scispace - formally typeset
Search or ask a question
Topic

View synthesis

About: View synthesis is a research topic. Over the lifetime, 1701 publications have been published within this topic receiving 42333 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: This paper proposes a reliability-based view synthesis framework, a depth refinement method is used to check the reliability of depth values and refine some of the unreliable pixels, and an adaptive background modeling algorithm is utilized to construct a background image aiming to fill the remaining empty regions after a proposed weighted blending process.
Abstract: View synthesis is a crucial technique for free viewpoint video and multi-view video coding because of its capability to render an unlimited number of virtual viewpoints from adjacent captured texture images and corresponding depth maps. The accuracy of depth maps is very important to the rendering quality, since depth image–based rendering (DIBR) is the most widely used technology among synthesis algorithms. There are some issues due to the fact that stereo depth estimation is error-prone. In addition, filling occlusions is another challenge in producing desirable synthesized images. In this paper, we propose a reliability-based view synthesis framework. A depth refinement method is used to check the reliability of depth values and refine some of the unreliable pixels, and an adaptive background modeling algorithm is utilized to construct a background image aiming to fill the remaining empty regions after a proposed weighted blending process. Finally, the proposed approach is implemented and tested on test video sequences, and experimental results indicate objective and subjective improvements compared to previous view synthesis methods.

5 citations

Journal ArticleDOI
TL;DR: An artifact handling method based on depth image is proposed, which has better performance compared with previous methods in subjective and objective evaluation.
Abstract: The depth image based rendering (DIBR) is a popular technology for 3D video and free viewpoint video (FVV) synthesis, by which numerous virtual views can be generated from a single reference view and its depth image. However, some artifacts are produced in the DIBR process and reduce the visual quality of virtual view. Due to the diversity of artifacts, effectively handling them becomes a challenging task. In this paper, an artifact handling method based on depth image is proposed. The reference image and its depth image are extended to fill the holes that belong to the out-of-field regions. A depth image preprocessing method is applied to project the ghosts to their correct place. The 3D warping process is optimized by an adaptive one-to-four method to deal with the cracks and pixel overlapping. For disocclusions, we calculate depth and background terms of the filling priority based on depth information. The search for the best matching patch is performed simultaneously in the reference image and the virtual image. Moreover, adaptive patch size is used in all hole-filling processes. Experimental results demonstrate the effectiveness of the proposed method, which has better performance compared with previous methods in subjective and objective evaluation.

5 citations

Proceedings ArticleDOI
07 May 2012
TL;DR: By warping the base view's frame of a multi view video to the position of the enhancement views' camera a prediction signal is formed, which can either be used for the proposed warped skip mode or as a predicted signal to reduce the residual's energy.
Abstract: Upcoming display technologies like auto stereoscopic displays require synthesis of virtual viewpoints to allow for depth impression without requiring the viewer to wear glasses. View synthesis relies on the availability of depth information at the receiver side to warp the recorded video data to arbitrary viewpoints. This depth data contains information about the 3D position of recorded pixel values and therefore inherently also contains the pixel-wise disparity information between multiple views to be coded. In this paper we propose to use this depth information also for compression of multi view video+depth sequences. By warping the base view's frame of a multi view video to the position of the enhancement views' camera a prediction signal is formed, which can either be used for the proposed warped skip mode or as a prediction signal to reduce the residual's energy.

5 citations

Proceedings ArticleDOI
01 Mar 2012
TL;DR: A disocclusion inpainting method guided by parallax-map to reconstruct disocclusions effectively is presented and experiments illustrate the efficiency of the proposed method.
Abstract: DIBR inherently would produce disocclusions in synthesized views. This paper presents a disocclusion inpainting method guided by parallax-map to reconstruct disocclusions effectively. Our experiments illustrate the efficiency of the proposed method.

5 citations

Proceedings ArticleDOI
16 May 2011
TL;DR: This paper provides an approach to synthesize virtual image from multi-view color and depth videos whose resolutions are different from each other.
Abstract: Multiview 3D videos can efficiently be represented using a mixed resolution multiview 3D video format that has a number of color and depth information with different resolutions. However, such a mixed resolution multiview video format would have a shortcoming on synthesizing virtual views between a low and a high resolution view. This paper provides an approach to synthesize virtual image from multi-view color and depth videos whose resolutions are different from each other.

5 citations


Network Information
Related Topics (5)
Image segmentation
79.6K papers, 1.8M citations
86% related
Feature (computer vision)
128.2K papers, 1.7M citations
86% related
Object detection
46.1K papers, 1.3M citations
85% related
Convolutional neural network
74.7K papers, 2M citations
85% related
Feature extraction
111.8K papers, 2.1M citations
84% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202354
2022117
2021189
2020158
2019114
2018102