Gait recognition using fractal scale and wavelet moments. Zhao G Cui L, L., H., &., P., M. In 2006.
abstract   bibtex   
Video-based gait recognition is a challenging problem in computer vision. In this paper, fractal scale wavelet analysis is applied to describe and automatically recognize gait. Fractal scale based on wavelet analysis represents the self-similarity of signals, and improves the flexibility of wavelet moments. Optimal wavelets based on generalized multi-resolution analysis are used to improve the recognition rate. Descriptors of fractal scale are translation, scale and rotation invariant. Moreover, a combination of fractal scale and wavelet moments improves the recognition rate. Experiments show that the proposed descriptor is efficient for gait recognition.
@inProceedings{
 title = {Gait recognition using fractal scale and wavelet moments.},
 type = {inProceedings},
 year = {2006},
 id = {6ea33f17-b76b-349a-a8d3-0b85a079dcc5},
 created = {2019-11-19T13:00:34.877Z},
 file_attached = {false},
 profile_id = {bddcf02d-403b-3b06-9def-6d15cc293e20},
 group_id = {17585b85-df99-3a34-98c2-c73e593397d7},
 last_modified = {2019-11-19T13:46:34.076Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {mvg:728},
 source_type = {inproceedings},
 notes = {Proc. 18th International Conference on Pattern Recognition (ICPR 2006), Hong Kong, 4: 4 p.},
 private_publication = {false},
 abstract = {Video-based gait recognition is a challenging
problem in computer vision. In this paper, fractal scale
wavelet analysis is applied to describe and
automatically recognize gait. Fractal scale based on
wavelet analysis represents the self-similarity of
signals, and improves the flexibility of wavelet
moments. Optimal wavelets based on generalized
multi-resolution analysis are used to improve the
recognition rate. Descriptors of fractal scale are
translation, scale and rotation invariant. Moreover, a
combination of fractal scale and wavelet moments
improves the recognition rate. Experiments show that
the proposed descriptor is efficient for gait recognition.},
 bibtype = {inProceedings},
 author = {Zhao G Cui L, Li H & Pietikäinen M}
}
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