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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Condición: Good. *Price HAS BEEN REDUCED by 10% until Monday, June 1 (sale item)* 374 pp., Paperback, ex library, else text clean and binding tight. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Nº de ref. del artículo: ZB720351
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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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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Face as Biometrics.- Face Identification and Verification via ECOC.- Pose-Independent Face Identification from Video Sequences.- Face Recognition Using Independent GaborWavelet Features.- Face Recognition from 2D and 3D Images.- Face Recognition Using Suppo. Nº de ref. del artículo: 4889689
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Face as Biometrics.- Face Identification and Verification via ECOC.- Pose-Independent Face Identification from Video Sequences.- Face Recognition Using Independent GaborWavelet Features.- Face Recognition from 2D and 3D Images.- Face Recognition Using Support Vector Machines with the Feature Set Extracted by Genetic Algorithms.- Comparative Performance Evaluation of Gray-Scale and Color Information for Face Recognition Tasks.- Evidence on Skill Differences of Women and Men Concerning Face Recognition.- Face Recognition by Auto-associative Radial Basis Function Network.- Face Recognition Using Independent Component Analysis and Support Vector Machines .- Face Image Processing.- A Comparison of Face/Non-face Classiffiers.- Using Mixture Covariance Matrices to Improve Face and Facial Expression Recognitions.- Real-Time Face Detection Using Edge-Orientation Matching.- Directional Properties of Colour Co-occurrence Features for Lip Location and Segmentation.- Robust Face Detection Using the Hausdorff Distance.- Multiple Landmark Feature Point Mapping for Robust Face Recognition.- Face Detection on Still Images Using HIT Maps.- Lip Recognition Using Morphological Pattern Spectrum.- A Face Location Algorithm Robust to Complex Lighting Conditions.- Automatic Facial Feature Extraction and Facial Expression Recognition.- Speech as Biometrics and Speech Processing.- Fusion of Audio-Visual Information for Integrated Speech Processing.- Revisiting Carl Bildt's Impostor: Would a Speaker Verification System Foil Him .- Speaker Discriminative Weighting Method for VQ-Based Speaker Identification.- Visual Speech: A Physiological or Behavioural Biometric .- An HMM-Based Subband Processing Approach to Speaker Identification.- Affine-Invariant Visual Features Contain SupplementaryInformation to Enhance Speech Recognition.- Fingerprints as Biometrics.- Recent Advances in Fingerprint Verification.- Fast and Accurate Fingerprint Verification.- An Intrinsic Coordinate System for Fingerprint Matching.- A Triplet Based Approach for Indexing of Fingerprint Database for Identification.- Twin Test: On Discriminability of Fingerprints.- An Improved Image Enhancement Scheme for Fingerprint Minutiae Extraction in Biometric Identification.- An Analysis of Minutiae Matching Strength.- Curvature-Based Singular Points Detection.- Algorithm for Detection and Elimination of False Minutiae in Fingerprint Images.- Fingerprint Classification by Combination of Flat and Structural Approaches.- Using Linear Symmetry Features as a Pre-processing Step for Fingerprint Images.- Fingerprint Classification with Combinations of Support Vector Machines.- Performance Evaluation of an Automatic Fingerprint Classification Algorithm Adapted to a Vucetich Based Classification System.- Quality Measures of Fingerprint Images.- Gait as Biometrics.- Automatic Gait Recognition by Symmetry Analysis.- Extended Model-Based Automatic Gait Recognition of Walking and Running.- EigenGait: Motion-Based Recognition of People Using Image Self-Similarity.- Visual Categorization of Children and Adult Walking Styles.- A Multi-view Method for Gait Recognition Using Static Body Parameters.- New Area Based Metrics for Gait Recognition.- Hand, Signature, and Iris as Biometrics.- On-Line Signature Verifier Incorporating Pen Position, Pen Pressure, and Pen Inclination Trajectories.- Iris Recognition with Low Template Size.- RBF Neural Networks for Hand-Based Biometric Recognition.- Hand Recognition Using Implicit Polynomials and Geometric Features.- Multi-modal Analysis and System Integration.- IncludingBiometric Authentication in a Smart Card Operating System.- Hybrid Biometric Person Authentication Using Face and Voice Features.- Information Fusion in Biometrics.- PrimeEye: A Real-Time Face Detection and Recognition System Robust to Illumination Changes.- A Fast Anchor Person Searching Scheme in News Sequences.Springer-Verlag KG, Sachsenplat. Nº de ref. del artículo: 9783540422167
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