2 May 2019: Gesture recognition has already made its foothold in gaming and media markets and is currently spreading its wings across various other sectors. It can be seen as a way for computers to understand human body language, therefore bridging the gap between humans and machines as compared to primitive text user interfaces and graphical user interfaces (GUIs).
This technology is catering to numerous business needs but is accompanied with major shortcomings. The available solutions offer very less or no flexibility as these are tightly coupled with corresponding hardware. Most of these devices come with a pre-defined camera configuration thus, leaving no room for using other customized cameras. As a result, manufacturers are striving to build solutions that can support multiple hardware platforms. Ongoing research and development activities are aimed to bring in alternatives that can comply with targeted OEM norms like medical, automobile, and educational sectors.
Constructing the System
Machine learning is the primary technology used for designing gesture recognition devices and has emerged as a stepping stone to processing images and creating the desired features. Kinect sensor developed by Microsoft can detect motion of an object with sensor depth ranging from 800mm to 4000mm. It has successfully cut down cost barriers owing to its affordable depth mapping sensors. Another product in the market is the Myo wrist band, is a wireless device, known for its touch-less visual entertainment features. It has been increasingly adopted in hospitals, sports business, and entertainment sectors.
Even though self-driving cars still have a long way to go, artificial intelligence is making breakthrough achievement in taking over driver controls. Waymo self-driving car can identify appropriate traffic cop hand gestures or signals by taking control of the vehicle and disengaging driver inputs. Ultigesture has developed a new level of interaction that uses the driver’s arm movements and creates a natural and connected driving experience with no bulky controller.
Market Insights:
The competitive landscape showcases the profiles and business strategies of the major players, along with their recent developments. Some of the major contenders operating in the market consist of GestureTek technologies; OmniVision Technologies, Inc.; Cognitec Systems GmbH; Infineon Technologies AG; PointGrab; eyeSight Technologies Ltd.; SOFTKINETIC; Elliptic Laboratories A/S; Crossmatch; Intel Corporation; Qualcomm Technologies; Microchip Technology Inc.; Google, Inc.; and Sony Corporation among others.
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