Distillation of human–object interaction contexts for action recognition

Action and interaction as contexts for enriching representations

Manipulative Action Recognition for Human-Robot Interaction

Recently, human-robot interaction is receiving more and more interest in the robotics as well as in the computer vision research community. From the robotics perspective, robots that cooperate with humans are an interesting application field that is expected to have a high future market potential. A couple of global and also mid-sized companies have come up with quite sophisticated robotic plat...

Contexts for Human Action

We argue that the mathematics developed for the semantics of computer languages can be fruitfully applied to problems in human communication and action.

Informative joints based human action recognition using skeleton contexts

The launching of Microsoft Kinect with skeleton tracking technique opens up new potentials for skeleton based human action recognition. However, the 3D human skeletons, generated via skeleton tracking from the depth map sequences, are generally very noisy and unreliable. In this paper, we introduce a robust informative joints based human action recognition method. Inspired by the instinct of th...

Deep Alternative Neural Network: Exploring Contexts as Early as Possible for Action Recognition

Contexts are crucial for action recognition in video. Current methods often mine contexts after extracting hierarchical local features and focus on their high-order encodings. This paper instead explores contexts as early as possible and leverages their evolutions for action recognition. In particular, we introduce a novel architecture called deep alternative neural network (DANN) stacking alte...