@article{oai:kyutech.repo.nii.ac.jp:00004729,
 author = {Ahsan, Sk. Md. Masudul and Tan, Joo kooi and タン, ジュークイ and Kim, Hyungseop and 金, 亨燮 and 石川, 聖二 and Ishikawa, Seiji},
 issue = {6},
 journal = {International Journal of Innovative Computing, Information and Control},
 month = {Dec},
 note = {The motion sequences of human actions have its own discriminating profile that can be represented as a spatiotemporal template like Motion History Image (MHI). A histogram is a popular statistic to present the underlying information in a template. In this paper a histogram oriented action recognition method is presented. In the proposed method, we use the Directional Motion History Images (DMHI), their corresponding Local Binary Pattern (LBP) images and the Motion Energy Image (MEI) as spatiotemporal template. The intensity histogram is then extracted from those images which are concatenated together to form the feature vector for action representation. A linear combination of the histograms taken from DMHIs and LBP images is used in the experiment. We evaluated the performance of the proposed method along with some variants of it using the renowned KTH action dataset and found higher accuracies. The obtained results justify the superiority of the proposed method compared to other approaches for action recognition found in literature.},
 pages = {1855--1867},
 title = {Human action representation and recognition: An approach to histogram of spatiotemporal templates},
 volume = {11},
 year = {2015}
}