Uddin, Md. ZiaTorresen, JimJabid, Taskeed2019-01-222019-01-222016-10-28IIUC-ICISET2016-ID-168978-1-5090-6121-1978-1-5090-6121-8http://dspace.iiuc.ac.bd:8080/xmlui/handle/88203/529This paper proposes a novel approach for human activity recognition based on body part histograms and Hidden Markov Models. From a depth video frame, body parts are segmented first using a trained random forest. Then, a histogram for each body part is combined to represent histogram features for a depth image. The depth video activity features are then applied on hidden Markov models for training and recognition. The proposed method was superior when compared with other conventional approaches.enDepth ImageHMMHistogramArticle