We expect a future where we are surrounded by embedded devices, ranging from Java-
enabled cell phones to sensor networks and smart appliances. An adversary can …

This paper presents a computationally efficient method for action recognition from depth
video sequences. It employs the so called depth motion maps (DMMs) from three projection …

Recognizing an action from a sequence of 3D skeletal poses is a challenging task. First,
different actors may perform the same action in various performing styles. Second, the …

In this paper, we study the problem of human action recognition from multiple feature
modalities. We propose bimodal hybrid centroid canonical correlation analysis (BHCCCA) …

This paper aims to determine which is the best human action recognition method based on
features extracted from RGB-D devices, such as the Microsoft Kinect. A review of all the …

Human action recognition methods based on single-modal data lack adequate information.
It is necessary to propose the methods based on multimodal data and the fusion algorithms …

Pose-based action recognition in 3D is the task of recognizing an action (eg, walking or
running) from a sequence of 3D skeletal poses. This is challenging because of variations …

This paper proposes a novel multimodal data classifier named Center Boundary Balancing
Multimodal Classifier (CBBMC) to fuse and classify the spatial and temporal descriptors for …

Hand gesture recognition has many practical applications including human-computer
interfaces. Many depth-based features for dynamic hand gesture recognition task have been …

We address the task of action recognition from a sequence of 3D human poses. This is a
challenging task firstly because the poses of the same class could have large intra-class …