360 research outputs found
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Holoscopic 3D imaging and display technology: Camera/ processing/ display
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonHoloscopic 3D imaging “Integral imaging” was first proposed by Lippmann in 1908. It has become an attractive technique for creating full colour 3D scene that exists in space. It promotes a single camera aperture for recording spatial information of a real scene and it uses a regularly spaced microlens arrays to simulate the principle of Fly’s eye technique, which creates physical duplicates of light field “true 3D-imaging technique”.
While stereoscopic and multiview 3D imaging systems which simulate human eye technique are widely available in the commercial market, holoscopic 3D imaging technology is still in the research phase. The aim of this research is to investigate spatial resolution of holoscopic 3D imaging and display technology, which includes holoscopic 3D camera, processing and display.
Smart microlens array architecture is proposed that doubles spatial resolution of holoscopic 3D camera horizontally by trading horizontal and vertical resolutions. In particular, it overcomes unbalanced pixel aspect ratio of unidirectional holoscopic 3D images. In addition, omnidirectional holoscopic 3D computer graphics rendering techniques are proposed that simplify the rendering complexity and facilitate holoscopic 3D content generation.
Holoscopic 3D image stitching algorithm is proposed that widens overall viewing angle of holoscopic 3D camera aperture and pre-processing of holoscopic 3D image filters are proposed for spatial data alignment and 3D image data processing. In addition, Dynamic hyperlinker tool is developed that offers interactive holoscopic 3D video content search-ability and browse-ability.
Novel pixel mapping techniques are proposed that improves spatial resolution and visual definition in space. For instance, 4D-DSPM enhances 3D pixels per inch from 44 3D-PPIs to 176 3D-PPIs horizontally and achieves spatial resolution of 1365 Ă— 384 3D-Pixels whereas the traditional spatial resolution is 341 Ă— 1536 3D-Pixels. In addition distributed pixel mapping is proposed that improves quality of holoscopic 3D scene in space by creating RGB-colour channel elemental images
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3D multiple description coding for error resilience over wireless networks
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Mobile communications has gained a growing interest from both customers and service providers alike in the last 1-2 decades. Visual information is used in many application domains such as remote health care, video –on demand, broadcasting, video surveillance etc. In order to enhance the visual effects of digital video content, the depth perception needs to be provided with the actual visual content. 3D video has earned a significant interest from the research community in recent years, due to the tremendous impact it leaves on viewers and its enhancement of the user’s quality of experience (QoE). In the near future, 3D video is likely to be used in most video applications, as it offers a greater sense of immersion and perceptual experience. When 3D video is compressed and transmitted over error prone channels, the associated packet loss leads to visual quality degradation. When a picture is lost or corrupted so severely that the concealment result is not acceptable, the receiver typically pauses video playback and waits for the next INTRA picture to resume decoding. Error propagation caused by employing predictive coding may degrade the video quality severely. There are several ways used to mitigate the effects of such transmission errors. One widely used technique in International Video Coding Standards is error resilience.
The motivation behind this research work is that, existing schemes for 2D colour video compression such as MPEG, JPEG and H.263 cannot be applied to 3D video content. 3D video signals contain depth as well as colour information and are bandwidth demanding, as they require the transmission of multiple high-bandwidth 3D video streams. On the other hand, the capacity of wireless channels is limited and wireless links are prone to various types of errors caused by noise, interference, fading, handoff, error burst and network congestion. Given the maximum bit rate budget to represent the 3D scene, optimal bit-rate allocation between texture and depth information rendering distortion/losses should be minimised. To mitigate the effect of these errors on the perceptual 3D video quality, error resilience video coding needs to be investigated further to offer better quality of experience (QoE) to end users.
This research work aims at enhancing the error resilience capability of compressed 3D video, when transmitted over mobile channels, using Multiple Description Coding (MDC) in order to improve better user’s quality of experience (QoE).
Furthermore, this thesis examines the sensitivity of the human visual system (HVS) when employed to view 3D video scenes. The approach used in this study is to use subjective testing in order to rate people’s perception of 3D video under error free and error prone conditions through the use of a carefully designed bespoke questionnaire.Petroleum Technology Development Fund (PTDF
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MistForm: adaptive shape changing fog screens
We present MistForm, a shape changing fog display that can support one or two users interacting with either 2D or 3D content. Mistform combines affordances from both shape changing interfaces and mid-air displays. For example, a concave display can maintain content in comfortable reach for a single user, while a convex shape can support several users engaged on individual tasks. MistForm also enables unique interaction possibilities by exploiting the synergies between shape changing interfaces and mid-air fog displays. For instance, moving the screen will affect the brightness and blurriness of the screen at specific locations around the display, creating spaces with similar (collaboration) or different visibility (personalized content). We describe the design of MistForm and analyse its inherent challenges, such as image distortion and uneven brightness on dynamic curved surfaces. We provide a machine learning approach to characterize the shape of the screen and a rendering algorithm to remove aberrations. We finally explore novel interactive possibilities and reflect on their potential and limitations
Light field image processing: an overview
Light field imaging has emerged as a technology allowing to capture richer visual information from our world. As opposed to traditional photography, which captures a 2D projection of the light in the scene integrating the angular domain, light fields collect radiance from rays in all directions, demultiplexing the angular information lost in conventional photography. On the one hand, this higher dimensional representation of visual data offers powerful capabilities for scene understanding, and substantially improves the performance of traditional computer vision problems such as depth sensing, post-capture refocusing, segmentation, video stabilization, material classification, etc. On the other hand, the high-dimensionality of light fields also brings up new challenges in terms of data capture, data compression, content editing, and display. Taking these two elements together, research in light field image processing has become increasingly popular in the computer vision, computer graphics, and signal processing communities. In this paper, we present a comprehensive overview and discussion of research in this field over the past 20 years. We focus on all aspects of light field image processing, including basic light field representation and theory, acquisition, super-resolution, depth estimation, compression, editing, processing algorithms for light field display, and computer vision applications of light field data
Cross-layer Optimized Wireless Video Surveillance
A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system.
The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion.
In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality.
The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos.
In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work.
Adviser: Song C
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