Holoscopic 3D image depth estimation and segmentation techniques

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonToday’s 3D imaging techniques offer significant benefits over conventional 2D imaging techniques. The presence of natural depth information in the scene affords the observer an overall improved sense of reality and naturalness. A variety of systems attempting to reach this goal have been designed by many independent research groups, such as stereoscopic and auto-stereoscopic systems. Though the images displayed by such systems tend to cause eye strain, fatigue and headaches after prolonged viewing as users are required to focus on the screen plane/accommodation to converge their eyes to a point in space in a different plane/convergence. Holoscopy is a 3D technology that targets overcoming the above limitations of current 3D technology and was recently developed at Brunel University. This work is part W4.1 of the 3D VIVANT project that is funded by the EU under the ICT program and coordinated by Dr. Aman Aggoun at Brunel University, West London, UK. The objective of the work described in this thesis is to develop estimation and segmentation techniques that are capable of estimating precise 3D depth, and are applicable for holoscopic 3D imaging system. Particular emphasis is given to the task of automatic techniques i.e. favours algorithms with broad generalisation abilities, as no constraints are placed on the setting. Algorithms that provide invariance to most appearance based variation of objects in the scene (e.g. viewpoint changes, deformable objects, presence of noise and changes in lighting). Moreover, have the ability to estimate depth information from both types of holoscopic 3D images i.e. Unidirectional and Omni-directional which gives horizontal parallax and full parallax (vertical and horizontal), respectively. The main aim of this research is to develop 3D depth estimation and 3D image segmentation techniques with great precision. In particular, emphasis on automation of thresholding techniques and cues identifications for development of robust algorithms. A method for depth-through-disparity feature analysis has been built based on the existing correlation between the pixels at a one micro-lens pitch which has been exploited to extract the viewpoint images (VPIs). The corresponding displacement among the VPIs has been exploited to estimate the depth information map via setting and extracting reliable sets of local features. ii Feature-based-point and feature-based-edge are two novel automatic thresholding techniques for detecting and extracting features that have been used in this approach. These techniques offer a solution to the problem of setting and extracting reliable features automatically to improve the performance of the depth estimation related to the generalizations, speed and quality. Due to the resolution limitation of the extracted VPIs, obtaining an accurate 3D depth map is challenging. Therefore, sub-pixel shift and integration is a novel interpolation technique that has been used in this approach to generate super-resolution VPIs. By shift and integration of a set of up-sampled low resolution VPIs, the new information contained in each viewpoint is exploited to obtain a super resolution VPI. This produces a high resolution perspective VPI with wide Field Of View (FOV). This means that the holoscopic 3D image system can be converted into a multi-view 3D image pixel format. Both depth accuracy and a fast execution time have been achieved that improved the 3D depth map. For a 3D object to be recognized the related foreground regions and depth information map needs to be identified. Two novel unsupervised segmentation methods that generate interactive depth maps from single viewpoint segmentation were developed. Both techniques offer new improvements over the existing methods due to their simple use and being fully automatic; therefore, producing the 3D depth interactive map without human interaction. The final contribution is a performance evaluation, to provide an equitable measurement for the extent of the success of the proposed techniques for foreground object segmentation, 3D depth interactive map creation and the generation of 2D super-resolution viewpoint techniques. The no-reference image quality assessment metrics and their correlation with the human perception of quality are used with the help of human participants in a subjective manner

Real-Time Algorithms for High Dynamic Range Video

A recurring problem in capturing video is the scene having a range of brightness values that exceeds the capabilities of the capturing device. An example would be a video camera in a bright outside area, directed at the entrance of a building. Because of the potentially big brightness difference, it may not be possible to capture details of the inside of the building and the outside simultaneously using just one shutter speed setting. This results in under- and overexposed pixels in the video footage. The approach we follow in this thesis to overcome this problem is temporal exposure bracketing, i.e., using a set of images captured in quick sequence at different shutter settings. Each image then captures one facet of the scene's brightness range. When fused together, a high dynamic range (HDR) video frame is created that reveals details in dark and bright regions simultaneously. The process of creating a frame in an HDR video can be thought of as a pipeline where the output of each step is the input to the subsequent one. It begins by capturing a set of regular images using varying shutter speeds. Next, the images are aligned with respect to each other to compensate for camera and scene motion during capture. The aligned images are then merged together to create a single HDR frame containing accurate brightness values of the entire scene. As a last step, the HDR frame is tone mapped in order to be displayable on a regular screen with a lower dynamic range. This thesis covers algorithms for these steps that allow the creation of HDR video in real-time. When creating videos instead of still images, the focus lies on high capturing and processing speed and on assuring temporal consistency between the video frames. In order to achieve this goal, we take advantage of the knowledge gained from the processing of previous frames in the video. This work addresses the following aspects in particular. The image size parameters for the set of base images are chosen such that only as little image data as possible is captured. We make use of the fact that it is not always necessary to capture full size images when only small portions of the scene require HDR. Avoiding redundancy in the image material is an obvious approach to reducing the overall time taken to generate a frame. With the aid of the previous frames, we calculate brightness statistics of the scene. The exposure values are chosen in a way, such that frequently occurring brightness values are well-exposed in at least one of the images in the sequence. The base images from which the HDR frame is created are captured in quick succession. The effects of intermediate camera motion are thus less intense than in the still image case, and a comparably simpler camera motion model can be used. At the same time, however, there is much less time available to estimate motion. For this reason, we use a fast heuristic that makes use of the motion information obtained in previous frames. It is robust to the large brightness difference between the images of an exposure sequence. The range of luminance values of an HDR frame must be tone mapped to the displayable range of the output device. Most available tone mapping operators are designed for still images and scale the dynamic range of each frame independently. In situations where the scene's brightness statistics change quickly, these operators produce visible image flicker. We have developed an algorithm that detects such situations in an HDR video. Based on this detection, a temporal stability criterion for the tone mapping parameters then prevents image flicker. All methods for capture, creation and display of HDR video introduced in this work have been fully implemented, tested and integrated into a running HDR video system. The algorithms were analyzed for parallelizability and, if applicable, adjusted and implemented on a high-performance graphics chip

Programmable Image-Based Light Capture for Previsualization

Previsualization is a class of techniques for creating approximate previews of a movie sequence in order to visualize a scene prior to shooting it on the set. Often these techniques are used to convey the artistic direction of the story in terms of cinematic elements, such as camera movement, angle, lighting, dialogue, and character motion. Essentially, a movie director uses previsualization (previs) to convey movie visuals as he sees them in his minds-eye . Traditional methods for previs include hand-drawn sketches, Storyboards, scaled models, and photographs, which are created by artists to convey how a scene or character might look or move. A recent trend has been to use 3D graphics applications such as video game engines to perform previs, which is called 3D previs. This type of previs is generally used prior to shooting a scene in order to choreograph camera or character movements. To visualize a scene while being recorded on-set, directors and cinematographers use a technique called On-set previs, which provides a real-time view with little to no processing. Other types of previs, such as Technical previs, emphasize accurately capturing scene properties but lack any interactive manipulation and are usually employed by visual effects crews and not for cinematographers or directors. This dissertation\u27s focus is on creating a new method for interactive visualization that will automatically capture the on-set lighting and provide interactive manipulation of cinematic elements to facilitate the movie maker\u27s artistic expression, validate cinematic choices, and provide guidance to production crews. Our method will overcome the drawbacks of the all previous previs methods by combining photorealistic rendering with accurately captured scene details, which is interactively displayed on a mobile capture and rendering platform. This dissertation describes a new hardware and software previs framework that enables interactive visualization of on-set post-production elements. A three-tiered framework, which is the main contribution of this dissertation is; 1) a novel programmable camera architecture that provides programmability to low-level features and a visual programming interface, 2) new algorithms that analyzes and decomposes the scene photometrically, and 3) a previs interface that leverages the previous to perform interactive rendering and manipulation of the photometric and computer generated elements. For this dissertation we implemented a programmable camera with a novel visual programming interface. We developed the photometric theory and implementation of our novel relighting technique called Symmetric lighting, which can be used to relight a scene with multiple illuminants with respect to color, intensity and location on our programmable camera. We analyzed the performance of Symmetric lighting on synthetic and real scenes to evaluate the benefits and limitations with respect to the reflectance composition of the scene and the number and color of lights within the scene. We found that, since our method is based on a Lambertian reflectance assumption, our method works well under this assumption but that scenes with high amounts of specular reflections can have higher errors in terms of relighting accuracy and additional steps are required to mitigate this limitation. Also, scenes which contain lights whose colors are a too similar can lead to degenerate cases in terms of relighting. Despite these limitations, an important contribution of our work is that Symmetric lighting can also be leveraged as a solution for performing multi-illuminant white balancing and light color estimation within a scene with multiple illuminants without limits on the color range or number of lights. We compared our method to other white balance methods and show that our method is superior when at least one of the light colors is known a priori

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