Manifold Learning Based Gait Feature Reduction and Recognition
The moving objectives' images are in tensor format in reality. That using for reference the thought of tensor space dimension reduction to gain the optimal gait characters with low dimension inaugurate a new gait recognition way. A novel gait expression and recognition algorithm based on the tensor space is introduced here. It is a tensor space learning algorithm that could investigate the inherent geometrical structure of the data manifold. The within-class and the between-class similarity graphs are respectively defined so as to preserve the local structure of the manifold and the global data information. It improves the ability of gait data reconstructing and the recognizing efficiency.