Mr. Hisayoshi Furihata Profile

Hisayoshi Furihata

at Nagoya Univ

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 18 February 2010 Paper

Novel view synthesis with residual error feedback for FTV

Hisayoshi Furihata, Tomohiro Yendo, Mehrdad Panahpour Tehrani, Toshiaki Fujii, Masayuki Tanimoto

Proceedings Volume 7524, 75240K (2010) https://doi.org/10.1117/12.839110

KEYWORDS: Cameras, Virtual reality, Error analysis, 3D image processing, Image processing, Optimization (mathematics), Image quality, Image classification, Digital imaging, Video

Read Abstract +

The availability of multi-view images of a scene makes possible new and exciting applications, including Free-viewpoint TV (FTV). FTV allows us to change viewpoint freely in a 3D world, where the virtual viewpoint images are synthesized by Depth-Image-Based Rendering (DIBR). In this paper, we propose a new method of DIBR using multi-view images acquired in a linear camera arrangement. The proposed method improves virtual viewpoint images by predicting the residual errors. For virtual viewpoint image synthesis, it is necessary to estimate the depth maps with multi-view images. Some algorithms to estimate depth map were proposed, but it is difficult to estimate accurate depth map. As a result, rendered virtual viewpoint images have some errors due to the depth errors. Therefore, our proposed method takes into account those depth errors and improves the quality of the rendered virtual viewpoint images. In the proposed method, the virtual images of each camera position are generated using the real images from each other camera. Then, the residual errors can be calculated between the generated images and the real images acquired by the actual cameras. The residual errors are processed and fed back to predict the residual errors that can be happened to virtual viewpoint images generated by conventional method. In the experiments, PSNR could be improved for few decibels compared with the conventional method.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years