Abstract:

We presents a new method for human action recognition to solve the problem of representing the invariant property of the moving target, which combining the local motion pattern and kernel principal component analysis. Firstly, using the local motion pattern descriptors to represent the human motion and then using the kernel principal component analysis algorithm to deal with the local motion pattern descriptors to form a new feature description. The experimentshows that human actionrecognition based on LMP-KPCA, with the other two classical methods (Cuboids+SVM and LMP+SR)by contrast, the recognition rateis improved obviously, the corresponding improved recognition rate is 1. 1% and 1%.

Key words: human action recognition, space and time interest points, local motion pattern(LMP), kernel principal component analysis(KPCA)