism & Related Disorders, Vol.
19, No. 12, (2013), 1106-1109.
22. Al-Ani, M.S. and Al-Ani, I.H., "Gait recognition based improved
histogram", Journal of Emerging Trends in Computing and
Information Sciences, Vol. 2, No. 12, (2011), 674-679.
23. Ma, G., Wang, Y. and Wu, L., "Subspace ensemble learning via
totally-corrective boosting for gait recognition",
Neurocomputing, Vol. 224, No. 1, (2017), 119-127.
24. Sun, B., Zhang, Z., Liu, X., Hu, B. and Zhu, T., "Self-esteem
recognition based on gait pattern using kinect", Gait & posture,
Vol. 58, No. 1, (2017), 428-432.
25. Kastaniotis, D., Theodorakopoulos, I., Economou, G. and
Fotopoulos, S., "Gait based recognition via fusing information
from euclidean and riemannian manifolds", Pattern Recognition
Letters, Vol. 84, No. 1, (2016), 245-251.
26. Chen, X., Wang, L.-q., Ye, X.-f., Wang, G. and Wang, H.-l.,
"Prototype development and gait planning of biologically inspired
multi-legged crablike robot", Mechatronics, Vol. 23, No. 4,
(2013), 429-444.
27. Ntantogian, C., Malliaros, S. and Xenakis, C., "Gaithashing: A
two-factor authentication scheme based on gait features",
Computers & Security, Vol. 52, No. 1, (2015), 17-32.
28. Yu, S., Chen, H., Wang, Q., Shen, L. and Huang, Y., "Invariant
feature extraction for gait recognition using only one uniform
model", Neurocomputing, Vol. 239, No. 1, (2017), 81-93.
29. Marín-Jiménez, M.J., Castro, F.M., Carmona-Poyato, Á. and
Guil, N., "On how to improve tracklet-based gait recognition
systems", Pattern Recognition Letters, Vol. 68, No. 1, (2015),
103-110.
30. Yam, K.C., Reynolds, S.J. and Hirsh, J.B., "The hungry thief:
Physiological deprivation and its effects on unethical behavior",
Organizational Behavior and Human Decision Processes, Vol.
125, No. 2, (2014), 123-133.
31. Kusakunniran, W., "Attribute-based learning for gait recognition
using spatio-temporal interest points", Image and Vision
Computing, Vol. 32, No. 12, (2014), 1117-1126.
32. Dupuis, Y., Savatier, X. and Vasseur, P., "Feature subset selection
applied to model-free gait recognition", Image and Vision
Computing, Vol. 31, No. 8, (2013), 580-591.
33. Lee, C.P., Tan, A.W. and Tan, S.C., "Gait recognition via
optimally interpolated deformable contours", Pattern
Recognition Letters, Vol. 34, No. 6, (2013), 663-669.
34. Aqmar, M.R., Fujihara, Y., Makihara, Y. and Yagi, Y., "Gait
recognition by fluctuations", Computer Vision and Image
Understanding, Vol. 126, No. 1, (2014), 38-52.
35. Zeng, W., Wang, C. and Yang, F., "Silhouette-based gait
recognition via deterministic learning", Pattern Recognition,
Vol. 47, No. 11, (2014), 3568-3584.
36. Chattopadhyay, P., Sural, S. and Mukherjee, J., "Frontal gait
recognition from occluded scenes", Pattern Recognition Letters,
Vol. 63, No. 1, (2015), 9-15.
37. Lee, C.P., Tan, A.W. and Tan, S.C., "Gait recognition with
transient binary patterns", Journal of Visual Communication
and Image Representation, Vol. 33, No. 1, (2015), 69-77.
38. Yang, K., Dou, Y., Lv, S., Zhang, F. and Lv, Q., "Relative
distance features for gait recognition with kinect", Journal of
Visual Communication and Image Representation, Vol. 39, No.
1, (2016), 209-217.
39. Deng, M., Wang, C. and Chen, Q., "Human gait recognition based
on deterministic learning through multiple views fusion", Pattern
Recognition Letters, Vol. 78, No. 1, (2016), 56-63.
40. Deng, M., Wang, C., Cheng, F. and Zeng, W., "Fusion of spatialtemporal
and kinematic features for gait recognition with
deterministic learning", Pattern Recognition, Vol. 67, No. 1,
(2017), 186-200.
41. More, S.A. and Deore, P.J., "Gait-based human recognition using
partial wavelet coherence and phase features", Journal of King
Saud University-Computer and Information Sciences, Vol. 32,
No. 3, (2017).
42. Gadaleta, M. and Rossi, M., "Idnet: Smartphone-based gait
recognition with convolutional neural networks", Pattern
Recognition, Vol. 74, No. 1, (2018), 25-37.
43. Connor, P. and Ross, A., "Biometric recognition by gait: A survey
of modalities and features", Computer Vision and Image
Understanding, Vol. 167, No. 1, (2018), 1-27.
44. Wan, C., Wang, L. and Phoha, V.V., "A survey on gait
recognition", ACM Computing Surveys (CSUR), Vol. 51, No. 5,
(2018), 1-35.
45. Wu, Z., Huang, Y., Wang, L., Wang, X. and Tan, T., "A
comprehensive study on cross-view gait based human
identification with deep cnns", IEEE transactions on pattern
analysis and machine intelligence, Vol. 39, No. 2, (2016), 209226.
46. Takemura, N., Makihara, Y., Muramatsu, D., Echigo, T. and
Yagi, Y., "On input/output architectures for convolutional neural
network-based cross-view gait recognition", IEEE Transactions
on Circuits and Systems for Video Technology, Vol. 29, No. 9,
(2019), 2708 - 2719.
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