VR Headset See-through Tech to Help in MR Development
- VR headsets’ see-through technology can enable an early MR experience and also help develop the ecosystem necessary for MR applications.
- Depth perception is essential in MR applications to demonstrate the occlusion phenomena. The current quality of the VR VST is barely adequate as it is achieved through cameras. However, this can be improved by incorporating an additional ToF sensor.
- There will be significantly more VR headsets with VST going forward, promoting a rise in the number of MR applications.
- Both stereo vision and depth perception are crucial for MR. In the future, VR headsets equipped with a time-of-flight (ToF) sensor will be able to capture more accurate distance information than the camera-equipped ones currently available.
- The VST of a VR headset barely achieves binocular vision. One of the reasons is that there is only one camera for VR VST, which makes it difficult to measure the distance of a close object. Additionally, there will still be warping and distortion of field-of-view objects. Future algorithms must improve this, or designers need to avoid letting users perceive items located closer. Additionally, more color and white balance sensors will be required for making more realistic approximations of the actual color.
- In a novel application of VR, VST technology can be used to bring several displays in the virtual world by creating a few virtual displays. However, the current resolution of virtual displays in VR headsets is less than that in real-world displays. Nevertheless, this issue can be resolved by increasing the resolution of the display on the VR headset, though it would cost more.
- Latency is a crucial characteristic of the VST VR headset because processors must encode the image captured by the camera. Therefore, the speed and bandwidth of processors will affect the performance of VR systems as future mid-range and high-end VR headsets in general will support 4K video streams. Therefore, the VR headset SoC’s requirement should be higher than that of smartphones.
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Author
Brady Wang
Hi, I’m Brady Wang, a seasoned professional with over 20 years of experience in the high-tech industry, spanning semiconductor manufacturing, market intelligence, and strategic advisory roles. Currently, I serve as an analyst at Counterpoint Research, where I specialize in semiconductors with a focus on advanced applications such as automotive, server platforms, and cutting-edge process nodes. My core research centers on AI servers and their key components, including GPUs, custom accelerators, high-bandwidth memory (HBM), CPUs, and advanced packaging technologies. I also track the evolution of AI server architectures, interconnect technologies, and data center deployment trends. By combining deep technical knowledge with market insight, I help clients navigate the fast-changing AI infrastructure landscape and make strategic, data-driven decisions.