2D to 3D convertion based on edge defocus and segmentation

This paper presents a depth estimation method which converts two-dimensional images into three-dimensional data. Based on two-dimensional wavelet analysis of Lipschitz regularity for defocus estimation on edges, this method can effectively eliminate the horizontal stripes in the depth map resulted from traditional one-dimensional wavelet based approaches. Besides, we also propose several techniques such as edge enhancement, color-based segmentation, and depth optimization to obtain a more reliable and smoother depth map. The experimental results demonstrate the effectiveness of our proposed techniques. ?2008 IEEE.EI

Descriptive quality of experience for mobile 3D video

ilmenau.de} Perceptual quality evaluation experiments are used to assess the excellence of multimedia quality. However, these studies disregard qualitative experiential descriptions, interpretations, and impressions of quality. The goal of this paper is to identify general descriptive characteristics of experienced quality of 3D video on mobile devices. We conducted five studies in which descriptive data was collected after the psychoperceptual quality evaluation experiment. Qualitative semi-structured interviews and written attribute description tasks were conducted with over 90 naïve participants. The experiments contained an extensive and heterogeneous set of produced quality by varying content, level of depth, compression and transmission parameters, and audio and display factors for 3D. The results showed that quality of experience is constructed from four main components, 1) visual quality, 2) viewing experience, 3) content, and 4) quality of other modalities and their interactions. Author Keywords Quality perception, quality of experience, multimedia, 3

View invariant DIBR-3D image watermarking using DT-CWT

In 3D image compression, depth image based rendering (DIBR) is one of the latest techniques where the center image (say the main view, is used to synthesise the left and the right view image) and the depth image are communicated to the receiver side. It has been observed in the literature that most of the existing 3D image watermarking schemes are not resilient to the view synthesis process used in the DIBR technique. In this paper, a 3D image watermarking scheme is proposed which is invariant to the DIBR view synthesis process. In this proposed scheme, 2D-dual-tree complex wavelet transform (2D-DT-CWT) coefficients of centre view are used for watermark embedding such that shift invariance and directional property of the DT-CWT can be exploited to make the scheme robust against view synthesis process. A comprehensive set of experiments has been carried out to justify the robustness of the proposed scheme over the related existing schemes with respect to the JPEG compression and synthesis view attack

Large-Scale Light Field Capture and Reconstruction

This thesis discusses approaches and techniques to convert Sparsely-Sampled Light Fields (SSLFs) into Densely-Sampled Light Fields (DSLFs), which can be used for visualization on 3DTV and Virtual Reality (VR) devices. Exemplarily, a movable 1D large-scale light field acquisition system for capturing SSLFs in real-world environments is evaluated. This system consists of 24 sparsely placed RGB cameras and two Kinect V2 sensors. The real-world SSLF data captured with this setup can be leveraged to reconstruct real-world DSLFs. To this end, three challenging problems require to be solved for this system: (i) how to estimate the rigid transformation from the coordinate system of a Kinect V2 to the coordinate system of an RGB camera; (ii) how to register the two Kinect V2 sensors with a large displacement; (iii) how to reconstruct a DSLF from a SSLF with moderate and large disparity ranges. To overcome these three challenges, we propose: (i) a novel self-calibration method, which takes advantage of the geometric constraints from the scene and the cameras, for estimating the rigid transformations from the camera coordinate frame of one Kinect V2 to the camera coordinate frames of 12-nearest RGB cameras; (ii) a novel coarse-to-fine approach for recovering the rigid transformation from the coordinate system of one Kinect to the coordinate system of the other by means of local color and geometry information; (iii) several novel algorithms that can be categorized into two groups for reconstructing a DSLF from an input SSLF, including novel view synthesis methods, which are inspired by the state-of-the-art video frame interpolation algorithms, and Epipolar-Plane Image (EPI) inpainting methods, which are inspired by the Shearlet Transform (ST)-based DSLF reconstruction approaches