Silhouette history and energy image information for human movement recognition

In this paper, we propose spatio-temporal silhouette representations, called silhouette energy image (SEI) and silhouette history image (SHI) to characterize motion and shape properties for recognition of human movements such as human actions, activities in daily life. The SEI and SHI are constructed by using the silhouette image sequence of an action. The span or difference of the end time and start time is used to make the SHI. For addressing the human shape variability, we used the variation of the anthropometry of the person. We extract the features based on geometric shape moments. We tested our approach successfully in the indoor and outdoor environment. Our experimental results show that the proposed method of human action recognition is robust, flexible and efficient.