KJGG28) and Natural Science Foundation of Nanyang Normal University (No. 15A413005), Key scientific and technological project of Nanyang City (No. 152102210336), Key scientific research project of Henan Provincial Education Department (No. 61402462), Key scientific and technological project of Henan Province (No. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the paper and its Supporting Information files.įunding: This work was supported in part by National Natural Science Foundation of China (No. Received: DecemAccepted: ApPublished: April 13, 2017Ĭopyright: © 2017 Liu et al. Numerical experimental results demonstrate the excellent performances of the proposed method.Ĭitation: Liu W, Ma L, Qiu B, Cui M, Ding J (2017) An efficient depth map preprocessing method based on structure-aided domain transform smoothing for 3D view generation. Thanks to these advantages, it can yield visually satisfactory results with less computational complexity for high quality 2D to 3D conversion. Different from the other similar methods, the proposed method can simultaneously achieve the effects of hole filling, edge correction and local smoothing for typical depth maps in a united framework. Then, adaptive smooth localization is cooperated and realized in the proposed framework to further reduce over-smoothness and enhance optimization in the non-hole regions. Firstly, our framework integrates hybrid constraints including scene structure, edge consistency and visual saliency information in the transformed domain to improve the performance of depth map preprocess in an implicit way. In this paper, we proposed a structure-aided depth map preprocessing framework in the transformed domain, which is inspired by recently proposed domain transform for its low complexity and high efficiency.
Due to the absence of knowledge about the 3D structure of a scene and its corresponding texture, DIBR in the 2D to 3D conversion process, inevitably leads to holes in the resulting 3D image as a result of newly-exposed areas. In addition to producing a superior 3D experience, a single channel (left or right) of a v3D production can be released as a depth enhanced v3 imagery that will play on standard 2D unaided displays.Depth image-based rendering (DIBR), which is used to render virtual views with a color image and the corresponding depth map, is one of the key techniques in the 2D to 3D conversion process. The result is a dramatically improved viewing experience and an invaluable perceptual tool for creative directors and producers alike. The parallax information provided by a moving iris allows for a more natural, unified, three dimensional perception on the part of the viewer.ĭPs and Stereographers can use v3D to create more compelling content than traditional 3D can offer without requiring changes in the 3D production cycle. v3D corrects for this problem by capturing additional parallax information that is similar to that from head motion and the scanning motion of one’s eyes. Standard lenses thereby fail to provide means to capture the additional visual cues that we perceive in everyday life.
This shortcoming can be explained by the fact that a traditional lens iris does not scan, unlike the human eye, which is in a constant state of motion. While this process is effective at capturing an image, it fails to collect the detailed information that one would perceive when viewing something in person. Since the onset of film, conventional lenses have used a static iris to capture visual information.
0 kommentar(er)
