Results 1  10
of
49
ShapefromSilhouette Across Time  Part I: Theory and Algorithms
 International Journal of Computer Vision
, 2005
"... ShapeFromSilhouette (SFS) is a shape reconstruction method which constructs a 3D shape estimate of an object using silhouette images of the object. The output of a SFS algorithm is known as the Visual Hull (VH). Traditionally SFS is either performed on static objects, or separately at each time in ..."
Abstract

Cited by 107 (3 self)
 Add to MetaCart
(Show Context)
ShapeFromSilhouette (SFS) is a shape reconstruction method which constructs a 3D shape estimate of an object using silhouette images of the object. The output of a SFS algorithm is known as the Visual Hull (VH). Traditionally SFS is either performed on static objects, or separately at each time instant in the case of videos of moving objects. In this paper we develop a theory of performing SFS across time: estimating the shape of a dynamic object (with unknown motion) by combining all of the silhouette images of the object over time. We first introduce a one dimensional element called a Bounding Edge to represent the Visual Hull. We then show that aligning two Visual Hulls using just their silhouettes is in general ambiguous and derive the geometric constraints (in terms of Bounding Edges) that govern the alignment. To break the alignment ambiguity, we combine stereo information with silhouette information and derive a Temporal SFS algorithm which consists of two steps: (1) estimate the motion of the objects over time (Visual Hull Alignment) and (2) combine the silhouette information using the estimated motion (Visual Hull Refinement). The algorithm is first developed for rigid objects and then extended to articulated objects. In the Part II of this paper we apply our temporal SFS algorithm to two humanrelated applications: (1) the acquisition of detailed human kinematic models and (2) markerless motion tracking.
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 ..."
Abstract

Cited by 63 (6 self)
 Add to MetaCart
(Show Context)
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
Silhouette coherence for camera calibration under circular motion
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2007
"... Abstract—We present a new approach to camera calibration as a part of a complete and practical system to recover digital copies of sculpture from uncalibrated image sequences taken under turntable motion. In this paper, we introduce the concept of the silhouette coherence of a set of silhouettes gen ..."
Abstract

Cited by 40 (6 self)
 Add to MetaCart
(Show Context)
Abstract—We present a new approach to camera calibration as a part of a complete and practical system to recover digital copies of sculpture from uncalibrated image sequences taken under turntable motion. In this paper, we introduce the concept of the silhouette coherence of a set of silhouettes generated by a 3D object. We show how the maximization of the silhouette coherence can be exploited to recover the camera poses and focal length. Silhouette coherence can be considered as a generalization of the wellknown epipolar tangency constraint for calculating motion from silhouettes or outlines alone. Further, silhouette coherence exploits all the geometric information encoded in the silhouette (not just at epipolar tangency points) and can be used in many practical situations where point correspondences or outer epipolar tangents are unavailable. We present an algorithm for exploiting silhouette coherence to efficiently and reliably estimate camera motion. We use this algorithm to reconstruct very high quality 3D models from uncalibrated circular motion sequences, even when epipolar tangency points are not available or the silhouettes are truncated. The algorithm has been integrated into a practical system and has been tested on more than 50 uncalibrated sequences to produce high quality photorealistic models. Three illustrative examples are included in this paper. The algorithm is also evaluated quantitatively by comparing it to a stateoftheart system that exploits only epipolar tangents. Index Terms—Silhouette coherence, epipolar tangency, imagebased visual hull, focal length estimation, circular motion, 3D modeling. 1
Metric 3D Reconstruction and Texture Acquisition of Surfaces of Revolution from a Single Uncalibrated View
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2005
"... Image analysis and computer vision can be effectively employed to recover the threedimensional structure of imaged objects, together with their surface properties. In this paper, we address the problem of metric reconstruction and texture acquisition from a single uncalibrated view of a surface of ..."
Abstract

Cited by 37 (11 self)
 Add to MetaCart
Image analysis and computer vision can be effectively employed to recover the threedimensional structure of imaged objects, together with their surface properties. In this paper, we address the problem of metric reconstruction and texture acquisition from a single uncalibrated view of a surface of revolution (SOR). Geometric constraints induced in the image by the symmetry properties of the SOR structure are exploited to perform selfcalibration of a natural camera, 3D metric reconstruction and texture acquisition. By exploiting the analogy with the geometry of single axis motion, we demonstrate that the imaged apparent contour and the visible segments of two imaged cross sections in a single SOR view provide enough information for these tasks. Original contributions of the paper are: single view selfcalibration and reconstruction based on planar rectification, previously developed for planar surfaces, has been extended to deal also with the SOR class of curved surfaces; selfcalibration is obtained by estimating both camera focal length (1 parameter) and principal point (2 parameters) from three independent linear constraints for the SOR fixed entities; the invariantbased description of the SOR scaling function has been extended from affine to perspective projection. The solution proposed exploits both the geometric and topological properties of the transformation that relates the apparent contour to the SOR scaling function. Therefore, with this method a metric localization of the SOR occluded parts can be made, so as to cope with them correctly. For the reconstruction of textured SORs, texture acquisition is performed without requiring the estimation of external camera calibration parameters, but only using internal camera parameters obtained from...
Camera Calibration from Surfaces of Revolution
 IEEE TRANS. ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2002
"... This paper addresses the problem of calibrating a pinhole camera from images of a surface of revolution. Camera calibration is the process of determining the intrinsic or internal parameters (i.e., aspect ratio, focal length and principal point) of a camera, and it is important for both motion estim ..."
Abstract

Cited by 31 (6 self)
 Add to MetaCart
(Show Context)
This paper addresses the problem of calibrating a pinhole camera from images of a surface of revolution. Camera calibration is the process of determining the intrinsic or internal parameters (i.e., aspect ratio, focal length and principal point) of a camera, and it is important for both motion estimation and metric reconstruction of 3D models. In this paper a novel and simple calibration technique is introduced, which is based on exploiting the symmetry of images of surfaces of revolution. Traditional techniques for camera calibration involve taking images of some precisely machined calibration pattern (such as a calibration grid). The use of surfaces of revolution, which are commonly found in daily life (e.g., bowls and vases), makes the process easier as a result of the reduced cost and increased accessibility of the calibration objects. In this paper, it is shown that two images of a surface of revolution will provide enough information for determining the aspect ratio, focal length and principal point of a camera with fixed intrinsic parameters. The algorithms presented in this paper have been implemented and tested with both synthetic and real data. Experimental results show that the camera calibration method presented here is both practical and accurate.
Reconstruction of sculpture from its profiles with unknown camera positions
 IEEE TRANSACTIONS ON IMAGE PROCESSING
, 2004
"... Profiles of a sculpture provide rich information about its geometry, and can be used for shape recovery under known camera motion. By exploiting correspondences induced by epipolar tangents on the profiles, a successful solution to motion estimation from profiles has been developed in the special ..."
Abstract

Cited by 28 (2 self)
 Add to MetaCart
(Show Context)
Profiles of a sculpture provide rich information about its geometry, and can be used for shape recovery under known camera motion. By exploiting correspondences induced by epipolar tangents on the profiles, a successful solution to motion estimation from profiles has been developed in the special case of circular motion. The main drawbacks of using circular motion alone, namely the difficulty in adding new views and part of the object always being invisible, can be overcome by incorporating arbitrary general views of the object and registering its new profiles with the set of profiles resulted from the circular motion. In this paper, we describe a complete and practical system for producing a 3D model from uncalibrated images of an arbitrary object using its profiles alone. Experimental results on various objects are presented, demonstrating the quality of the reconstructions using the estimated motion.
On using silhouettes for camera calibration
 In Proceedings of the 7th Asian Conference on Computer Vision (ACCV
, 2006
"... Abstract. This paper addresses the problem of camera calibration using object silhouettes in image sequences. It is known that silhouettes encode information on camera parameters by the fact that their associated viewing cones should present a common intersection in space. In this paper, we investig ..."
Abstract

Cited by 19 (5 self)
 Add to MetaCart
(Show Context)
Abstract. This paper addresses the problem of camera calibration using object silhouettes in image sequences. It is known that silhouettes encode information on camera parameters by the fact that their associated viewing cones should present a common intersection in space. In this paper, we investigate how to evaluate calibration parameters given a set of silhouettes, and how to optimize such parameters with silhouette cues only. The objective is to provide online tools for silhouette based modeling applications in multiple camera environments. Our contributions with respect to existing works in this field is first to establish the exact constraint that camera parameters should satisfy with respect to silhouettes, and second to derive from this constraint new practical criteria to evaluate and to optimize camera parameters. Results on both synthetic and real data illustrate the interest of the proposed framework. 1
Reconstruction of Surfaces of Revolution from Single Uncalibrated Views
 Proc. British Machine Vision Conference 2002
, 2002
"... This paper addresses the problem of recovering the 3D shape of a surface of revolution from a single uncalibrated perspective view. The algorithm introduced here makes use of the invariant properties of a surface of revolution and its silhouette to locate the image of the revolution axis, and to ..."
Abstract

Cited by 15 (2 self)
 Add to MetaCart
(Show Context)
This paper addresses the problem of recovering the 3D shape of a surface of revolution from a single uncalibrated perspective view. The algorithm introduced here makes use of the invariant properties of a surface of revolution and its silhouette to locate the image of the revolution axis, and to calibrate the focal length of the camera. The image is then normalized and rectified such that the resulting silhouette exhibits bilateral symmetry. Such a rectification leads to a simpler differential analysis of the silhouette, and yields a simple equation for depth recovery. Ambiguities in the reconstruction are analyzed and experimental results on real images are presented, which demonstrate the quality of the reconstruction.
Reconstruction in the round using photometric normals and silhouettes
 IN: PROC. IEEE CONF. ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR
, 2006
"... This paper addresses the problem of obtaining complete, detailed reconstructions of shiny textureless objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under varying illumination conditions. In contrast with previous photometric stereo techniques, ours ..."
Abstract

Cited by 15 (4 self)
 Add to MetaCart
(Show Context)
This paper addresses the problem of obtaining complete, detailed reconstructions of shiny textureless objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under varying illumination conditions. In contrast with previous photometric stereo techniques, ours is not limited to a single viewpoint and produces accurate reconstructions in full 3D. A number of images of the object are obtained from multiple viewpoints, under varying lighting conditions. Starting from the silhouettes, the algorithm recovers camera motion and constructs the object’s visual hull. This is then used to recover the illumination and initialise a multiview photometric stereo scheme to obtain a closed surface reconstruction. The contributions of the paper are twofold: Firstly we describe a robust technique to estimate light directions and intensities and secondly, we introduce a novel formulation of photometric stereo which combines multiple viewpoints and hence allows closed surface reconstructions. The algorithm has been implemented as a practical model acquisition system. Here, a quantitative evaluation of the algorithm on synthetic data is presented together with a complete reconstruction of a challenging real object.
Circular motion geometry using minimal data
 IEEE Trans. Pattern Analysis and Machine Intelligence
, 2004
"... Circular motion or single axis motion is widely used in computer vision and graphics for 3D model acquisition. This paper describes a new and simple method for recovering the geometry of uncalibrated circular motion from a minimal set of only two points in four images. This problem has been previou ..."
Abstract

Cited by 13 (0 self)
 Add to MetaCart
(Show Context)
Circular motion or single axis motion is widely used in computer vision and graphics for 3D model acquisition. This paper describes a new and simple method for recovering the geometry of uncalibrated circular motion from a minimal set of only two points in four images. This problem has been previously solved using nonminimal data either by computing the fundamental matrix and trifocal tensor in three images, or by fitting conics to tracked points in five or more images. It is first established that two sets of tracked points in different images under circular motion for two distinct space points are related by a homography. Then, we compute a plane homography from a minimal two points in four images. After that, we show that the unique pair of complex conjugate eigenvectors of this homography are the image of the circular points of the parallel planes of the circular motion. Subsequently, all other motion and structure parameters are computed from this homography in a straighforward manner. The experiments on real image sequences demonstrate the simplicity, accuracy and robustness of the new method. Key words: structure from motion, minimal data, turntable, circular motion, vision geometry, single axis motion. 1 1