Adopting multiview pixel mapping for enhancing quality of holoscopic 3D scene in parallax barriers based holoscopic 3D displays

The Autostereoscopic multiview 3D Display is robustly developed and widely available in commercial markets. Excellent improvements are made using pixel mapping techniques and achieved an acceptable 3D resolution with balanced pixel aspect ratio in lens array technology. This paper proposes adopting multiview pixel mapping for enhancing quality constructed holoscopic 3D scene in parallax barriers based holoscopic 3D displays achieving great results. The Holoscopic imaging technology mimics the imaging system of insects, such as the fly, utilizing a single camera, equipped with a large number of micro-lenses, to capture a scene, offering rich parallax information and enhanced 3D feeling without the need of wearing specific eyewear. In addition pixel mapping and holoscopic 3D rendering tools are developed including a custom built holoscopic 3D displays to test the proposed method and carry out a like-to-like comparison.This work has been supported by European Commission under Grant FP7-ICT-2009-4 (3DVIVANT). The authors wish to ex-press their gratitude and thanks for the support given throughout the project

3D Depth Measurement for Holoscopic 3D Imaging System

Holoscopic 3D imaging is a true 3D imaging system mimics fly’s eye technique to acquire a true 3D optical model of a real scene. To reconstruct the 3D image computationally, an efficient implementation of an Auto-Feature-Edge (AFE) descriptor algorithm is required that provides an individual feature detector for integration of 3D information to locate objects in the scene. The AFE descriptor plays a key role in simplifying the detection of both edge-based and region-based objects. The detector is based on a Multi-Quantize Adaptive Local Histogram Analysis (MQALHA) algorithm. This is distinctive for each Feature-Edge (FE) block i.e. the large contrast changes (gradients) in FE are easier to localise. The novelty of this work lies in generating a free-noise 3D-Map (3DM) according to a correlation analysis of region contours. This automatically combines the exploitation of the available depth estimation technique with edge-based feature shape recognition technique. The application area consists of two varied domains, which prove the efficiency and robustness of the approach: a) extracting a set of setting feature-edges, for both tracking and mapping process for 3D depthmap estimation, and b) separation and recognition of focus objects in the scene. Experimental results show that the proposed 3DM technique is performed efficiently compared to the state-of-the-art algorithms

Size Optimization of 3D Stereoscopic Film Frames

3D stereoscopic film has inherently the problem of large frame size that many 3D images compression algorithms already investigated for exploiting complex method, outputting poorly displayed frame, andtakings a long processing time. Consequently, this paper presents the development of a unique technique of clipping the redundant areas from the frames that do not appear in 3D stereoscopic film which delivered side-by-side (SbS) format over anorthodox packet-based network. This implies reducing the size of the 3D film with natural depth perception

Real Time Holoscopic 3D Video Interlacing

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Moiré-Free Full Parallax Holoscopic 3D Display based on Cross-Lenticular

Holoscopic imaging also known as Integral imaging is a promising 3D solution that mimics the imaging system of insects, such as the fly, utilizing a single camera, equipped with a large number of microlens array, to capture a scene, offering rich parallax information and enhanced 3D feeling without the need of wearing specific eyewear. Recently, initial developments are made for designing a full parallax holoscopic 3D display using parallax barriers which suffers low lighting throughput as the constructed 3D scene is a rather dim. Also a first attempt was made designing an omnidirectional holoscopic 3D display using cross-lenticular which introduces moiré effect. This paper proposes and presents a moiré-free full parallax holoscopic 3D display which offers omnidirectional motion parallax and complete 3D depth

Dynamic Hyperlinker: Innovative Solution for 3D Video Content Search and Retrieval

Recently, 3D display technology, and content creation tools have been undergone rigorous development and as a result they have been widely adopted by home and professional users. 3D digital repositories are increasing and becoming available ubiquitously. However, searching and visualizing 3D content remains a great challenge. In this paper, we propose and present the development of a novel approach for creating hypervideos, which ease the 3D content search and retrieval. It is called the dynamic hyperlinker for 3D content search and retrieval process. It advances 3D multimedia navigability and searchability by creating dynamic links for selectable and clickable objects in the video scene whilst the user consumes the 3D video clip. The proposed system involves 3D video processing, such as detecting/tracking clickable objects, annotating objects, and metadata engineering including 3D content descriptive protocol. Such system attracts the attention from both home and professional users and more specifically broadcasters and digital content providers. The experiment is conducted on full parallax holoscopic 3D videos “also known as integral images”.ICT program as Project 3D VIVAN

Effective extrusion-based 3D printing system design for cementitious-based materials

Mycobacterium tuberculosis (M.tb) infection results in approximately 1.3 million human deaths each year. M.tb resides primarily inside macrophages, and maintains persistent infection. In response to infection and inflammation, platelet activating factor C-16 (PAF C16), a phospholipid compound, is released by various cells including neutophils and monocytes. We have recently shown that PAF C-16 can directly inhibit the growth of two representative non-pathogenic mycobacteria, Mycobacterium bovis BCG and Mycobacterium smegmatis (M. smegmatis), by damaging the bacterial cell membrane. Here, we have examined the effect of PAF C-16 on M. smegmatis residing within macrophages, and identified mechanisms involved in their growth inhibitory function. Our results demonstrated that exogenous PAF C-16 inhibited the growth of M. smegmatis inside phagocytic cells of monocytic cell line, THP1; this effect was partially blocked by PAF receptor antagonists, suggesting the involvement of PAF receptor-mediated signalling pathways. Arachidonic acid, a downstream metabolite of PAF C-16 signalling pathway, directly inhibited the growth of M. smegmatis in vitro. Moreover, the inhibition of phospholipase C and phospholipase A2 activities, involved in PAF C-16 signalling pathway, increased survival of intracellular M. smegmatis. Interestingly, we also observed that inhibition of inducible nitric oxide synthase (iNOS) enzyme and antibody-mediated neutralization of TNF-α partially mitigated the intracellular growth inhibitory effect of PAF C-16. Use of a number of PAF C-16 structural analogues, including Lyso-PAF, 2-O-methyl PAF, PAF C-18 and Hexanolamino PAF, revealed that the presence of acetyl group (CH3CO) at sn-2 position of the glycerol backbone of PAF is important for the intracellular growth inhibition activity against M. smegmatis. Taken together, these results suggest that exogenous PAF C-16 treatment inhibits intracellular M. smegmatis growth, at least partially, in a nitric oxide and TNF-α dependent manner

Latent cluster analysis of ALS phenotypes identifies prognostically differing groups

BACKGROUND Amyotrophic lateral sclerosis (ALS) is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes. METHODS Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method. RESULTS The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001). Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb) and time from symptom onset to diagnosis (p<0.00001). CONCLUSION The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research