1. Color Contrast Enhanced Rendering for Optical See-Through Head-Mounted Displays
- Author
-
Evan Peng, Yunjin Zhang, Wei Hua, Rui Wang, and Hujun Bao
- Subjects
Computer science ,Color vision ,media_common.quotation_subject ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Luminance ,Rendering (computer graphics) ,User-Computer Interface ,Computer Graphics ,Psychophysics ,Contrast (vision) ,Computer vision ,Chromaticity ,ComputingMethodologies_COMPUTERGRAPHICS ,media_common ,Pixel ,business.industry ,Equipment Design ,Computer Graphics and Computer-Aided Design ,Mixed reality ,Signal Processing ,Smart Glasses ,Computer Vision and Pattern Recognition ,Artificial intelligence ,business ,Head ,Software - Abstract
Most commercially available optical see-through head-mounted displays (OST-HMDs) utilize optical combiners to simultaneously visualize the physical background and virtual objects. The displayed images perceived by users are a blend of rendered pixels and background colors. Enabling high fidelity color perception in mixed reality (MR) scenarios using OST-HMDs is an important but challenging task. We propose a real-time rendering scheme to enhance the color contrast between virtual objects and the surrounding background for OST-HMDs. Inspired by the discovery of color perception in psychophysics, we first formulate the color contrast enhancement as a constrained optimization problem. We then design an end-to-end algorithm to search the optimal complementary shift in both chromaticity and luminance of the displayed color. This aims at enhancing the contrast between virtual objects and the real background as well as keeping the consistency with the original displayed color. We assess the performance of our approach using a simulated OST-HMD environment and an off-the-shelf OST-HMD. Experimental results from objective evaluations and subjective user studies demonstrate that the proposed approach makes rendered virtual objects more distinguishable from the surrounding background, thereby bringing a better visual experience.
- Published
- 2022