Angular features analysis for gait recognition
Automatic gait recognition is an emergent biometrics notification system for recognizing humans by the way they walk. Its system is non-invasive because it operates from a distance via video cameras. The videos cum image frames are manually labeled to extract angular displacements of high’s and...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
2005
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| Subjects: | |
| Online Access: | http://eprints.utm.my/1582/ http://eprints.utm.my/1582/1/ccsp2.pdf |
| _version_ | 1848890168015060992 |
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| author | Mohd. Isa, Nur Shahidah Sudirman, Rubita Salleh, Sh-Hussain |
| author_facet | Mohd. Isa, Nur Shahidah Sudirman, Rubita Salleh, Sh-Hussain |
| author_sort | Mohd. Isa, Nur Shahidah |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | Automatic gait recognition is an emergent biometrics notification system for recognizing humans by the way they
walk. Its system is non-invasive because it operates from a
distance via video cameras. The videos cum image frames are
manually labeled to extract angular displacements of high’s and lower leg’s rotation, and foot flexion. The angular displacements data is analyzed using standard approach of Principal Component Analysis (PCA) and Canonical Analysis (CA). A cycle extraction procedure consisting of cubic-spline interpolation in SVR (Support Vector machine for Regression) and resampling within zero crossings is performed beforehand for an invariant analysis
due to difference in walking speed of subjects. Combined dataset, is proposed for analyzing features that provide the most variations in gait recognition. Results have shown that the hip accounts for most variations among the three limbs’ displacements data. Also, difference in temporal information of gait’s signal does affect the recognition performance. |
| first_indexed | 2025-11-15T20:37:47Z |
| format | Article |
| id | utm-1582 |
| institution | Universiti Teknologi Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:37:47Z |
| publishDate | 2005 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utm-15822012-01-05T04:51:56Z http://eprints.utm.my/1582/ Angular features analysis for gait recognition Mohd. Isa, Nur Shahidah Sudirman, Rubita Salleh, Sh-Hussain TK Electrical engineering. Electronics Nuclear engineering Automatic gait recognition is an emergent biometrics notification system for recognizing humans by the way they walk. Its system is non-invasive because it operates from a distance via video cameras. The videos cum image frames are manually labeled to extract angular displacements of high’s and lower leg’s rotation, and foot flexion. The angular displacements data is analyzed using standard approach of Principal Component Analysis (PCA) and Canonical Analysis (CA). A cycle extraction procedure consisting of cubic-spline interpolation in SVR (Support Vector machine for Regression) and resampling within zero crossings is performed beforehand for an invariant analysis due to difference in walking speed of subjects. Combined dataset, is proposed for analyzing features that provide the most variations in gait recognition. Results have shown that the hip accounts for most variations among the three limbs’ displacements data. Also, difference in temporal information of gait’s signal does affect the recognition performance. 2005-11-14 Article NonPeerReviewed application/pdf en http://eprints.utm.my/1582/1/ccsp2.pdf Mohd. Isa, Nur Shahidah and Sudirman, Rubita and Salleh, Sh-Hussain (2005) Angular features analysis for gait recognition. 1st Conference on Computers, Communications, and Signal Processing . pp. 236-238. ISSN 1-4244-0012-0 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Mohd. Isa, Nur Shahidah Sudirman, Rubita Salleh, Sh-Hussain Angular features analysis for gait recognition |
| title | Angular features analysis for gait recognition |
| title_full | Angular features analysis for gait recognition |
| title_fullStr | Angular features analysis for gait recognition |
| title_full_unstemmed | Angular features analysis for gait recognition |
| title_short | Angular features analysis for gait recognition |
| title_sort | angular features analysis for gait recognition |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utm.my/1582/ http://eprints.utm.my/1582/1/ccsp2.pdf |