A Review of Temporal Aspects of Hand Gesture Analysis Applied to Discourse Analysis and Natural Conversation

TL;DR

This paper reviews how temporal features of hand gestures are analyzed in natural conversation and discourse, emphasizing methods, applications, and the use of machine learning in recent research.

Contribution

It provides a systematic review of temporal analysis methods of hand gestures in natural communication, highlighting recent trends and applications.

Findings

Organized works by analysis type, methods, and applications.

Highlighted the prevalent use of machine learning techniques.

Identified key areas in discourse and psycholinguistic analysis.

Abstract

Lately, there has been an increasing interest in hand gesture analysis systems. Recent works have employed pattern recognition techniques and have focused on the development of systems with more natural user interfaces. These systems may use gestures to control interfaces or recognize sign language gestures, which can provide systems with multimodal interaction; or consist in multimodal tools to help psycholinguists to understand new aspects of discourse analysis and to automate laborious tasks. Gestures are characterized by several aspects, mainly by movements and sequence of postures. Since data referring to movements or sequences carry temporal information, this paper presents a literature review about temporal aspects of hand gesture analysis, focusing on applications related to natural conversation and psycholinguistic analysis, using Systematic Literature Review methodology. In our results, we organized works according to type of analysis, methods, highlighting the use of Machine Learning techniques, and applications.