Abstract
We present a parametric method to automatically identify people in monocular low-resolution video by estimating the height and stride parameters of their walking gait. Stride parameters (stride length and cadence) are functions of body height, weight, and gender. Previous work has demonstrated effective use of these biometrics for identification and verification of people. In this paper, we show that performance is significantly improved by using height as an additional discriminant feature. Height is estimated by robustly segmenting the person from the background and fitting their apparent height to a time-dependent model. This method is correspondence-free and works with low-resolution images of people. It is also view-invariant, albeit performance is optimal in near fronto-parallel configurations. Identification accuracy is estimated at 47% for fronto-parallel sequences of 41 people, and 65% for non-fronto-parallel sequences of 17 people, compared with 18% and 51%, respectively, when only stride and cadence are used.
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References
Cattin, P.C., Zlatnik, D., Borer, R.: Biometric system using human gait. In: Mechatronics and Machine Vision in Practice. (2001)
Hayfron-Acquah, J.B., Nixon, M.S., Carter, J.N.: Recognising human and animal movement by symmetry. In: AVBPA. (2001)
Johansson, G.: Visual perception of biological motion and a model for its analysis. Perception and Psychophysics 14 (1973)
Cutting, J., Kozlowski, L.: Recognizing friends by their walk: Gait perception without familiarity cues. Bulletin Psychonomic Soc. 9 (1977) 353–356
Barclay, C., Cutting, J., Kozlowski, L.: Temporal and spatial factors in gait perception that influence gender recognition. Perception and Psychophysics 23 (1978) 145–152
Inman, V., Ralston, H.J., Todd, F.: Human Walking. Williams and Wilkins (1981)
Winter, D.: The Biomechanics and Motor Control of Human Gait. Univesity of Waterloo Press (1987)
Perry, J.: Gait Analysis: Normal and Pathological Function. SLACK Inc. (1992)
Niyogi, S., Adelson, E.: Analyzing and recognizing walking figures in XYT. In: CVPR. (1994)
Murase, H., Sakai, R.: Moving object recognition in eigenspace representation: gait analysis and lip reading. PRL 17 (1996)
Little, J., Boyd, J.: Recognizing people by their gait: the shape of motion. Videre 1 (1998)
Huang, P.S., Harris, C.J., Nixon, M.S.: Comparing different template features for recognizing people by their gait. In: BMVC. (1998)
He, Q., Debrunner, C.: Individual recognition from periodic activity using hidden markov models. In: IEEE Workshop on Human Motion. (2000)
BenAbdelkader, C., Cutler, R., Davis, L.: Eigengait: Motion-based recognition of people using image self-similarity. In: AVBPA. (2001)
Cunado, D., Nixon, M., Carter, J.: Gait extraction and description by evidence gathering. In: AVBPA. (1999)
Yam, C., Nixon, M.S., Carter, J.N.: Extended model-based automatic gait recognition of walking and running. In: AVBPA. (2001)
Johnson, A., Bobick, A.: Gait recognition using static activity-specific parameters. In: CVPR. (2001)
Yasutomi, S., Mori, H.: A method for discriminating pedestrians based on rythm. In: IEEE/RSG Intl Conf. on Intelligent Robots and Systems. (1994)
Cutler, R., Davis, L.: Robust real-time periodic motion detection, analysis and applications. PAMI 13 (2000)
Song, Y., Feng, X., Perona, P.: Towards detection of human motion. In: CVPR. (2000)
Campbell, L.W., Bobick, A.: Recognition of human body motion using phase space constraints. In: ICCV (1995)
Meyer, D., Psl, J., Niemann, H.: Gait classification with hmms for trajectories of body parts extracted by mixture densities. In: BMVC. (1998)
Davis, J.W.: Visual categorization of children and adult walking styles. In: AVBPA. (2001)
Elgammal, A., Harwood, D., Davis, L.: Non-parametric model for background subtraction. In: ICCV. (2000)
Haritaoglu, I., Harwood, D., Davis, L.: W4s: A real-time system for detecting and tracking people in 21/2 d. In: ECCV. (1998)
BenAbdelkader, C., Cutler, R., Davis, L.: Stride and cadence as a biometric in automatic person identification and verification. In: FGR. (2002)
Rose, J., Gamble, J.G.: Human Walking. Williams and Wilkins (1994)
Murray, M., Kory, C., Clarkson, B.H., Sepic, S.B.: Comparison of free and fast speed walking patterns of normal men. American Journal of Physical Medicine 45 (1966)
Bloomfield, P.: Fourier Analysis of Time Series: an Introduction. John Wiley and Sons (1976)
Bevington, P.R., Robinson, D.K.: Data reduction and error analysis for the physical sciences. McGraw-Hill (1992)
Grieve, D.W., Gear, R.: The relationship between length of stride, step frequency, time of swing and speed of walking for children and adults. Journal of Ergonomics 5 (1966)
Zatsiorky, V.M., Werner, S.L., Kaimin, M.A.: Basic kinematics of walking. Journal of Sports Medicine and Physical Fitness 34 (1994)
Fukunaga, K.: Introduction to Statistical Pattern Recognition. New York Academic Press (1990)
Philips, J., Hyeonjoon, Rizvi, S., Rauss, P.: The feret evaluation methodology for face recognition algorithms. PAMI 22 (2000)
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BenAbdelkader, C., Cutler, R., Davis, L. (2002). View-invariant Estimation of Height and Stride for Gait Recognition. In: Tistarelli, M., Bigun, J., Jain, A.K. (eds) Biometric Authentication. BioAW 2002. Lecture Notes in Computer Science, vol 2359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47917-1_16
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DOI: https://doi.org/10.1007/3-540-47917-1_16
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