Abstract
Gesture recognition technology based on visual detection to acquire gestures information is obtained in a non-contact manner. There are two types of gesture recognition: independent and continuous gesture recognition. The former aims to classify videos or other types of gesture sequences that only contain one isolated gesture instance in each sequence (e.g., RGB-D or skeleton data). In this study, we review existing research methods of visual gesture recognition and will be grouped according to the following family: static, dynamic, based on the supports (Kinect, Leap…etc), works that focus on the application of gesture recognition on robots and works on dealing with gesture recognition at the browser level. Following that, we take a look at the most common JavaScript-based deep learning frameworks. Then we present the idea of defining a process for improving user interface control based on gesture recognition to streamline the implementation of this mechanism.
Highlights
Understanding and classifying gestures from human gestural data is referred to as gesture recognition
Since the classes are identified ahead of time, gesture recognition is achieved by supervised learning, in which a supervisor modifies the training data collection, defining gestural instances and the corresponding class details for each gesture instance
This paper summarizes the following technical difficulties, which are used as a guideline for relevant scientific research personnel, in order to improve the way of humancomputer interaction using gesture recognition
Summary
Understanding and classifying gestures from human gestural data is referred to as gesture recognition. Individual and distinct gestures are groups, and gestural instances containing gesture-data are instances, so gesture recognition is generally a pattern classification issue. There are both conventional and machine learning approaches to gesture recognition. A machine learning approach entails creating a mapping feature from gestural data to gestureclasses. As an important human-computer interaction method, gesture control provides people with a natural and intuitive way of communication. It has been initially used in the entertainment industry and it has strong practicability in robot control [1]. This article addresses the problems and drawbacks of gesture recognition, as well as potential future research directions
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