Image Completion for View Synthesis Using Markov Random Fields and Efficient Belief Propagation

View synthesis is a process for generating novel views from a scene which has been recorded with a 3-D camera setup. It has important applications in 3-D post-production and 2-D to 3-D conversion. However, a central problem in the generation of novel views lies in the handling of disocclusions. Background content, which was occluded in the original view, may become unveiled in the synthesized view. This leads to missing information in the generated view which has to be filled in a visually plausible manner. We present an inpainting algorithm for disocclusion filling in synthesized views based on Markov random fields and efficient belief propagation. We compare the result to two state-of-the-art algorithms and demonstrate a significant improvement in image quality.Comment: Published version: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=673843

Wavelet based stereo images reconstruction using depth images

It is believed by many that three-dimensional (3D) television will be the next logical development toward a more natural and vivid home entertaiment experience. While classical 3D approach requires the transmission of two video streams, one for each view, 3D TV systems based on depth image rendering (DIBR) require a single stream of monoscopic images and a second stream of associated images usually termed depth images or depth maps, that contain per-pixel depth information. Depth map is a two-dimensional function that contains information about distance from camera to a certain point of the object as a function of the image coordinates. By using this depth information and the original image it is possible to reconstruct a virtual image of a nearby viewpoint by projecting the pixels of available image to their locations in 3D space and finding their position in the desired view plane. One of the most significant advantages of the DIBR is that depth maps can be coded more efficiently than two streams corresponding to left and right view of the scene, thereby reducing the bandwidth required for transmission, which makes it possible to reuse existing transmission channels for the transmission of 3D TV. This technique can also be applied for other 3D technologies such as multimedia systems. In this paper we propose an advanced wavelet domain scheme for the reconstruction of stereoscopic images, which solves some of the shortcommings of the existing methods discussed above. We perform the wavelet transform of both the luminance and depth images in order to obtain significant geometric features, which enable more sensible reconstruction of the virtual view. Motion estimation employed in our approach uses Markov random field smoothness prior for regularization of the estimated motion field. The evaluation of the proposed reconstruction method is done on two video sequences which are typically used for comparison of stereo reconstruction algorithms. The results demonstrate advantages of the proposed approach with respect to the state-of-the-art methods, in terms of both objective and subjective performance measures

3D Reconstruction: Novel Method for Finding of Corresponding Points using Pseudo Colors

This paper deals with the reconstruction of spatial coordinates of an arbitrary point in a scene using two images scanned by a 3D camera or two displaced cameras. Calculations are based on the perspective geom-etry. Accurate determination of corresponding points is a fundamental step in this process. The usually used methods can have a problem with points, which lie in areas without sufficient contrast. This paper describes our proposed method based on the use of the relationship between the selected points and area feature points. The proposed method finds correspondence using a set of feature points found by SURF. An algorithm is proposed and described for quick removal of false correspondences, which could ruin the correct reconstruction. The new method, which makes use of pseudo color image representation (pseudo coloring) has been proposed subsequently. By means of this method it is possible to significantly increase the color contrast of the surveyed image, and therefore add more information to find the correct correspondence. Reliability of the found correspondence can be verified by reconstruction of 3D position of selected points. Executed experiments confirm our assumption

Depth filtering for auto-stereoscopic mobile devices

In this work we address a scenario where 3D content is transmitted to a mobile terminal with 3D display capabilities. We consider the use of 2D plus depth format to represent the 3D content and focus on the generation of synthetic views in the terminal. We evaluate different types of smoothing filters that are applied to depth maps with the aim of reducing the disoccluded regions. The evaluation takes into account the reduction of holes in the synthetic view as well as the presence of geometrical distortion caused by the smoothing operation. The selected filter has been included within an implemented module for the VideoLan Client (VLC) software in order to render 3D content from the 2D plus depth data format

An Improved Depth Image Inpainting

[[abstract]]In recent years, the price of depth camera became low, so that researchers can use depth camera to do more application. For computer vision, depth images can provide more useful information. However, generally there are some problems in depth image, such as holes, incomplete edge, and temporal random fluctuations. Conventional inpainting approach must rely on color image and it cannot be processed in real time. Therefore, this paper proposes a real time depth image inpainting method. First, we use background subtraction and mask filter to patch up the no-measured pixels, and then using the relationship between successive depth images to remove temporal random fluctuations. Finally, using erosion and dilation smooth the edge. Experimental results outperform than traditional one.[[sponsorship]]Asia-Pacific Education & Research Association[[conferencetype]]國際[[conferencedate]]20140711~20140713[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]普吉島, 泰

Object-based 2D-to-3D video conversion for effective stereoscopic content generation in 3D-TV applications

Three-dimensional television (3D-TV) has gained increasing popularity in the broadcasting domain, as it enables enhanced viewing experiences in comparison to conventional two-dimensional (2D) TV. However, its application has been constrained due to the lack of essential contents, i.e., stereoscopic videos. To alleviate such content shortage, an economical and practical solution is to reuse the huge media resources that are available in monoscopic 2D and convert them to stereoscopic 3D. Although stereoscopic video can be generated from monoscopic sequences using depth measurements extracted from cues like focus blur, motion and size, the quality of the resulting video may be poor as such measurements are usually arbitrarily defined and appear inconsistent with the real scenes. To help solve this problem, a novel method for object-based stereoscopic video generation is proposed which features i) optical-flow based occlusion reasoning in determining depth ordinal, ii) object segmentation using improved region-growing from masks of determined depth layers, and iii) a hybrid depth estimation scheme using content-based matching (inside a small library of true stereo image pairs) and depth-ordinal based regularization. Comprehensive experiments have validated the effectiveness of our proposed 2D-to-3D conversion method in generating stereoscopic videos of consistent depth measurements for 3D-TV applications

Direction Hole-Filling Method for a 3D View Generator

[[abstract]]Depth image-based rendering (DIBR) technology is an approach to creating a virtual 3D image from one single 2D image. A desired view can be synthesised at the receiver side using depth images to make transmission and storage efficient. While this technique has many advantages, one of the key challenges is how to fill the holes caused by disocclusion regions and wrong depth values in the warped left/right images. A common means to alleviate the sizes and the number of holes is to smooth the depth image. But smoothing results in geometric distortions and degrades the depth image quality. This study proposes a hole-filling method based on the oriented texture direction. Parallax correction is first implemented to mitigate the wrong depth values. Texture directional information is then probed in the background pixels where holes take place after warping. Next, in the warped image, holes are filled according to their directions. Experimental results showed that this algorithm preserves the depth information and greatly reduces the amount of geometric distortion.[[notice]]補正完

Automatic 2D-to-3D video conversion technique based on depth-from-motion and color segmentation

Most of the TV manufacturers have released 3DTVs in the summer of 2010 using shutter-glasses technology. 3D video applications are becoming popular in our daily life, especially at home entertainment. Although more and more 3D movies are being made, 3D video contents are still not rich enough to satisfy the future 3D video market. There is a rising demand on new techniques for automatically converting 2D video content to stereoscopic 3D video displays. In this paper, an automatic monoscopic video to stereoscopic 3D video conversion scheme is presented using block-based depth from motion estimation and color segmentation for depth map enhancement. The color based region segmentation provides good region boundary information, which is used to fuse with block-based depth map for eliminating the staircase effect and assigning good depth value in each segmented region. The experimental results show that this scheme can achieve relatively high quality 3D stereoscopic video output. ? 2010 IEEE.EI

A perceptual approach for stereoscopic rendering optimization

Cataloged from PDF version of article.The traditional way of stereoscopic rendering requires rendering the scene for left and right eyes separately: which doubles the rendering complexity. In this study, we propose a perceptually-based approach for accelerating stereoscopic rendering. This optimization approach is based on the Binocular Suppression Theory, which claims that the overall percept of a stereo pair in a region is determined by the dominant image on the corresponding region. We investigate how binocular suppression mechanism of human visual system can be utilized for rendering optimization. Our aim is to identify the graphics rendering and modeling features that do not affect the overall quality of a stereo pair when simplified in one view. By combining the results of this investigation with the principles of visual attention, we infer that this optimization approach is feasible if the high quality view has more intensity contrast. For this reason, we performed a subjective experiment, in which various representative graphical methods were analyzed. The experimental results verified our hypothesis that a modification, applied on a single view, is not perceptible if it decreases the intensity contrast, and thus can be used for stereoscopic rendering. (C) 2009 Elsevier Ltd. All rights reserved

Efficient dense blur map estimation for automatic 2D-to-3D conversion

Focus is an important depth cue for 2D-to-3D conversion of low depth-of-field images and video. However, focus can be only reliably estimated on edges. Therefore, Bea et al. [1] first proposed an optimization based approach to propagate focus to non-edge image portions, for single image focus editing. While their approach produces accurate dense blur maps, the computational complexity and memory requirements for solving the resulting sparse linear system with standard multigrid or (multilevel) preconditioning techniques, are infeasible within the stringent requirements of the consumer electronics and broadcast industry. In this paper we propose fast, efficient, low latency, line scanning based focus propagation, which mitigates the need for complex multigrid or (multilevel) preconditioning techniques. In addition we propose facial blur compensation to compensate for false shading edges that cause incorrect blur estimates in people's faces. In general shading leads to incorrect focus estimates, which may lead to unnatural 3D and visual discomfort. Since visual attention mostly tends to faces, our solution solves the most distracting errors. A subjective assessment by paired comparison on a set of challenging low-depth-of-field images shows that the proposed approach achieves equal 3D image quality as optimization based approaches, and that facial blur compensation results in a significant improvemen