Techniques, Information Sources, and Current Progress in Vision-Based Hand Gesture Recognition for HCI Systems

Abstract

According to computer vision, the recognition of hand gestures is regarded as an important area of research that has a number of applications in the realm of human-computer interaction (HCI). The ability to recognize gestures is extremely beneficial in a variety of sectors, including but not limited to sign language, healthcare, virtual and augmented reality, and others. The primary objective of a job opportunity   The collection of raw data is the primary objective of the Human-Computer Interaction (HCI) architecture that is based on hand gestures. This objective can be accomplished largely through the utilization of sensor-based or vision-based technologies. In order to extract information using the sensor-based technique, it is required to either use equipment or physically link the sensors to the user's arm or hand. This is the only way to accomplish this. On the other hand, designs that rely on vision necessitate the utilization of a fixed or video camera in order to record images or movies that demonstrate the movements of the hand.  The following part will provide a concise overview of sensor-based data gathering methods, and then proceed to concentrate primarily on the recognition of hand gestures based on vision. The purpose of this study is to provide a description of the primary techniques that are utilized in human-computer interaction (HCI) for the purpose of recognizing hand gestures based on visual information. The primary topics that are covered in this course are the various classifications of gestures, the techniques that can be used to acquire gestures, the main challenges that are encountered by gesture recognition systems, and the step-by-step processes of acquisition, detection, pre-processing, representation and feature extraction, and recognition. This article presents a comprehensive compilation of databases, as well as an analysis of the most recent advancements and applications of systems that are based on hand gestures. The purpose of this article is to provide a comprehensive overview of feature extraction as well as the primary classification algorithms that are prevalent today, including deep learning techniques. The categorization of the many schemes and approaches that are utilized throughout the various phases of the gesture recognition system is given a particular amount of importance. The purpose of this is to aid in the development of future research in this area and to enhance comprehension of the subject matter.

Keywords. Human–computer interaction (HCI) · Vision-based gesture recognition (VGR) · Static and dynamic gestures · Deep learning methods