TY - GEN
T1 - Grassmannian locality preserving discriminant analysis to view invariant gait recognition with image sets
AU - Connie, Tee
AU - Michael, Goh Kah Ong
AU - Jin, Andrew Teoh Beng
PY - 2012
Y1 - 2012
N2 - In studies to date, gait recognition across appearance changes has been a challenging task. In this paper, we present a gait recognition method that models the gait image sets as subspaces on the Grassmannian manifold. This formulation provides a convenient way to represent the subspaces as points on the manifold. By using a suitable Grassmannian kernel, the non-linear manifold can be treated as if it were a Euclidean space. This implies that conventional data analysis tool like LDA can be used on this manifold. To this end, we apply a graph based locality preserving discriminant analysis method on the Grassmannian manifold. Experiment results suggest that the proposed method can tolerate variations in appearance for gait identification.
AB - In studies to date, gait recognition across appearance changes has been a challenging task. In this paper, we present a gait recognition method that models the gait image sets as subspaces on the Grassmannian manifold. This formulation provides a convenient way to represent the subspaces as points on the manifold. By using a suitable Grassmannian kernel, the non-linear manifold can be treated as if it were a Euclidean space. This implies that conventional data analysis tool like LDA can be used on this manifold. To this end, we apply a graph based locality preserving discriminant analysis method on the Grassmannian manifold. Experiment results suggest that the proposed method can tolerate variations in appearance for gait identification.
UR - http://www.scopus.com/inward/record.url?scp=84873331864&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84873331864&partnerID=8YFLogxK
U2 - 10.1145/2425836.2425913
DO - 10.1145/2425836.2425913
M3 - Conference contribution
AN - SCOPUS:84873331864
SN - 9781450314732
T3 - ACM International Conference Proceeding Series
SP - 400
EP - 405
BT - Proceedings of IVCNZ 2012 - The 27th Image and Vision Computing New Zealand Conference
T2 - 27th Image and Vision Computing New Zealand Conference, IVCNZ 2012
Y2 - 26 November 2012 through 28 November 2012
ER -