The global gesture recognition market is expected to reach value of US$ 51.3 Bn by the end of 2031
Analysts’ Viewpoint on Global Gesture Recognition Market Scenario
The development of more accurate accelerometers, infrared cameras, and associated technologies has resulted in the accelerated use of gesture recognition systems. Touchless gesture recognition includes the use of various techniques such as motion sensor fusion, camera-based gesture, proximity touchscreen, short-range wireless, eye-tracking, voice recognition, etc. Companies operating in the gesture recognition market are focusing on high-growth applications such as automotive, consumer electronics, and healthcare to keep their businesses growing post the COVID-19 pandemic. In addition, the market is estimated to grow, owing to advancements in technology such as AI/ML, IoT, big data, Natural User Interface (NUI), etc., and increasing rate of adoption of gesture recognition technology in end-user segments.
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Gesture recognition is a mathematical conversion of the human movement or gesture into a machine command. The technology enables anyone to interact with a machines using human gestures and movements such as hand, finger, arm, head, or complete body movement. It enables users to operate and control devices using only their hands, without the usage of physical devices such as touch panels, keyboards, or mouse. For instance, users can, move a cursor by pointing their finger at a screen.
The global gesture recognition market is likely to grow due to its favorable properties such as touchless control and higher safety specifically for applications in automotive and consumer electronics.
The global automotive sensors market is estimated to reach the value of US$ 11.7 Bn by 2023, owing to the increasing demand for safety and security in automobiles. Automotive Gesture Recognition Systems (AGRS) offer high accuracy, and enhance vehicle control and safety. These systems can use human touch or other gestures to start and complete the required activity. Increasing safety standards and initiatives to prevent driver distraction are only a few aspects to consider while designing and installing an automotive gesture recognition system.
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The integration of electronics in vehicles has increased due to the rising demand for additional vehicle infotainment (entertainment and informative features such as video players and GPS) and safety features (e.g., backup cameras and sensors). These new components contribute around 30% to 35% to a vehicle’s total cost, which is expected to reach 50% by 2030. As gesture control is part of vehicles electronics, inclusion of electronics into vehicles would have an impact on the gesture recognition market.
The automotive gesture recognition system reads and interprets hand movements as commands using sensors, which enables the driver and passengers to interact with the car usually to control the infotainment system without touching any buttons or screens in the vehicle.
The increased demand for luxury cars equipped with modern intelligent driving assistance, infotainment, and newly incorporated safety features and electronics control units is boosting the use of automotive electronics. Consequently, automakers are focusing on incorporating new features to their vehicles, and gesture recognition is a key feature being added.
For instance, touchless sensing gesture recognition helps reduce driver distraction and improves safety. Thus, more intuitive control can be also utilized for a wider range of car functions. Maxim Integrated Products, Inc. introduced the next generation of its infrared-based dynamic optical sensor, which is able to sense a broader range of gestures at extended distances. The MAX25405 detects a wider proximity of movement and doubles the sensing range to 40 cm, as compared to earlier generations, all in a quarter of the size and at 10x lower cost than time-of-flight (ToF) camera-based systems that are utilized in automotive, industrial, and consumer applications. These enhancements offer an alternative to voice communications, thereby enabling drivers to focus on the road.
Consumer electronics, such as gaming consoles, interactive devices, digital signage, and commercial automation account for more than half of the share of the global gesture recognition market. The gesture recognition technology has been considered to be a highly successful technology, as it ultimately saves time when interacting with a device. Internet of Things, or IoT, is a developed version of the Internet that connects sensors, consumer electrical devices, and other embedded systems remote access, in addition to computers, smartphones, and tablets, in order to gather and share data. The IoT technology can also be utilized to develop a smart home concept, which includes Gesture Recognition Smart TV that provides intelligence and comfort and consequently, improves the quality of life. For instance, with Google Assistant and Alexa built in, TCL AI TVs offer an AI solution for home life. One can easily control the TV and other home devices just with your voice.
Home automation refers to the use of remote control, the internet, speech, and gestures to operate appliances. Human-computer interaction (HCI) is the technology of computers and humans understanding each other’s language and creating a user-friendly interface. HCI uses wireless interface controlled by gestures, a non-verbal means of communication. The market for home automation is predicted to grow at a steady pace to reach a value of US$ 124.1 Bn by 2027, from a value of US$ 69 Bn in 2018.
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In 2018, in a survey of 1,000 U.S. households conducted by Alarm.com, a U.S.-based technology company, revealed that almost 48% of participants were excited about smart home solutions; however, 59% were bewildered about the wide variety of products available in the market. The survey participants placed high priority on the security that smart homes would offer and comfort, energy savings come next to security.
The future of gesture recognition includes development of a system that can recognize and use specific human gestures to convey information or control devices. Hand gesture identification is difficult, as various people produce gestures in various ways and at varied speeds. The precision of hand detection remains an issue for hand gesture identification. Several algorithms have been proposed to improve the accuracy of gesture recognition.
Consistent rise in population, improving purchasing power of people, and technological advancements are fueling the demand for smart electronics, which, in turn, is propelling the demand for gesture recognition.
