Background and Objectives: Action recognition, as the processes of labeling an unknown action of a query video, is a challenging problem, due to the event complexity, variations in imaging conditions, and intra- and inter-individual action-variability. A number of solutions proposed to solve action recognition problem. Many of these frameworks suppose that each video sequence includes only one ...

exploiting multimodal information like acceleration and heart rate is a promising method to achieve human action recognition. a semi-supervised action recognition approach aucc (action understanding with combinational classifier) using the diversity of base classifiers to create a high-quality ensemble for multimodal human action recognition is proposed in this paper. furthermore, both labeled ...

Recognition in planning seeks to find agent intentions, goals or activities given a set of observations and knowledge library (e.g. goal states, plans domain theories). In this work we introduce the problem Online Action Recognition. It consists recognizing, an open world, action that best explains partially observable state transition from first-order STRIPS actions, which is initially empty. ...

Due to the compact and rich high-level representations offered, skeleton-based human action recognition has recently gained more attraction. Although joint relationships investigation in spatial temporal dimensions provides effective information critical recognition, effectively encoding global dependencies of joints during spatio-temporal feature extraction is a prohibitive task. In this paper...

human action recognition is an important problem in computer vision. one of the methods that are recently used is sparse coding. conventional sparse coding algorithms learn dictionaries and codes in an unsupervised manner and neglect class information that is available in the training set. but in this paper for solving this problem, we use a discriminative sparse code based on multi-manifolds. ...