Computer graphics applications such as movie effects, video gaming, and product demonstration demand 3D models of dynamic objects. For this purpose, numerous methods, such as light fields, stereo reconstruction and vi...
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ISBN:
(纸本)9781595936288
Computer graphics applications such as movie effects, video gaming, and product demonstration demand 3D models of dynamic objects. For this purpose, numerous methods, such as light fields, stereo reconstruction and visual hulls have been extended to model dynamic objects. These methods use multiple cameras to acquire images simultaneously and use the synchronized samples to reconstruct the model for each time instance. However, a large number of cameras are required to obtain compelling results. We introduce an efficient acquisition and modeling schema for dynamic objects with repetitive motions. Our method requires as few as two cameras. The key idea is that repetitive motions can be described by a finite number of states. images capturing the same state can be grouped together and fed to the later modeling phase as if they are captured from multiple cameras simultaneously. Our work includes an acquisition system with interactive feedback, a graph traversal algorithm to help obtain a near minimum subset of images to sample the object and its motion, and a space-time image optimization method. We demonstrate this system using several datasets with different complexity of motion, and different number of desired viewpoints.
In this paper, we present a method for modeling a complex scene from a small set of input images taken from widely separated viewpoints and then synthesizing novel views. First, we find sparse correspondences across m...
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In this paper, we present a method for modeling a complex scene from a small set of input images taken from widely separated viewpoints and then synthesizing novel views. First, we find sparse correspondences across multiple input images and calibrate these input images taken with unknown cameras. Then one of the input images is chosen as the reference image for modeling by match propagation. A sparse set of reliably matched pixels in the reference image is initially selected and then propagated to neighboring pixels based on both the clustering-based light invariant photoconsistency constraint and the data-driven depth smoothness constraint, which are integrated into a pixel matching quality function to efficiently deal with occlusions, light changes and depth discontinuity. Finally, a novel view rendering algorithm is developed to fast synthesize a novel view by match propagation again. Experimental results show that the proposed method can produce good scene models from a small set of widely separated images and synthesize novel views in good quality. (c) 2006 Elsevier B.V. All rights reserved.
This article proposes a technique to animate a Chinese style painting given its image. We first extract descriptions of the brush strokes that hypothetically produced it. The key to the extraction process is the use o...
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This article proposes a technique to animate a Chinese style painting given its image. We first extract descriptions of the brush strokes that hypothetically produced it. The key to the extraction process is the use of a brush stroke library, which is obtained by digitizing single brush strokes drawn by an experienced artist. The steps in our extraction technique are first to segment the input image, then to find the best set of brush strokes that fit the regions, and, finally, to refine these strokes to account for local appearance. We model a single brush stroke using its skeleton and contour, and we characterize texture variation within each stroke by sampling perpendicularly along its skeleton. Once these brush descriptions have been obtained, the painting can be animated at the brush stroke level. In this article, we focus on Chinese paintings with relatively sparse strokes. The animation is produced using a graphical application we developed. We present several animations of real paintings using our technique.
This paper proposes a visual representation named scene tunnel for capturing urban scenes along routes and visualizing them on the Internet. We scan scenes with multiple cameras or a fish- eye camera on a moving vehic...
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This paper proposes a visual representation named scene tunnel for capturing urban scenes along routes and visualizing them on the Internet. We scan scenes with multiple cameras or a fish- eye camera on a moving vehicle, which generates a real scene archive along streets that is more complete than previously proposed route panoramas. Using a translating spherical eye, properly set planes of scanning, and unique parallel- central projection, we explore the image acquisition of the scene tunnel from camera selection and alignment, slit calculation, scene scanning, to image integration. The scene tunnels cover high buildings, ground, and various viewing directions and have uniformed resolutions along the street. The sequentially organized scene tunnel benefits texture mapping onto the urban models. We analyze the shape characteristics in the scene tunnels for designing visualization algorithms. After combining this with a global panorama and forward image caps, the capped scene tunnels can provide continuous views directly for virtual or real navigation in a city. We render scene tunnel dynamically by view warping, fast transmission, and flexible interaction. The compact and continuous scene tunnel facilitates model construction, data streaming, and seamless route traversing on the Internet and mobile devices.
This paper proposes a visual representation named scene tunnel for capturing urban scenes along routes and visualizing them on the Internet. We scan scenes with multiple cameras or a fish- eye camera on a moving vehic...
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This paper proposes a visual representation named scene tunnel for capturing urban scenes along routes and visualizing them on the Internet. We scan scenes with multiple cameras or a fish- eye camera on a moving vehicle, which generates a real scene archive along streets that is more complete than previously proposed route panoramas. Using a translating spherical eye, properly set planes of scanning, and unique parallel- central projection, we explore the image acquisition of the scene tunnel from camera selection and alignment, slit calculation, scene scanning, to image integration. The scene tunnels cover high buildings, ground, and various viewing directions and have uniformed resolutions along the street. The sequentially organized scene tunnel benefits texture mapping onto the urban models. We analyze the shape characteristics in the scene tunnels for designing visualization algorithms. After combining this with a global panorama and forward image caps, the capped scene tunnels can provide continuous views directly for virtual or real navigation in a city. We render scene tunnel dynamically by view warping, fast transmission, and flexible interaction. The compact and continuous scene tunnel facilitates model construction, data streaming, and seamless route traversing on the Internet and mobile devices.
The ability to change illumination is a crucial factor in image-based modeling and rendering. image-based relighting offers such capability. However, the tradeoff is the enormous increase of storage requirement. In th...
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The ability to change illumination is a crucial factor in image-based modeling and rendering. image-based relighting offers such capability. However, the tradeoff is the enormous increase of storage requirement. In this paper, we propose a compression scheme that effectively reduces the data volume while maintaining the real-time relighting capability. The proposed method is based on principal component analysis (PCA). A block-wise PCA is used to practically process the huge input data. The output of PCA is a set of eigenimages and the corresponding relighting coefficients. By dropping those low-energy eigenimages, the data size is drastically reduced. To further compress the data, eigenimages left are compressed using transform coding and quantization while the relighting coefficients are compressed using uniform quantization. We also suggest the suitable target bit rate for each phase of the compression method in order to preserve the visual quality. Finally, we propose a real-time engine that relights images from the compressed data.
We present an approach for modeling and rendering a dynamic, real-world event from an arbitrary viewpoint, and at any time, using images captured from multiple video cameras. The event is modeled as a nonrigidly varyi...
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We present an approach for modeling and rendering a dynamic, real-world event from an arbitrary viewpoint, and at any time, using images captured from multiple video cameras. The event is modeled as a nonrigidly varying dynamic scene, captured by many images from different viewpoints, at discrete times. First, the spatio-temporal geometric properties (shape and instantaneous motion) are computed. The view synthesis problem is then solved using a reverse mapping algorithm, ray-casting across space and time, to compute a novel image from any viewpoint in the 4D space of position and time. Results are shown on real-world events captured in the CMU 3D Room, by creating synthetic renderings of the event from novel, arbitrary positions in space and time. Multiple such recreated renderings can be put together to create retimed fly-by movies of the event, with the resulting visual experience richer than that of a regular video clip, or switching between images from multiple cameras.
We address the problem of estimating the three-dimensional shape and complex appearance of a scene from a calibrated set of views under fixed illumination. Our approach relies on a rank condition that must be satisfie...
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We address the problem of estimating the three-dimensional shape and complex appearance of a scene from a calibrated set of views under fixed illumination. Our approach relies on a rank condition that must be satisfied when the scene exhibits "specular + diffuse" reflectance characteristics. This constraint is used to define a cost functional for the discrepancy between the measured images and those generated by the estimate of the scene, rather than attempting to match image-to-image directly. Minimizing such a functional yields the optimal estimate of the shape of the scene, represented by a dense surface, as well as its radiance, represented by four functions defined on such a surface. These can be used to generate novel views that capture the non-Lambertian appearance of the scene.
This paper presents a novel scheme based on a hybrid NPR/IBMR approach, for providing non-photorealistic virtual environment navigation from images. As a preprocess, we first divide the background and the foreground c...
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This paper presents a novel scheme based on a hybrid NPR/IBMR approach, for providing non-photorealistic virtual environment navigation from images. As a preprocess, we first divide the background and the foreground components in the image and then construct a simple 3D scene model consisting of background model and foreground object models, together with the corresponding non-photorealistic texture maps. Thus, through interactive navigation at runtime, non-photorealistic walk-through images for novel viewpoints can be generated in real time. To reduce visual artifacts in the resulting animation, we propose an effective method for generating multiresolution and view-dependent nonphotorealistic texture maps that preserve the stroke size and coherence across different viewing resolutions and angles.
A compact visual representation, called the 3D layered, adaptive-resolution, and multi-perspective panorama (LAMP), is proposed for representing large-scale 3D scenes with large variations of depths and obvious occlus...
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A compact visual representation, called the 3D layered, adaptive-resolution, and multi-perspective panorama (LAMP), is proposed for representing large-scale 3D scenes with large variations of depths and obvious occlusions. Two kinds of 3D LAMP representations are proposed: the relief-like LAMP and the image-based LAMP. Both types of LAMPs concisely represent almost all the information from a long image sequence. Methods to construct LAMP representations from video sequences with dominant translation are provided. The relief-like LAMP is basically a single extended multi-perspective panoramic view image. Each pixel has a pair of texture and depth values, but each pixel may also have multiple pairs of texture-depth values to represent occlusion in layers, in addition to adaptive resolution changing with depth. The image-based LAMP, on the other hand, consists of a set of multi-perspective layers, each of which has a pair of 2D texture and depth maps, but with adaptive time-sampling scales depending on depths of scene points. Several examples of 3D LAMP construction for real image sequences are given. The 3D LAMP is a concise and powerful representation for image-basedrendering. (C) 2004 Elsevier Inc. All rights reserved.
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