Adaptive Image Warping for HMDs Using Depth Segmentation
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Solution Overview
Problem
Head-mountable devices (HMDs) cause user discomfort due to spatial offset between the camera and display planes, leading to motion sickness, and per-pixel rendering is computationally expensive, resulting in high power consumption and latency.
Innovation Solution
Adaptive image warping based on visual features and distance between the device and a reference point, using different warping functions for foreground and background objects to optimize processing resources and reduce latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If per-pixel rendering is used to correct spatial offset, then visual perception alignment is improved, but computational cost and power consumption increase significantly
Solution Approach 1:
The image is divided into multiple regions based on depth information, with each region processed using appropriate warping functions. Foreground objects are processed differently from background regions, allowing selective application of computational resources to areas requiring higher precision while reducing processing for areas where simple warping suffices.
Solution Approach 2:
Different warping functions and processing granularities are applied to different spatial regions of the image based on their depth characteristics. Foreground regions receive more sophisticated processing while background regions use simpler methods, optimizing the balance between visual accuracy and computational efficiency.
2Measurement precision
If per-pixel rendering is used to correct spatial offset, then visual perception alignment is improved, but processing latency increases
Solution Approach 1:
The image processing is segmented into depth-based regions that can be processed in parallel. By identifying foreground and background regions separately, the system can apply different processing pipelines simultaneously, reducing overall latency while maintaining visual alignment accuracy.
Solution Approach 2:
The system applies full per-pixel warping only to foreground regions where visual alignment is critical, while using simplified warping for background regions. This partial application of the expensive processing method reduces latency while maintaining sufficient visual perception alignment for the most important areas.
3Measurement precision
If adaptive image warping is applied to all regions, then visual perception alignment is improved, but processing complexity increases
Solution Approach 1:
The processing system is segmented into multiple stages: depth map generation, region classification, and selective warping application. This segmentation allows the complex adaptive warping to be applied only where necessary, reducing overall system complexity while maintaining visual alignment where it matters most.
Solution Approach 2:
The system applies different levels of processing complexity to different image regions based on their depth characteristics. Foreground regions receive full adaptive warping while background regions use simpler methods, reducing the overall computational complexity of the system while maintaining visual perception alignment for critical areas.
Data Source
AI summary
A method includes obtaining an image via an image sensor, and identifying, within the image, a physical object represented by a portion of the image. The method includes determining, based on the image, a visual feature characterizing the physical object. The method includes warping, based on the visual feature satisfying a first feature criterion, the portion of the image according to a first warping function that is based on the first feature criterion and a distance between the electronic device and a reference point. The method includes warping, based on the visual feature satisfying a second feature criterion that is different from the first feature criterion, the portion of the image according to a second warping function that is based on the second feature criterion and the distance between the electronic device and the reference point.