OmniVision releases ultra small size global shutter image sensor for AR/VR/MR And Metaverse

     OmniVision has unveiled the industry's first and only three-layer stacked BSI Global Shutter (GS) image sensor, the OG0TB. The ultra-small size image sensor for eye and face tracking in AR/VR/MR And Metaverse consumer devices is available in a package size OF just 1.64mm x 1.64mm in a 2.2 micron pixel size and 1/14.46 inch optical format (OF). With a 400x400 resolution and ultra-low power consumption, this CMOS image sensor is ideal for small, lightweight, battery-powered wearables such as eye masks and glasses

     David Shin, senior product marketing manager of OmniVision IoT/Emerging, said: "OmniVision has developed the world's first three-layer stacked global shutter pixel technology, and applied it to the ultra small GS image sensor without sacrificing performance, leading the industry to further develop. We integrate all features and functions into the ultra small 'out of the box' sensor, which helps designers flexibly install cameras in the ideal location of some small, lightweight wearable devices." He added: "Ultra low power consumption is critical for battery powered equipment with 10 or more cameras in each system. The power consumption of OG0TB BSI GS image sensor is less than 7.2 mW at 30 frames per second."

     OmniVision is introducing new products such as OG0TB GS image sensor to support the growing AR/VR head display market. OG0TB GS adopts the following advanced technologies of OmniVision: OmniVision PureCelPlus-S chip stacking technology is used, and a three-layer stacked sensor with a pixel size of 2.2 microns is used in the 1/14.46 inch optical format to achieve 400x400 resolution. Nyxel technology has excellent quantum efficiency (QE) under 940 nm near-infrared wavelength, which can obtain clear and accurate images of moving objects. High modulation transfer function (MTF) makes images clearer, Higher contrast and richer details are particularly important for improving the decision-making process of machine vision applications