1,235 research outputs found

    Motion and disparity estimation with self adapted evolutionary strategy in 3D video coding

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    Real world information, obtained by humans is three dimensional (3-D). In experimental user-trials, subjective assessments have clearly demonstrated the increased impact of 3-D pictures compared to conventional flat-picture techniques. It is reasonable, therefore, that we humans want an imaging system that produces pictures that are as natural and real as things we see and experience every day. Three-dimensional imaging and hence, 3-D television (3DTV) are very promising approaches expected to satisfy these desires. Integral imaging, which can capture true 3D color images with only one camera, has been seen as the right technology to offer stress-free viewing to audiences of more than one person. In this paper, we propose a novel approach to use Evolutionary Strategy (ES) for joint motion and disparity estimation to compress 3D integral video sequences. We propose to decompose the integral video sequence down to viewpoint video sequences and jointly exploit motion and disparity redundancies to maximize the compression using a self adapted ES. A half pixel refinement algorithm is then applied by interpolating macro blocks in the previous frame to further improve the video quality. Experimental results demonstrate that the proposed adaptable ES with Half Pixel Joint Motion and Disparity Estimation can up to 1.5 dB objective quality gain without any additional computational cost over our previous algorithm.1Furthermore, the proposed technique get similar objective quality compared to the full search algorithm by reducing the computational cost up to 90%

    Exploring the Potential of 3D Visualization Techniques for Usage in Collaborative Design

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    Best practice for collaborative design demands good interaction between its collaborators. The capacity to share common knowledge about design models at hand is a basic requirement. With current advancing technologies gathering collective knowledge is more straightforward, as the dialog between experts can be supported better. The potential for 3D visualization techniques to become the right support tool for collaborative design is explored. Special attention is put on the possible usage for remote collaboration. The opportunities for current state-of-the-art visualization techniques from stereoscopic vision to holographic displays are researched. A classification of the various systems is explored with respect to their tangible usage for augmented reality. Appropriate interaction methods can be selected based on the usage scenario

    A compressive light field projection system

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    For about a century, researchers and experimentalists have strived to bring glasses-free 3D experiences to the big screen. Much progress has been made and light field projection systems are now commercially available. Unfortunately, available display systems usually employ dozens of devices making such setups costly, energy inefficient, and bulky. We present a compressive approach to light field synthesis with projection devices. For this purpose, we propose a novel, passive screen design that is inspired by angle-expanding Keplerian telescopes. Combined with high-speed light field projection and nonnegative light field factorization, we demonstrate that compressive light field projection is possible with a single device. We build a prototype light field projector and angle-expanding screen from scratch, evaluate the system in simulation, present a variety of results, and demonstrate that the projector can alternatively achieve super-resolved and high dynamic range 2D image display when used with a conventional screen.MIT Media Lab ConsortiumNatural Sciences and Engineering Research Council of Canada (NSERC Postdoctoral Fellowship)National Science Foundation (U.S.) (Grant NSF grant 0831281

    Efficient rendering for three-dimensional displays

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    This thesis explores more efficient methods for visualizing point data sets on three-dimensional (3D) displays. Point data sets are used in many scientific applications, e.g. cosmological simulations. Visualizing these data sets in {3D} is desirable because it can more readily reveal structure and unknown phenomena. However, cutting-edge scientific point data sets are very large and producing/rendering even a single image is expensive. Furthermore, current literature suggests that the ideal number of views for 3D (multiview) displays can be in the hundreds, which compounds the costs. The accepted notion that many views are required for {3D} displays is challenged by carrying out a novel human factor trials study. The results suggest that humans are actually surprisingly insensitive to the number of viewpoints with regard to their task performance, when occlusion in the scene is not a dominant factor. Existing stereoscopic rendering algorithms can have high set-up costs which limits their use and none are tuned for uncorrelated {3D} point rendering. This thesis shows that it is possible to improve rendering speeds for a low number of views by perspective reprojection. The novelty in the approach described lies in delaying the reprojection and generation of the viewpoints until the fragment stage of the pipeline and streamlining the rendering pipeline for points only. Theoretical analysis suggests a fragment reprojection scheme will render at least 2.8 times faster than na\"{i}vely re-rendering the scene from multiple viewpoints. Building upon the fragment reprojection technique, further rendering performance is shown to be possible (at the cost of some rendering accuracy) by restricting the amount of reprojection required according to the stereoscopic resolution of the display. A significant benefit is that the scene depth can be mapped arbitrarily to the perceived depth range of the display at no extra cost than a single region mapping approach. Using an average case-study (rendering from a 500k points for a 9-view High Definition 3D display), theoretical analysis suggests that this new approach is capable of twice the performance gains than simply reprojecting every single fragment, and quantitative measures show the algorithm to be 5 times faster than a naïve rendering approach. Further detailed quantitative results, under varying scenarios, are provided and discussed
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