Path: Top -> Journal -> Jurnal Internasional -> King Saud University -> 2020 -> Volume 32, Issue 3, March
Gait-based human recognition using partial wavelet coherence and phase features
Oleh : Sagar Arun More, Pramod Jagan Deore, King Saud University
Dibuat : 2020-03-30, dengan 1 file
Keyword : Gait recognition, Wavelet coherence, Partial wavelet coherence
Url : http://www.sciencedirect.com/science/article/pii/S1319157817301362
Sumber pengambilan dokumen : Web
In this paper, a multi-view human gait recognition method which utilizes Partial Wavelet Coherence (PWC) as a novel feature is proposed. The Euclidean distance representation of PWC of the 1D signals generated due to movements of hands, legs, shoulders from multi-view gait sequences preserves the spatio-temporal information of walking individual. This method directly extracts the dynamic information without using any model. We got average recognition accuracy when considered only PWC feature. Further, we investigate Phase Feature (PF) which also preserves discriminant information of dynamic phase angle between body parts. When PF considered additionally with PWC feature the system performance improved significantly and average recognition accuracy reported.
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|---|---|
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| Organisasi | King Saud University |
| Nama Kontak | Herti Yani, S.Kom |
| Alamat | Jln. Jenderal Sudirman |
| Kota | Jambi |
| Daerah | Jambi |
| Negara | Indonesia |
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