3D+2DTV

Author:

Scher Steven1,Liu Jing1,Vaish Rajan1,Gunawardane Prabath1,Davis James1

Affiliation:

1. University of California Santa Cruz, CA

Abstract

3D displays are increasingly popular in consumer and commercial applications. Many such displays show 3D images to viewers wearing special glasses, while showing an incomprehensible double image to viewers without glasses. We demonstrate a simple method that provides those with glasses a 3D experience, while viewers without glasses see a 2D image without artifacts. In addition to separate left and right images in each frame, we add a third image, invisible to those with glasses. In the combined view seen by those without glasses, this cancels the right image, leaving only the left. If the left and right images are of equal brightness, this approach results in low contrast for viewers without glasses. Allowing differential brightness between the left and right images improves 2D contrast. We observe experimentally that: (1) viewers without glasses prefer our 3D+2DTV to a standard 3DTV, (2) viewers with glasses maintain a strong 3D percept, even when one eye is significantly darker than the other, and (3) sequential-stereo display viewers with glasses experience a depth illusion caused by the Pulfrich effect, but it is small and innocuous. Our technique is applicable to displays using either active shutter glasses or passive glasses. Our prototype uses active shutter glasses and a polarizer.

Funder

LANLISSDM

Division of Computing and Communication Foundations

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design

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1. Modified 2D-Ghost-Free Stereoscopic Display with Depth-of-Field Effects;ACM Transactions on Multimedia Computing, Communications, and Applications;2023-01-23

2. Psycho-visual modulation based information display: introduction and survey;Frontiers of Computer Science;2021-02-11

3. Mononizing binocular videos;ACM Transactions on Graphics;2020-12-31

4. 人間の視覚の理解に基づいたステレオ画像生成手法「Hidden Stereo」;The Journal of The Institute of Image Information and Television Engineers;2020

5. Deep Visual Sharing With Colorblind;IEEE Transactions on Computational Imaging;2019-12

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