Gait and Anthropometric Profile Biometrics: A Step Forward
- 2 Citations
- 1.1k Downloads
Abstract
Emerging biometrics based on the measurements of body dynamic and static characteristics have gained increased importance in all the surveillance environments where the security is a mandatory priority. Some technology branches are involved to find unobtrusive solutions for authentication systems, where the human subject should not take care of the system itself so that he/she is free to perform his/her normal actions. In the first part of the chapter a novel gait recognition system is presented that introduces the use of range data for gait signal analysis. In the second part of the chapter, a description of system based on a sensing seat for event-related continuous authentication purpose in office and car scenarios is presented. Both biometric technologies introduce new means of verifying the user identity, by exploiting the analysis of common and every-day activities recorded in an unobtrusive manner and their recognition accuracy has been seen to be very high in the performed experiments.
Keywords
Strain Sensor Biometric System False Rejection Rate Gait Recognition Silhouette ImageReferences
- Abate, A.F., M. Nappi, D. Riccio, and G. Sabatino. 2007. 2D and 3D face recognition: Survey. Pattern Recognition Letters 28(14): 1885–1906.CrossRefGoogle Scholar
- Bodor, R., A. Drenner, D. Fehr, O. Masoud, and N. Papanikolopoulos. 2009. View-independent human motion classification using image-based reconstruction. Image and Vision Computing 27(8): 1194–1206.CrossRefGoogle Scholar
- Bouchrika, I., and M. Nixon. 2007. Model-based feature extraction for gait analysis and recognition. Computer vision/computer graphics collaboration techniques, 150–160.Google Scholar
- Bouchrika, I., and M. Nixon. 2008. Gait recognition by dynamic cues. In 19th IEEE International Conference on Pattern Recognition, 2008, Tampa, FL, USA.Google Scholar
- Bouchrika, I., M. Goffredo, J. Carter, and M. Nixon. 2009. Covariate analysis for view-point independent gait recognition. In The 3rd IAPR/IEEE International Conference on Biometrics, Italy.Google Scholar
- Boulgouris, N.V., Chi, Z.X., 2007 “Gait recognition using radon transform and linear discriminant analysis,” IEEE Transactions on Image Processing 16(3): 731–740, March 2007.CrossRefGoogle Scholar
- Boulgouris, N.V., K.N. Plataniotis, and D. Hatzinakos. 2004. Gait recognition using dynamic time warping. In IEEE 6th Workshop on Multimedia Signal Processing, 263–266, September 29–October 1, 2004.Google Scholar
- Boulgouris, N.V., D. Hatzinakos, and K.N. Plataniotis. 2005. Gait recognition: A challenging signal processing technology for biometric identification. IEEE Signal Processing Magazine 22(6): 78–90.CrossRefGoogle Scholar
- Bowyer, K.W., K. Hollingsworth, and P.J. Flynn. 2008. Image understanding for iris biometrics: A survey. Computer Vision and Image Understanding 110(2): 281–307.CrossRefGoogle Scholar
- Chen, C., J. Liang, H. Zhao, H. Hu, and J. Tian. 2009. Frame difference energy image for gait recognition with incomplete silhouettes. Pattern Recognition Letters 30(11): 977–984.CrossRefGoogle Scholar
- Cucchiara, R., C. Grana, M. Piccardi, A. Prati, and S. Sirotti. 2001. Improving shadow suppression in moving object detection with HSV color information. In 2001 IEEE Intelligent Transportation Systems Proceedings, 334–339.Google Scholar
- Daras, P., D. Zarpalas, D. Tzovaras, and M.G. Strintzis. 2006. Efficient 3-D model search and retrieval using generalized 3-D radon transforms. IEEE Transactions on Multimedia 8(1): 101–114.CrossRefGoogle Scholar
- Federspiel L. Sensor mat for a vehicle seat. I.E.E. International Electronics & Engineering S.a.r.l. Patent, US6794590, Sept. 2004.Google Scholar
- Ferro, M., G. Pioggia, A. Tognetti, N. Carbonaro, and D. De Rossi. 2009. A sensing seat for human authentication. Transactions on Information Forensics and Security 4(3): 451–459.CrossRefGoogle Scholar
- Ford Global Technologies Inc. Vehicle air bag deployment dependent on sensing seat and pedal positions. Patent, priorities: [US09681903 Jun. 22, 2001], UKC Headings: G4N Int Cl7 B60R 21/01, B60R 21/16, GB2377536 (GB0212617.5), May 2002.Google Scholar
- Gloor, P.A. 1980. Bertillon’s method and anthropological research; A new use for old anthropometric files. Journal of the Forensic Science Society 20(2): 99–101. ISSN 0015–7368.CrossRefGoogle Scholar
- Goffredo, M., J.N. Carter, and M.S. Nixon. 2008. Front-view gait recognition. In IEEE Second International Conference on Biometrics: Theory, Applications and Systems, BTAS.Google Scholar
- Hilliard G.G. Seat cushion. Patent, GB0228513.8, Dec. 2002.Google Scholar
- Ioannidis, D., D. Tzovaras, I.G. Damousis, S. Argyropoulos, and K. Moustakas. 2007. Gait recognition using compact feature extraction transforms and depth information. IEEE Transaction Information Forensics and Security 2: 623–630.CrossRefGoogle Scholar
- Jain, A.K., A. Ross, and S. Prabhakar. 2004. An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology 14(1): 4–20.CrossRefGoogle Scholar
- Jean, F., Alexandra Branzan Albu, and Robert Bergevin. 2009. Towards view-invariant gait modeling: Computing view-normalized body part trajectories. Pattern Recognition 42(11): 2936–2949.CrossRefGoogle Scholar
- Lorussi, F., W. Rocchia, E.P. Scilingo, A. Tognetti, and D. De Rossi. 2004. Wearable redundant fabric-based sensors arrays for reconstruction of Body segment posture. IEEE Sensors Journal 4(6): 807–818.CrossRefGoogle Scholar
- Lorussi, F., E.P. Scilingo, M. Tesconi, A. Tognetti, and D. De Rossi. 2005. Strain sensing fabric for hand posture and gesture monitoring. IEEE Transactions on Information Technology in Biomedicine 9(3): 372–381.CrossRefGoogle Scholar
- Mademlis, A., A. Axenopoulos, P. Daras, D. Tzovaras, and M.G. Strintzis. 2006. 3D content-based search based on 3D Krawtchouk moments. In 3DPVT 2006, University of North Carolina, Chapel Hill, NC, USA, June 2006.Google Scholar
- Moustakas, K., D. Tzovaras, and M.G. Strintzis. 2007. SQ-Map: Efficient layered collision detection and haptic rendering. IEEE Transactions on Visualization and Computer Graphics 13(1): 80–93.CrossRefGoogle Scholar
- Salembier, P., and F. Marqués. 1999. Region-based representations of image and video: Segmentation tools for multimedia services. IEEE Transactions on Circuits and Systems for Video Technology 9(8): 1147–1169.CrossRefGoogle Scholar
- Sarkar, S., P.J. Phillips, Z. Liu, I.R. Vega, P. Grother, and K.W. Bowyer. 2005. The human ID gait challenge problem: Data sets, performance, and analysis. IEEE Transaction Pattern Analysis and Machine Intelligence 27(2): 162–177.CrossRefGoogle Scholar
- Scilingo, E.P., F. Lorussi, A. Mazzoldi, and D. De Rossi. 2003. Sensing fabrics for wearable kinaesthetic-like systems. IEEE Sensors Journal 3(4): 460–467.CrossRefGoogle Scholar
- Tan, H.Z., L.A. Slivovsky, and A. Pentland. 2001. A sensing chair using pressure distribution sensors. IEEE/ASME Transactions on Mechatronics 6(3): 261–268.CrossRefGoogle Scholar
- The Johnson Controls Company. http://www.johnsoncontrols.com/. Accessed on 17 Mar 2008.
- The Softswitch Company. http://www.softswitch.co.uk/. Accessed on 17 Mar 2008.
- The Tekscan Company. http://www.tekscan.com. Accessed on 17 Mar 2008.
- The Wacker Company. The grades and properties of Elastosil LR liquid silicon rubber. http://www.wacker.com/internet/webcache/de_DE/_Downloads/EL_LR_Eigensch_en.pdf. Accessed on 17 Mar 2008.
- Zhang, R., C. Vogler, and D. Metaxas. 2007. Human gait recognition at sagittal plane. Image and Vision Computing 25: 321–330.CrossRefGoogle Scholar