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Providing a wider movement range of virtual camera is an unsolved problem for state-of-the-art image-based rendering system. In this paper, we present a new image based rendering technology called pan- oramic mosaics of slit image...
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Providing a wider movement range of virtual camera is an unsolved problem for state-of-the-art image-based rendering system. In this paper, we present a new image based rendering technology called pan- oramic mosaics of slit images with depth that can provide large virtual camera motion region for some scenes. By limiting camera motion to a horizontal plane only, a slit image with united depth value is used as the ren- dering element.
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摘要 :
Providing a wider movement range of virtual camera is an unsolvedproblem for state-of-the-art image-based rendering system. In thispaper, we present a new image based rendering technology called pan-oramic mosaics of slit images w...
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Providing a wider movement range of virtual camera is an unsolvedproblem for state-of-the-art image-based rendering system. In thispaper, we present a new image based rendering technology called pan-oramic mosaics of slit images with depth that can provide largevirtual camera motion region for some scenes. By limiting cameramotion to a horizontal plane only, a slit image with united depthvalue is used as the ren- dering element.
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摘要 :
Providing a wide movement range of virtual camera is an unsolved problem for state-of-the-art image-based rendering system. In this paper, we present a new image based rendering technology called panoramic mosaics of slit images w...
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Providing a wide movement range of virtual camera is an unsolved problem for state-of-the-art image-based rendering system. In this paper, we present a new image based rendering technology called panoramic mosaics of slit images with depth that can provide large virtual camera motion region of some scenes. By limiting camera motion to a horizontal plane only, a slit image with united depth value is used as the rendering element. The panoramic mosaics of slit images with depth are easy to capture, and the data size is as small as that of panorama. We present here the capturing, construction as well as rendering process of panoramic slit images mosaic with depth. In addition, we present the joint up process of multiple panoramic slit images mosaic with depth.
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Volumetric three-dimensional (3-D) displays allow the user to explore a 3-D scene free of joysticks, keyboards, goggles, or trackers. For non-trivial scenes, computing and transferring a 3-D image to the display takes hundreds of ...
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Volumetric three-dimensional (3-D) displays allow the user to explore a 3-D scene free of joysticks, keyboards, goggles, or trackers. For non-trivial scenes, computing and transferring a 3-D image to the display takes hundreds of seconds, which is a serious bottleneck for many applications. We propose to represent the 3-D scene with an occlusion camera reference image (OCRI). The OCRI is a compact scene representation that stores only and all scene samples that are visible from a viewing volume centered at a reference viewpoint. The OCRI enables computing and transferring the 3-D image an order of magnitude faster than when the entire scene is processed. The OCRI approach can be readily applied to several volumetric display technologies; we have tested the OCRI approach with good results on a volumetric display that creates a 3-D image by projecting 2-D scene slices onto a rotating screen.
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Rendering of virtual views in interactive streaming of compressed image-based scene representations requires random access to arbitrary parts of the reference image data. The degree of interframe dependencies exploited during enco...
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Rendering of virtual views in interactive streaming of compressed image-based scene representations requires random access to arbitrary parts of the reference image data. The degree of interframe dependencies exploited during encoding has an impact on the transmission and decoding time and, at the same time, delimits the (storage) rate-distortion (RD) tradeoff that can be achieved. In this work, we extend the classical RD optimization approach using hybrid video coding concepts to a tradeoff between the storage rate (R), distortion (D), transmission data rate (T), and decoding complexity (C). We present a theoretical model for this RDTC space with a focus on the decoding complexity and, in addition, the impact of client side caching on the RDTC measures is considered and evaluated. Experimental results qualitatively match those predicted by our theoretical models and show that an adaptation of the encoding process to scenario specific parameters like computational power of the receiver and channel throughput can significantly reduce the user-perceived delay or required storage for RDTC optimized streams compared to RD optimized or independently encoded scene representations.
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Interactive streaming of compressed image-based scene representations requires random access to the reference image data. The degree of interframe dependencies exploited during encoding has an impact on the transmission and decodi...
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Interactive streaming of compressed image-based scene representations requires random access to the reference image data. The degree of interframe dependencies exploited during encoding has an impact on the transmission and decoding time and, at the same time, delimits the (storage) rate-distortion (RD) tradeoff that can be achieved. The transmission data rate and the decoding complexity at the client have received attention in the literature, but their incorporation into the optimization procedure for compression and streaming is missing. If scenario-specific measures are considered, the traditional RD optimization can be extended to a tradeoff between the (storage) rate (R), distortion (D), transmission data rate (T), and decoding complexity (C). In the first part of this sequel of papers, we have theoretically analyzed the RDTC space for the compression of densely sampled image-based scene representations. In this second part, we consider practical RDTC optimization. We propose a modeling and encoding parameter selection procedure that allows us to adapt the compression to scenario-specific properties. The impact of client side caching is considered and evaluated using an experimental testbed. Our results show a significant reduction of the user perceived delay, memory consumption or required minimum channel and storage bitrate for RDTC optimized streams compared to classical RD optimized or independently encoded scene representations.
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This paper proposes a movable image-based rendering (M-IBR) system for improving the viewing freedom and environmental modeling capability of conventional static IBR systems. The system supports object-based rendering and 3-D reco...
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This paper proposes a movable image-based rendering (M-IBR) system for improving the viewing freedom and environmental modeling capability of conventional static IBR systems. The system supports object-based rendering and 3-D reconstruction capability and consists of three main components. An improved video stabilization method to reduce the shaky motion frequently encountered in movable IBR systems. It employs local polynomial regression (LPR) to automatically select an appropriate bandwidth for smoothing the estimated motion.
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Over the last several decades, developments in underwater laser line scan (LLS) serial imaging sensors have resulted in significant improvements in turbid water imaging performance. In the last few years, there has been renewed in...
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Over the last several decades, developments in underwater laser line scan (LLS) serial imaging sensors have resulted in significant improvements in turbid water imaging performance. In the last few years, there has been renewed interest in distributed, truly multistatic time-varying intensity (TVI) (i.e., multiple transmitter nonsynchronous LLS) sensor configurations. In addition to being capable of high-quality image acquisition through tens of beam attenuation lengths, while simultaneously establishing a non-line-of-sight free-space communications link, these system architectures also have the potential to provide a more synoptic image coverage of larger regions of seabed and the flexibility to simultaneously examine a target from different perspectives. A related issue worth investigation is how to utilize these capabilities to improve rendering of the underwater scenes. In this regard, light field rendering (LFR)—a type of image-based rendering (IBR) technique—offers several advantages. Compared to other IBR techniques, LFR can provide signal-to-noise ratio (SNR) improvements and the ability to image through obscuring objects in front of the target. On the other hand, multistatic nonsynchronous LLS can be readily configured to acquire image sequences needed to generate LFR. This paper investigates the application of LFR to images taken from a distributed bistatic nonsynchronous LLS imager using both line-of-sight and non-line-of-sight imaging geometries to create multiperspective rendering of an unknown underwater scene. The issues related to effectively applying this technique to underwater LLS imagery are analyzed and an image postprocessing flow to address these issues is proposed. The results from a series of experiments at the Harbor Branch Oceanographic Institute at the Florida Atlantic University (HBOI–FAU, Fort Pierce, FL, USA) optical imaging test tank demonstrated the capability of using bistatic/multistatic nonsynch- onous LLS system to generated LFR and, therefore, verify the proposed image processing flow. The benefits of LFR to underwater imaging in challenging environments were further demonstrated via imaging against a variety of obstacles such as mesh screens, bubbles, and water at different turbidity. Image quality metrics based on mutual information and texture features were used in the analysis of the experimental results.
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The plenoptic function (POF) provides a powerful conceptual tool for describing a number of problems in image/video processing, vision, and graphics. For example, image-based rendering is shown as sampling and interpolation of the...
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The plenoptic function (POF) provides a powerful conceptual tool for describing a number of problems in image/video processing, vision, and graphics. For example, image-based rendering is shown as sampling and interpolation of the POF. In such applications, it is important to characterize the bandwidth of the POF. We study a simple but representative model of the scene where band-limited signals (e.g., texture images) are “painted” on smooth surfaces (e.g., of objects or walls). We show that, in general, the POF is not band limited unless the surfaces are flat. We then derive simple rules to estimate the essential bandwidth of the POF for this model. Our analysis reveals that, in addition to the maximum and minimum depths and the maximum frequency of painted signals, the bandwidth of the POF also depends on the maximum surface slope. With a unifying formalism based on multidimensional signal processing, we can verify several key results in POF processing, such as induced filtering in space and depth-corrected interpolation, and quantify the necessary sampling rates.
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We propose a new approach to quantitatively analyze the rendering quality of image-based rendering (IBR) algorithms with depth information. The resulting error bounds for synthesized views depend on IBR configurations including t...
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We propose a new approach to quantitatively analyze the rendering quality of image-based rendering (IBR) algorithms with depth information. The resulting error bounds for synthesized views depend on IBR configurations including the depth and intensity estimate errors, the scene geometry and texture, the number of actual cameras, their positions and resolution. Specifically, the IBR error is bounded by the summation of three terms, highlighting the impact of using multiple actual cameras, the impact of the noise level at the actual cameras, and the impact of the depth accuracy. We also quantify the impact of occlusions and intensity discontinuities. The proposed methodology is applicable to a large class of common IBR algorithms and can be applied locally. Experiments with synthetic and real scenes show that the developed error bounds accurately characterize the rendering errors. In particular, the error bounds correctly characterize the decay rates of synthesized views' mean absolute errors as $ {cal O}(lambda ^{-1})$ and $ {cal O}(lambda ^{-2})$, where $lambda $ is the local density of actual samples, for 2-D and 3-D scenes, respectively. Finally, we discuss the implications of the proposed analysis on camera placement, budget allocation, and bit allocation.
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