We presented an approach for the visual discrimination of children (3-5 years old) from adults using stride-based properties of their walking style. Trajectories of marked head and ankle positions for six children and nine adults were used to compute the relative stride and stride frequency for each walker at di?erent speeds. The distinction between child and adult for these features is quite strong and reduces the task of categorization to a linear discrimination test. Using a trained two-class linear perceptron, we were able to achieve a correct classi?- tion rate of 93-95% for our dataset. Given that only two motion features were used to characterize and di?erentiate children from adults, the result is quite - couraging. The use of natural modes as a means of visual categorization provides a useful bottom-up framework for the classi?cation and recognition of humans in motion. References 1. A. Baumberg and D. Hogg. Learning ?exible models from image sequences. In Proc. European Conf. Comp. Vis. , pages 299-308, 1994. 2. W. Boda, W. Tapp, and T. Findley. Biomechanical comparison of treadmill and overground walking. In Proc. Can. Soc. for Biomech. , pages 88-89, 1994. 3. C. Bregler and J. Malik. Tracking people with twists and exponential maps. In Proc. Comp. Vis. and Pattern Rec. , pages 8-15, 1998. 4. I. Chang and C. Huang. The model-based human body motion analysis system. Image and Vision Comp. , 18(14):1067-1083, 2000. 5. D. Gavrila. Pedestrian detection from a moving vehicle. In Proc. European Conf.
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We presented an approach for the visual discrimination of children (3-5 years old) from adults using stride-based properties of their walking style. Trajectories of marked head and ankle positions for six children and nine adults were used to compute the relative stride and stride frequency for each walker at di?erent speeds. The distinction between child and adult for these features is quite strong and reduces the task of categorization to a linear discrimination test. Using a trained two-class linear perceptron, we were able to achieve a correct classi?- tion rate of 93-95% for our dataset. Given that only two motion features were used to characterize and di?erentiate children from adults, the result is quite - couraging. The use of natural modes as a means of visual categorization provides a useful bottom-up framework for the classi?cation and recognition of humans in motion. References 1. A. Baumberg and D. Hogg. Learning ?exible models from image sequences. In Proc. European Conf. Comp. Vis. , pages 299-308, 1994. 2. W. Boda, W. Tapp, and T. Findley. Biomechanical comparison of treadmill and overground walking. In Proc. Can. Soc. for Biomech. , pages 88-89, 1994. 3. C. Bregler and J. Malik. Tracking people with twists and exponential maps. In Proc. Comp. Vis. and Pattern Rec. , pages 8-15, 1998. 4. I. Chang and C. Huang. The model-based human body motion analysis system. Image and Vision Comp. , 18(14):1067-1083, 2000. 5. D. Gavrila. Pedestrian detection from a moving vehicle. In Proc. European Conf.
This book constitutes the refereed proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication, AVBPA 2001, held in Halmstad, Sweden in June 2001.
The 51 revised papers presented together with three invited papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on face as biometrics; face image processing; speech as biometrics and speech processing; fingerprints as biometrics; gait as biometrics; and hand, signature, and iris as biometrics.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We presented an approach for the visual discrimination of children (3 5 years old) from adults using stride-based properties of their walking style. Trajectories of marked head and ankle positions for six children and nine adults were used to compute the relative stride and stride frequency for each walker at di erent speeds. The distinction between child and adult for these features is quite strong and reduces the task of categorization to a linear discrimination test. Using a trained two-class linear perceptron, we were able to achieve a correct classi - tion rate of 93 95% for our dataset. Given that only two motion features were used to characterize and di erentiate children from adults, the result is quite - couraging. The use of natural modes as a means of visual categorization provides a useful bottom-up framework for the classi cation and recognition of humans in motion. References 1. A. Baumberg and D. Hogg. Learning exible models from image sequences. In Proc. European Conf. Comp. Vis. , pages 299 308, 1994. 2. W. Boda, W. Tapp, and T. Findley. Biomechanical comparison of treadmill and overground walking. In Proc. Can. Soc. for Biomech. , pages 88 89, 1994. 3. C. Bregler and J. Malik. Tracking people with twists and exponential maps. In Proc. Comp. Vis. and Pattern Rec. , pages 8 15, 1998. 4. I. Chang and C. Huang. The model-based human body motion analysis system. Image and Vision Comp. , 18(14):1067 1083, 2000. 5. D. Gavrila. Pedestrian detection from a moving vehicle. In Proc. European Conf. 400 pp. Englisch. Nº de ref. del artículo: 9783540422167
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - We presented an approach for the visual discrimination of children (3 5 years old) from adults using stride-based properties of their walking style. Trajectories of marked head and ankle positions for six children and nine adults were used to compute the relative stride and stride frequency for each walker at di erent speeds. The distinction between child and adult for these features is quite strong and reduces the task of categorization to a linear discrimination test. Using a trained two-class linear perceptron, we were able to achieve a correct classi - tion rate of 93 95% for our dataset. Given that only two motion features were used to characterize and di erentiate children from adults, the result is quite - couraging. The use of natural modes as a means of visual categorization provides a useful bottom-up framework for the classi cation and recognition of humans in motion. References 1. A. Baumberg and D. Hogg. Learning exible models from image sequences. In Proc. European Conf. Comp. Vis. , pages 299 308, 1994. 2. W. Boda, W. Tapp, and T. Findley. Biomechanical comparison of treadmill and overground walking. In Proc. Can. Soc. for Biomech. , pages 88 89, 1994. 3. C. Bregler and J. Malik. Tracking people with twists and exponential maps. In Proc. Comp. Vis. and Pattern Rec. , pages 8 15, 1998. 4. I. Chang and C. Huang. The model-based human body motion analysis system. Image and Vision Comp. , 18(14):1067 1083, 2000. 5. D. Gavrila. Pedestrian detection from a moving vehicle. In Proc. European Conf. Nº de ref. del artículo: 9783540422167
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