A Novel Inpainting Framework for Virtual View Synthesis

Multi-view imaging has stimulated significant research to enhance the user experience of free viewpoint video, allowing interactive navigation between views and the freedom to select a desired view to watch. This usually involves transmitting both textural and depth information captured from different viewpoints to the receiver, to enable the synthesis of an arbitrary view. In rendering these virtual views, perceptual holes can appear due to certain regions, hidden in the original view by a closer object, becoming visible in the virtual view. To provide a high quality experience these holes must be filled in a visually plausible way, in a process known as inpainting. This is challenging because the missing information is generally unknown and the hole-regions can be large. Recently depth-based inpainting techniques have been proposed to address this challenge and while these generally perform better than non-depth assisted methods, they are not very robust and can produce perceptual artefacts. This thesis presents a new inpainting framework that innovatively exploits depth and textural self-similarity characteristics to construct subjectively enhanced virtual viewpoints. The framework makes three significant contributions to the field: i) the exploitation of view information to jointly inpaint textural and depth hole regions; ii) the introduction of the novel concept of self-similarity characterisation which is combined with relevant depth information; and iii) an advanced self-similarity characterising scheme that automatically determines key spatial transform parameters for effective and flexible inpainting. The presented inpainting framework has been critically analysed and shown to provide superior performance both perceptually and numerically compared to existing techniques, especially in terms of lower visual artefacts. It provides a flexible robust framework to develop new inpainting strategies for the next generation of interactive multi-view technologies

INTERMEDIATE VIEW RECONSTRUCTION FOR MULTISCOPIC 3D DISPLAY

This thesis focuses on Intermediate View Reconstruction (IVR) which generates additional images from the available stereo images. The main application of IVR is to generate the content of multiscopic 3D displays, and it can be applied to generate different viewpoints to Free-viewpoint TV (FTV). Although IVR is considered a good approach to generate additional images, there are some problems with the reconstruction process, such as detecting and handling the occlusion areas, preserving the discontinuity at edges, and reducing image artifices through formation of the texture of the intermediate image. The occlusion area is defined as the visibility of such an area in one image and its disappearance in the other one. Solving IVR problems is considered a significant challenge for researchers. In this thesis, several novel algorithms have been specifically designed to solve IVR challenges by employing them in a highly robust intermediate view reconstruction algorithm. Computer simulation and experimental results confirm the importance of occluded areas in IVR. Therefore, we propose a novel occlusion detection algorithm and another novel algorithm to Inpaint those areas. Then, these proposed algorithms are employed in a novel occlusion-aware intermediate view reconstruction that finds an intermediate image with a given disparity between two input images. This novelty is addressed by adding occlusion awareness to the reconstruction algorithm and proposing three quality improvement techniques to reduce image artifices: filling the re-sampling holes, removing ghost contours, and handling the disocclusion area. We compared the proposed algorithms to the previously well-known algorithms on each field qualitatively and quantitatively. The obtained results show that our algorithms are superior to the previous well-known algorithms. The performance of the proposed reconstruction algorithm is tested under 13 real images and 13 synthetic images. Moreover, analysis of a human-trial experiment conducted with 21 participants confirmed that the reconstructed images from our proposed algorithm have very high quality compared with the reconstructed images from the other existing algorithms

Compression and Subjective Quality Assessment of 3D Video

In recent years, three-dimensional television (3D TV) has been broadly considered as the successor to the existing traditional two-dimensional television (2D TV) sets. With its capability of offering a dynamic and immersive experience, 3D video (3DV) is expected to expand conventional video in several applications in the near future. However, 3D content requires more than a single view to deliver the depth sensation to the viewers and this, inevitably, increases the bitrate compared to the corresponding 2D content. This need drives the research trend in video compression field towards more advanced and more efficient algorithms. Currently, the Advanced Video Coding (H.264/AVC) is the state-of-the-art video coding standard which has been developed by the Joint Video Team of ISO/IEC MPEG and ITU-T VCEG. This codec has been widely adopted in various applications and products such as TV broadcasting, video conferencing, mobile TV, and blue-ray disc. One important extension of H.264/AVC, namely Multiview Video Coding (MVC) was an attempt to multiple view compression by taking into consideration the inter-view dependency between different views of the same scene. This codec H.264/AVC with its MVC extension (H.264/MVC) can be used for encoding either conventional stereoscopic video, including only two views, or multiview video, including more than two views. In spite of the high performance of H.264/MVC, a typical multiview video sequence requires a huge amount of storage space, which is proportional to the number of offered views. The available views are still limited and the research has been devoted to synthesizing an arbitrary number of views using the multiview video and depth map (MVD). This process is mandatory for auto-stereoscopic displays (ASDs) where many views are required at the viewer side and there is no way to transmit such a relatively huge number of views with currently available broadcasting technology. Therefore, to satisfy the growing hunger for 3D related applications, it is mandatory to further decrease the bitstream by introducing new and more efficient algorithms for compressing multiview video and depth maps. This thesis tackles the 3D content compression targeting different formats i.e. stereoscopic video and depth-enhanced multiview video. Stereoscopic video compression algorithms introduced in this thesis mostly focus on proposing different types of asymmetry between the left and right views. This means reducing the quality of one view compared to the other view aiming to achieve a better subjective quality against the symmetric case (the reference) and under the same bitrate constraint. The proposed algorithms to optimize depth-enhanced multiview video compression include both texture compression schemes as well as depth map coding tools. Some of the introduced coding schemes proposed for this format include asymmetric quality between the views. Knowing that objective metrics are not able to accurately estimate the subjective quality of stereoscopic content, it is suggested to perform subjective quality assessment to evaluate different codecs. Moreover, when the concept of asymmetry is introduced, the Human Visual System (HVS) performs a fusion process which is not completely understood. Therefore, another important aspect of this thesis is conducting several subjective tests and reporting the subjective ratings to evaluate the perceived quality of the proposed coded content against the references. Statistical analysis is carried out in the thesis to assess the validity of the subjective ratings and determine the best performing test cases

Real-time video-plus-depth content creation utilizing time-of-flight sensor - from capture to display

Recent developments in 3D camera technologies, display technologies and other related fields have been aiming to provide 3D experience for home user and establish services such as Three-Dimensional Television (3DTV) and Free-Viewpoint Television (FTV). Emerging multiview autostereoscopic displays do not require any eyewear and can be watched by multiple users at the same time, thus are very attractive for home environment usage. To provide a natural 3D impression, autostereoscopic 3D displays have been design to synthesize multi-perspective virtual views of a scene using Depth-Image-Based Rendering (DIBR) techniques. One key issue of DIBR is that scene depth information in a form of a depth map is required in order to synthesize virtual views. Acquiring this information is quite complex and challenging task and still an active research topic. In this thesis, the problem of dynamic 3D video content creation of real-world visual scenes is addressed. The work assumed data acquisition setting including Time-of-Flight (ToF) depth sensor and a single conventional video camera. The main objective of the work is to develop efficient algorithms for the stages of synchronous data acquisition, color and ToF data fusion, and final view-plus-depth frame formatting and rendering. The outcome of this thesis is a prototype 3DTV system capable for rendering live 3D video on a 3D autostereoscopic display. The presented system makes extensive use of the processing capabilities of modern Graphics Processing Units (GPUs) in order to achieve real-time processing rates while providing an acceptable visual quality. Furthermore, the issue of arbitrary view synthesis is investigated in the context of DIBR and a novel approach based on depth layering is proposed. The proposed approach is applicable for general virtual views synthesis, i.e. in terms of different camera parameters such as position, orientation, focal length and varying sensors spatial resolutions. The experimental results demonstrate real-time capability of the proposed method even for CPU-based implementations. It compares favorably to other view synthesis methods in terms of visual quality, while being more computationally efficient

Die Virtuelle Videokamera: ein System zur Blickpunktsynthese in beliebigen, dynamischen Szenen

The Virtual Video Camera project strives to create free viewpoint video from casually captured multi-view data. Multiple video streams of a dynamic scene are captured with off-the-shelf camcorders, and the user can re-render the scene from novel perspectives. In this thesis the algorithmic core of the Virtual Video Camera is presented. This includes the algorithm for image correspondence estimation as well as the image-based renderer. Furthermore, its application in the context of an actual video production is showcased, and the rendering and image processing pipeline is extended to incorporate depth information.Das Virtual Video Camera Projekt dient der Erzeugung von Free Viewpoint Video Ansichten von Multi-View Aufnahmen: Material mehrerer Videoströme wird hierzu mit handelsüblichen Camcordern aufgezeichnet. Im Anschluss kann die Szene aus beliebigen, von den ursprünglichen Kameras nicht abgedeckten Blickwinkeln betrachtet werden. In dieser Dissertation wird der algorithmische Kern der Virtual Video Camera vorgestellt. Dies beinhaltet das Verfahren zur Bildkorrespondenzschätzung sowie den bildbasierten Renderer. Darüber hinaus wird die Anwendung im Kontext einer Videoproduktion beleuchtet. Dazu wird die bildbasierte Erzeugung neuer Blickpunkte um die Erzeugung und Einbindung von Tiefeninformationen erweitert

3D coding tools final report

Livrable D4.3 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D4.3 du projet. Son titre : 3D coding tools final repor