This paper surveys the state of the art on multimodal gesture recognition and introduces the
JMLR special topic on gesture recognition 2011–2015. We began right at the start of the …

Gesture recognition has attracted considerable attention owing to its great potential in
applications. Although the great progress has been made recently in multi-modal learning …

This paper reviews the historic of ChaLearn Looking at People (LAP) events. We started in
2011 (with the release of the first Kinect device) to run challenges related to human …

In this paper, we tackle the continuous gesture recognition problem with a two streams
Recurrent Neural Networks (2S-RNN) for the RGB-D data input. In our framework, the …

In this article, to utilize long-term dynamics over an isolated sign sequence, we propose a
covariance matrix--based representation to naturally fuse information from multimodal …

Within the context of assistive robotics we develop an intelligent interface that provides
multimodal sensory processing capabilities for human action recognition. Human action is …

Gesture and sign language recognition in a continuous video stream is a challenging task,
especially with a large vocabulary. In this work, we approach this as a framewise …

Human-machine interaction has been around for several decades now, with new
applications emerging every day. One of the major goals that remain to be achieved is …

Visual sign language recognition is an interesting and challenging problem. To create a
discriminative representation, a hierarchical Grassmann covariance matrix (HGCM) model is …

Music transcription, which deals with the conversion of music sources into a structured
digital format, is a key problem for Music Information Retrieval (MIR). When addressing this …