We investigate dynamical models of human motion that can
support both synthesis and analysis tasks. Unlike coarser
discriminative models that work well when action classes are ...
Abstract This paper focuses on human behavior recognition where the main problem is to bridge the semantic gap between the analogue observations of the real world and the symbolic ...
We consider the fully automated recognition of actions in uncontrolled environment. Most existing work relies on domain knowledge to construct complex handcrafted features from in...
In this paper, we propose a novel Spatiotemporal Interest Point (MC-STIP) detector based on the coherent motion pattern around each voxel in videos. Our detector defines the local...
— Recent development of information technology is making electric household appliances computerized and networked. If the environments surrounding us could recognize our activiti...