Since the inception of machines, humans have always tried to maneuver them to run in alignment with human intentions. During the initial stages of machine development, switches and joysticks, etc. were used to control a machine’s functionality. However, in the era of computers, the human-machine interface (HMI) environment has become increasingly user-friendly, empowering individuals to convey information to machines via input devices like mouse and keyboard while also keeping a track of their operations via the display. In recent years, there has been a trend of computers decreasing in size, but with significant enhancements in their operating efficiency. The basic input signals can command machines to autonomously execute complex tasks through programming. Building upon this technology, researchers have invented several human-computer interaction technologies like gesture recognition, brain-computer interaction, and voice control. 

Hand gestures, being a crucial means for humans to communicate information and express intuitive intentions to machines, possess numerous advantages, including high flexibility, and strong intuition. Hence, hand gesture recognition (HGR) is extensively utilized and developed as a Human-Machine Interface (HMI) technology. 

As per the Fortune Business Insights report in 2022, the global gesture recognition market reached a size of USD 15.19 billion. It is projected to grow from USD 19.37 billion in 2023 to USD 115.70 billion by 2030, with a compound annual growth rate (CAGR) of 29.1% during the forecast period. In 2022, North America held the largest market share globally, accounting for 37.66%. 

Source: Fortune Business Insights 

When analyzed per application, the human-computer interaction segment commands the largest global share and is projected to maintain the highest CAGR during the forecast period. This is attributed to its numerous advantages, which improve the user experience and interaction with technology, with enhanced usability and accessibility. 

Source: Fortune Business Insights 

What is Gesture recognition 

Gesture recognition is a technology that refers to the use of cameras, haptic devices, and various sensors to capture, recognize, and interpret physical human gestures and movements in real time. Typically, these gestures are characterized by simple movements, such as vertical and horizontal arm movements, hand waves, or arm swipes. However, modern gesture recognition systems can identify subtle and intricate movements, including gentle swipes, individual finger motions, and pinching actions. 

Gesture recognition can enable natural and intuitive interaction between humans and their systems in circumstances where the use of a mouse, keyboard, voice control, and other input devices is not practical or convenient. This technology has a diverse range of applications across various industries, including human-computer interaction, virtual reality, gaming, and robotics. Its implementation enables businesses to enhance user experiences, facilitate more immersive interactions, and produce intuitive control mechanisms. 

In manufacturing and industrial environments, gesture recognition plays a vital role in automating processes to manage robots and machinery. This enhances operational efficiency and lowers the dependency on physical buttons or controls, thereby improving the safety of the workers. 

How it works 

Gesture recognition passes on the real-time input data to the computer so it can acknowledge the user’s command. The device’s motion detectors analyze gestures, which are then used as the primary source of input data. The gesture recognition systems combine both 3D depth sensing and infrared cameras along with machine learning algorithms. Machine learning systems are trained using deep images of hand notation and enable them to detect the correct position of hands and fingers. 

It consists of three basic levels: 

• Detection: The advanced imaging device tracks hand and finger movements, while the machine learning algorithm processes the captured image to identify edges and finger positions. 

• Tracking: The device captures each movement and provides the correct input for data analysis. 

• Recognition: The system analyzes the patterns based on the data analysis, and upon finding an exact match, it performs the action associated with the recognized gesture. 

Several growing factors contribute to the growth of the market 

• Adoption of smart devices: The increasing popularity and use of smart devices like smartphones, tablets, and wearables in recent years are increasing the demand for gesture recognition systems. These devices are commonly utilized in the hands-free mode, which makes gesture recognition seamless and an effective method for interaction between humans and devices. 

• Evolution of sensor technology: The advancement in sensor technologies is enhancing the accuracy and reliability of gesture recognition. As a result, there is a growing adaptation of gesture recognition across various applications. 

• Increasing demand for contactless interfaces: The gesture recognition system provides a touch-free method to interact with devices, improving both convenience and accessibility. 

eInfochips has several years of experience in delivering comprehensive industrial automation solutions, including HMI development, robotics, connected camera and vision solutions, and sensor integration, to various industries. Leveraging an extensive technology partnership with big tech players like Qualcomm, NVIDIA, and NXP, eInfochips has served many customers with cutting-edge innovation and provided end-to-end service to our valued clients.