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A Survey of Methods for Volumetric Scene Reconstruction from Photographs
"... Scene reconstruction, the task of generating a 3D model of a scene given multiple 2D photographs taken of the scene, is an old and difficult problem in computer vision. Since its introduction, scene reconstruction has found application in many fields, including robotics, virtual reality, and entert ..."
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Cited by 80 (1 self)
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Scene reconstruction, the task of generating a 3D model of a scene given multiple 2D photographs taken of the scene, is an old and difficult problem in computer vision. Since its introduction, scene reconstruction has found application in many fields, including robotics, virtual reality, and entertainment. Volumetric models are a natural choice for scene reconstruction. Three broad classes of volumetric reconstruction techniques have been developed based on geometric intersections, color consistency, and pairwise matching. Some of these techniques have spawned a number of variations and undergone considerable refinement. This paper is a survey of techniques for volumetric scene reconstruction.
Widebaseline stereo from multiple views: A probabilistic account
 In CVPR
, 2004
"... This paper describes a method for dense depth reconstruction from a small set of widebaseline images. In a widebaseline setting an inherent difficulty which complicates the stereocorrespondence problem is selfocclusion. Also, we have to consider the possibility that image pixels in different imag ..."
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Cited by 70 (7 self)
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This paper describes a method for dense depth reconstruction from a small set of widebaseline images. In a widebaseline setting an inherent difficulty which complicates the stereocorrespondence problem is selfocclusion. Also, we have to consider the possibility that image pixels in different images, which are projections of the same point in the scene, will have different color values due to nonLambertian effects or discretization errors. We propose a Bayesian approach to tackle these problems. In this framework, the images are regarded as noisy measurements of an underlying ’true ’ imagefunction. Also, the image data is considered incomplete, in the sense that we do not know which pixels from a particular image are occluded in the other images. We describe an EMalgorithm, which iterates between estimating values for all hidden quantities, and optimizing the current depth estimates. The algorithm has few free parameters, displays a stable convergence behavior and generates accurate depth estimates. The approach is illustrated with several challenging realworld examples. We also show how the algorithm can generate realistic view interpolations and how it merges the information of all images into a new, synthetic view. 1.
Camera network calibration from dynamic silhouettes
 in CVPR
, 2004
"... In this paper we present an automatic method for calibrating a network of cameras from only silhouettes. This is particularly useful for shapefromsilhouette or visualhull systems, as no additional data is needed for calibration. The key novel contribution of this work is an algorithm to robustly ..."
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Cited by 63 (6 self)
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In this paper we present an automatic method for calibrating a network of cameras from only silhouettes. This is particularly useful for shapefromsilhouette or visualhull systems, as no additional data is needed for calibration. The key novel contribution of this work is an algorithm to robustly compute the epipolar geometry from dynamic silhouettes. We use the fundamental matrices computed by this method to determine the projective reconstruction of the complete camera configuration. This is refined into a metric reconstruction using selfcalibration. We validate our approach by calibrating a four camera visualhull system from archive data where the dynamic object is a moving person. Once the calibration parameters have been computed, we use a visualhull algorithm to reconstruct the dynamic object from its silhouettes. 1
Towards urban 3d reconstruction from video
 in 3DPVT
, 2006
"... The paper introduces a data collection system and a processing pipeline for automatic georegistered 3D reconstruction of urban scenes from video. The system collects multiple video streams, as well as GPS and INS measurements in order to place the reconstructed models in georegistered coordinates. ..."
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Cited by 63 (7 self)
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The paper introduces a data collection system and a processing pipeline for automatic georegistered 3D reconstruction of urban scenes from video. The system collects multiple video streams, as well as GPS and INS measurements in order to place the reconstructed models in georegistered coordinates. Besides high quality in terms of both geometry and appearance, we aim at realtime performance. Even though our processing pipeline is currently far from being realtime, we select techniques and we design processing modules that can achieve fast performance on multiple CPUs and GPUs aiming at realtime performance in the near future. We present the main considerations in designing the system and the steps of the processing pipeline. We show results on real video sequences captured by our system. 1
Capturing and animating occluded cloth
 ACM Trans. on Graphics (Proc. of ACM SIGGRAPH
, 2007
"... Figure 1: We reconstruct a stationary sleeve using thousands of markers to estimate the geometry (texture added with bump mapping). We capture the shape of moving cloth using a custom set of color markers printed on the surface of the cloth. The output is a sequence of triangle meshes with static co ..."
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Cited by 63 (1 self)
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Figure 1: We reconstruct a stationary sleeve using thousands of markers to estimate the geometry (texture added with bump mapping). We capture the shape of moving cloth using a custom set of color markers printed on the surface of the cloth. The output is a sequence of triangle meshes with static connectivity and with detail at the scale of individual markers in both smooth and folded regions. We compute markers ’ coordinates in space using correspondence across multiple synchronized video cameras. Correspondence is determined from color information in small neighborhoods and refined using a novel strain pruning process. Final correspondence does not require neighborhood information. We use a novel data driven holefilling technique to fill occluded regions. Our results include several challenging examples: a wrinkled shirt sleeve, a dancing pair of pants, and a rag tossed onto a cup. Finally, we demonstrate that cloth capture is reusable by animating a pair of pants using human motion capture data. 1
Structure and Motion from Uncalibrated Catadioptric Views
 In Proc. CVPR
, 2001
"... In this paper we present a new algorithm for structure from motion from point correspondences in images taken from uncalibrated catadioptric cameras with parabolic mirrors. We assume that the unknown intrinsic parameters are three: the combined focal length of the mirror and lens and the intersectio ..."
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Cited by 56 (5 self)
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In this paper we present a new algorithm for structure from motion from point correspondences in images taken from uncalibrated catadioptric cameras with parabolic mirrors. We assume that the unknown intrinsic parameters are three: the combined focal length of the mirror and lens and the intersection of the optical axis with the image. We introduce a new representation for images of points and lines in catadioptric images which we call the circle space. This circle space includes imaginary circles, one of which is the image of the absolute conic. We formulate the epipolar constraint in this space and establish a new 4 &times; 4 catadioptric fundamental matrix. We show that the image of the absolute conic belongs to the kernel of this matrix. This enables us to prove that Euclidean reconstruction is feasible from two views with constant parameters and from three views with varying parameters. In both cases, it is one less than the number of views necessary with perspective cameras.
Globally optimal estimates for geometric reconstruction problems
 In ICCV
, 2005
"... We introduce a framework for computing statistically optimal estimates of geometric reconstruction problems. While traditional algorithms often suffer from either local minima or nonoptimality or a combination of both we pursue the goal of achieving global solutions of the statistically optimal c ..."
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Cited by 53 (15 self)
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We introduce a framework for computing statistically optimal estimates of geometric reconstruction problems. While traditional algorithms often suffer from either local minima or nonoptimality or a combination of both we pursue the goal of achieving global solutions of the statistically optimal costfunction. Our approach is based on a hierarchy of convex relaxations to solve nonconvex optimization problems with polynomials. These convex relaxations generate a monotone sequence of lower bounds and we show how one can detect whether the global optimum is attained at a given relaxation. The technique is applied to a number of classical vision problems: triangulation, camera pose, homography estimation and last, but not least, epipolar geometry estimation. Experimental validation on both synthetic and real data is provided. In practice, only a few relaxations are needed for attaining the global optimum. 1
Skeletal graphs for efficient structure from motion
"... We address the problem of efficient structure from motion for large, unordered, highly redundant, and irregularly sampled photo collections, such as those found on Internet photosharing sites. Our approach computes a small skeletal subset of images, reconstructs the skeletal set, and adds the remai ..."
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Cited by 53 (9 self)
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We address the problem of efficient structure from motion for large, unordered, highly redundant, and irregularly sampled photo collections, such as those found on Internet photosharing sites. Our approach computes a small skeletal subset of images, reconstructs the skeletal set, and adds the remaining images using pose estimation. Our technique drastically reduces the number of parameters that are considered, resulting in dramatic speedups, while provably approximating the covariance of the full set of parameters. To compute a skeletal image set, we first estimate the accuracy of twoframe reconstructions between pairs of overlapping images, then use a graph algorithm to select a subset of images that, when reconstructed, approximates the accuracy of the full set. A final bundle adjustment can then optionally be used to restore any loss of accuracy. 1.
SelfCalibration of a camera from video of a walking human
 In ICPR
, 2002
"... Analysis of human activity from a video camera is simplified by the knowledge of the camera’s intrinsic and extrinsic parameters. We describe a technique to estimate such parameters from image observations without requiring measurements of scene objects. We first develop a general technique for cali ..."
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Cited by 49 (2 self)
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Analysis of human activity from a video camera is simplified by the knowledge of the camera’s intrinsic and extrinsic parameters. We describe a technique to estimate such parameters from image observations without requiring measurements of scene objects. We first develop a general technique for calibration using vanishing points and vanishing line. We then describe a method for estimating the needed points and line by observing the motion of a human in the scene. Experimental results, including error estimates, are presented.
Towards a View Invariant Gait Recognition Algorithm
 PROCEEDINGS OF IEEE CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE
, 2003
"... Human gait is a spatiotemporal phenomenon and typifies the motion characteristics of an individual. The gait of a person is easily recognizable when extracted from a sideview of the person. Accordingly, gaitrecognition algorithms work best when presented with images where the person walks parallel ..."
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Cited by 49 (5 self)
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Human gait is a spatiotemporal phenomenon and typifies the motion characteristics of an individual. The gait of a person is easily recognizable when extracted from a sideview of the person. Accordingly, gaitrecognition algorithms work best when presented with images where the person walks parallel to the camera (i.e. the image plane). However, it is not realistic to expect that this assumption will be valid in most reallife scenarios. Hence it is important to develop methods whereby the sideview can be generated from any other arbitrary view in a simple, yet accurate, manner. That is the main theme of this paper. We show that if the person is far enough from the camera, it is possible to synthesize a side view (referred to as canonical view) from any other arbitrary view using a single camera. Two methods are proposed for doing this: i) by using the perspective projection model, and ii) by using the optical flow based structure from motion equations. A simple camera calibration scheme for this method is also proposed. Examples of synthesized views are presented. Preliminary testing with gait recognition algorithms gives encouraging results. A byproduct of this method is a simple algorithm for synthesizing novel views of a planar scene.