Survey of image-based representations and compression techniques

In this paper, we survey the techniques for image-based rendering (IBR) and for compressing image-based representations. Unlike traditional three-dimensional (3-D) computer graphics, in which 3-D geometry of the scene is known, IBR techniques render novel views directly from input images. IBR techniques can be classified into three categories according to how much geometric information is used: rendering without geometry, rendering with implicit geometry (i.e., correspondence), and rendering with explicit geometry (either with approximate or accurate geometry). We discuss the characteristics of these categories and their representative techniques. IBR techniques demonstrate a surprising diverse range in their extent of use of images and geometry in representing 3-D scenes. We explore the issues in trading off the use of images and geometry by revisiting plenoptic-sampling analysis and the notions of view dependency and geometric proxies. Finally, we highlight compression techniques specifically designed for image-based representations. Such compression techniques are important in making IBR techniques practical.published_or_final_versio

Compressing the illumination-adjustable images with principal component analysis.

Pun-Mo Ho.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 90-95).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Background --- p.1Chapter 1.2 --- Existing Approaches --- p.2Chapter 1.3 --- Our Approach --- p.3Chapter 1.4 --- Structure of the Thesis --- p.4Chapter 2 --- Related Work --- p.5Chapter 2.1 --- Compression for Navigation --- p.5Chapter 2.1.1 --- Light Field/Lumigraph --- p.5Chapter 2.1.2 --- Surface Light Field --- p.6Chapter 2.1.3 --- Concentric Mosaics --- p.6Chapter 2.1.4 --- On the Compression --- p.7Chapter 2.2 --- Compression for Relighting --- p.7Chapter 2.2.1 --- Previous Approaches --- p.7Chapter 2.2.2 --- Our Approach --- p.8Chapter 3 --- Image-Based Relighting --- p.9Chapter 3.1 --- Plenoptic Illumination Function --- p.9Chapter 3.2 --- Sampling and Relighting --- p.11Chapter 3.3 --- Overview --- p.13Chapter 3.3.1 --- Codec Overview --- p.13Chapter 3.3.2 --- Image Acquisition --- p.15Chapter 3.3.3 --- Experiment Data Sets --- p.16Chapter 4 --- Data Preparation --- p.18Chapter 4.1 --- Block Division --- p.18Chapter 4.2 --- Color Model --- p.23Chapter 4.3 --- Mean Extraction --- p.24Chapter 5 --- Principal Component Analysis --- p.29Chapter 5.1 --- Overview --- p.29Chapter 5.2 --- Singular Value Decomposition --- p.30Chapter 5.3 --- Dimensionality Reduction --- p.34Chapter 5.4 --- Evaluation --- p.37Chapter 6 --- Eigenimage Coding --- p.39Chapter 6.1 --- Transform Coding --- p.39Chapter 6.1.1 --- Discrete Cosine Transform --- p.40Chapter 6.1.2 --- Discrete Wavelet Transform --- p.47Chapter 6.2 --- Evaluation --- p.49Chapter 6.2.1 --- Statistical Evaluation --- p.49Chapter 6.2.2 --- Visual Evaluation --- p.52Chapter 7 --- Relighting Coefficient Coding --- p.57Chapter 7.1 --- Quantization and Bit Allocation --- p.57Chapter 7.2 --- Evaluation --- p.62Chapter 7.2.1 --- Statistical Evaluation --- p.62Chapter 7.2.2 --- Visual Evaluation --- p.62Chapter 8 --- Relighting --- p.65Chapter 8.1 --- Overview --- p.66Chapter 8.2 --- First-Phase Decoding --- p.66Chapter 8.3 --- Second-Phase Decoding --- p.68Chapter 8.3.1 --- Software Relighting --- p.68Chapter 8.3.2 --- Hardware-Assisted Relighting --- p.71Chapter 9 --- Overall Evaluation --- p.81Chapter 9.1 --- Compression of IAIs --- p.81Chapter 9.1.1 --- Statistical Evaluation --- p.81Chapter 9.1.2 --- Visual Evaluation --- p.86Chapter 9.2 --- Hardware-Assisted Relighting --- p.86Chapter 10 --- Conclusion --- p.89Bibliography --- p.9

Efficient acquisition, representation and rendering of light fields

In this thesis we discuss the representation of three-dimensional scenes using image data (image-based rendering), and more precisely the so-called light field approach. We start with an up-to-date survey on previous work in this young field of research. Then we propose a light field representation based on image data and additional per-pixel depth values. This enables us to reconstruct arbitrary views of the scene in an efficient way and with high quality. Furtermore, we can use the same representation to determine optimal reference views during the acquisition of a light field. We further present the so-called free form parameterization, which allows for a relatively free placement of reference views. Finally, we demonstrate a prototype of the Lumi-Shelf system, which acquires, transmits, and renders the light field of a dynamic scene at multiple frames per second.Diese Doktorarbeit beschäftigt sich mit der Repräsentierung dreidimensionaler Szenen durch Bilddaten (engl. image-based rendering, deutsch bildbasierte Bildsynthese), speziell mit dem Ansatz des sog. Lichtfelds. Nach einem aktuellen Überblick über bisherige Arbeiten in diesem jungen Forschungsgebiet stellen wir eine Datenrepräsentation vor, die auf Bilddaten mit zusätzlichen Tiefenwerten basiert. Damit sind wir in der Lage, beliebige Ansichten der Szene effizient und in hoher Qualität zu rekonstruieren sowie die optimalen Referenz-Ansichten bei der Akquisition eines Lichtfelds zu bestimmen. Weiterhin präsentieren wir die sog. Freiform-Parametrisierung, die eine relativ freie Anordnung der Referenz-Ansichten erlaubt. Abschließend demonstrieren wir einen Prototyp des Lumishelf-Systems, welches die Aufnahme, Übertragung und Darstellung des Lichtfeldes einer dynamischen Szene mit mehreren Bildern pro Sekunde ermöglicht

Efficient acquisition, representation and rendering of light fields

In this thesis we discuss the representation of three-dimensional scenes using image data (image-based rendering), and more precisely the so-called light field approach. We start with an up-to-date survey on previous work in this young field of research. Then we propose a light field representation based on image data and additional per-pixel depth values. This enables us to reconstruct arbitrary views of the scene in an efficient way and with high quality. Furtermore, we can use the same representation to determine optimal reference views during the acquisition of a light field. We further present the so-called free form parameterization, which allows for a relatively free placement of reference views. Finally, we demonstrate a prototype of the Lumi-Shelf system, which acquires, transmits, and renders the light field of a dynamic scene at multiple frames per second.Diese Doktorarbeit beschäftigt sich mit der Repräsentierung dreidimensionaler Szenen durch Bilddaten (engl. image-based rendering, deutsch bildbasierte Bildsynthese), speziell mit dem Ansatz des sog. Lichtfelds. Nach einem aktuellen Überblick über bisherige Arbeiten in diesem jungen Forschungsgebiet stellen wir eine Datenrepräsentation vor, die auf Bilddaten mit zusätzlichen Tiefenwerten basiert. Damit sind wir in der Lage, beliebige Ansichten der Szene effizient und in hoher Qualität zu rekonstruieren sowie die optimalen Referenz-Ansichten bei der Akquisition eines Lichtfelds zu bestimmen. Weiterhin präsentieren wir die sog. Freiform-Parametrisierung, die eine relativ freie Anordnung der Referenz-Ansichten erlaubt. Abschließend demonstrieren wir einen Prototyp des Lumishelf-Systems, welches die Aufnahme, Übertragung und Darstellung des Lichtfeldes einer dynamischen Szene mit mehreren Bildern pro Sekunde ermöglicht

Low Bit-rate Color Video Compression using Multiwavelets in Three Dimensions

In recent years, wavelet-based video compressions have become a major focus of research because of the advantages that it provides. More recently, a growing thrust of studies explored the use of multiple scaling functions and multiple wavelets with desirable properties in various fields, from image de-noising to compression. In term of data compression, multiple scaling functions and wavelets offer a greater flexibility in coefficient quantization at high compression ratio than a comparable single wavelet. The purpose of this research is to investigate the possible improvement of scalable wavelet-based color video compression at low bit-rates by using three-dimensional multiwavelets. The first part of this work included the development of the spatio-temporal decomposition process for multiwavelets and the implementation of an efficient 3-D SPIHT encoder/decoder as a common platform for performance evaluation of two well-known multiwavelet systems against a comparable single wavelet in low bitrate color video compression. The second part involved the development of a motion-compensated 3-D compression codec and a modified SPIHT algorithm designed specifically for this codec by incorporating an advantage in the design of 2D SPIHT into the 3D SPIHT coder. In an experiment that compared their performances, the 3D motion-compensated codec with unmodified 3D SPIHT had gains of 0.3dB to 4.88dB over regular 2D wavelet-based motion-compensated codec using 2D SPIHT in the coding of 19 endoscopy sequences at 1/40 compression ratio. The effectiveness of the modified SPIHT algorithm was verified by the results of a second experiment in which it was used to re-encode 4 of the 19 sequences with lowest performance gains and improved them by 0.5dB to 1.0dB. The last part of the investigation examined the effect of multiwavelet packet on 3-D video compression as well as the effects of coding multiwavelet packets based on the frequency order and energy content of individual subbands

Human-Centric Machine Vision

Recently, the algorithms for the processing of the visual information have greatly evolved, providing efficient and effective solutions to cope with the variability and the complexity of real-world environments. These achievements yield to the development of Machine Vision systems that overcome the typical industrial applications, where the environments are controlled and the tasks are very specific, towards the use of innovative solutions to face with everyday needs of people. The Human-Centric Machine Vision can help to solve the problems raised by the needs of our society, e.g. security and safety, health care, medical imaging, and human machine interface. In such applications it is necessary to handle changing, unpredictable and complex situations, and to take care of the presence of humans

Camera positioning for 3D panoramic image rendering

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.Virtual camera realisation and the proposition of trapezoidal camera architecture are the two broad contributions of this thesis. Firstly, multiple camera and their arrangement constitute a critical component which affect the integrity of visual content acquisition for multi-view video. Currently, linear, convergence, and divergence arrays are the prominent camera topologies adopted. However, the large number of cameras required and their synchronisation are two of prominent challenges usually encountered. The use of virtual cameras can significantly reduce the number of physical cameras used with respect to any of the known camera structures, hence adequately reducing some of the other implementation issues. This thesis explores to use image-based rendering with and without geometry in the implementations leading to the realisation of virtual cameras. The virtual camera implementation was carried out from the perspective of depth map (geometry) and use of multiple image samples (no geometry). Prior to the virtual camera realisation, the generation of depth map was investigated using region match measures widely known for solving image point correspondence problem. The constructed depth maps have been compare with the ones generated using the dynamic programming approach. In both the geometry and no geometry approaches, the virtual cameras lead to the rendering of views from a textured depth map, construction of 3D panoramic image of a scene by stitching multiple image samples and performing superposition on them, and computation of virtual scene from a stereo pair of panoramic images. The quality of these rendered images were assessed through the use of either objective or subjective analysis in Imatest software. Further more, metric reconstruction of a scene was performed by re-projection of the pixel points from multiple image samples with a single centre of projection. This was done using sparse bundle adjustment algorithm. The statistical summary obtained after the application of this algorithm provides a gauge for the efficiency of the optimisation step. The optimised data was then visualised in Meshlab software environment, hence providing the reconstructed scene. Secondly, with any of the well-established camera arrangements, all cameras are usually constrained to the same horizontal plane. Therefore, occlusion becomes an extremely challenging problem, and a robust camera set-up is required in order to resolve strongly the hidden part of any scene objects. To adequately meet the visibility condition for scene objects and given that occlusion of the same scene objects can occur, a multi-plane camera structure is highly desirable. Therefore, this thesis also explore trapezoidal camera structure for image acquisition. The approach here is to assess the feasibility and potential of several physical cameras of the same model being sparsely arranged on the edge of an efficient trapezoid graph. This is implemented both Matlab and Maya. The quality of the depth maps rendered in Matlab are better in Quality

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Image Registration Workshop Proceedings

Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research