10330894
Reconstruction of sculpture from uncalibrated image profiles
Profiles of a sculpture provide rich information about its geometry, and can be used for model reconstruction under known camera motion. By exploiting correspondences induced by epipolar tangents on the profiles, a successful solution to motion estimation has been developed for the case of circular motion. Arbitrary general views can then be incorporated to refine the model built from circular motion.
15199591
Structure and motion from silhouettes
This paper addresses the problem of recovering structure and motion from silhouettes. Silhouettes are projections of contour generators which are viewpoint dependent, and hence do not readily provide point correspondences for exploitation in motion estimation. Previous works have exploited correspondences induced by epipolar tangencies, and a successful solution has been developed in the special case of circular motion (turnable sequences). However, the main drawbacks are (1) new views cannot be added easily at a later time, and (2) part of the structure will always remain invisible under circular motion. In this paper we overcome the above problems by incorporating arbitrary general views and estimating the camera poses using silhouettes alone. We present a complete and practical system which produces high quality 3D models from 2D uncalibrated silhouettes. The 3D models thus obtained can be refined incrementally by adding new arbitrary views and estimating their poses. Experimental results on various objects are presented, demonstrating the quality of the reconstructions.
12775677
Camera Pose Estimation and Reconstruction from Image Profiles under Circular Motion
This paper addresses the problem of motion estimation and reconstruction of 3D models from profiles of an object rotating on a turntable, obtained from a single camera. Its main contribution is the development of a practical and accurate technique for solving this problem from profiles alone, which is, for the first time, precise enough to allow the reconstruction of the object. No correspondence between points or lines are necessary, although the method proposed can be equally used when these features are available, without any further adaptation. Symmetry properties of the surface of revolution swept out by the rotating object are exploited to obtain the image of the rotation axis and the homography relating epipolar lines, in a robust and elegant way. These, together with geometric constraints for images of rotating objects, are then used to obtain first the image of the horizon, which is the projection of the plane that contains the camera centres, and then the epipoles, thus fully determining the epipolar geometry of the sequence of images. The estimation of the epipolar geometry by this sequential approach (image of rotation axis -- homography -- image of the horizon -- epipoles) avoids many of the problems usually found in other algorithms for motion recovery from profiles. In particular, the search for the epipoles, by far the most critical step, is carried out as a simple one-dimensional optimisation problem. The initialisation of the parameters is trivial and completely automatic for all stages of the algorithm. After the estimation of the epipolar geometry, the Euclidean motion is recovered using the fixed intrinsic parameters of the camera, obtained either from a calibration grid or from self-calibration techniques. Finally, the spinning object is reconstructed from its profiles, using the motion estimated in the previous stage. Results from real data are presented, demonstrating the efficiency and usefulness of the proposed methods.
12048594
Camera Calibration from Symmetry
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 is important for both motion estimation and metric reconstruction of 3D models. In this paper, a novel and simple calibration technique has been introduced which is based on 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 2 images of surface of revolution will provide enough information for determining the aspect ratio, focal length and principal point of a camera. An analytical error model is developed, providing variances and confidence intervals of the parameters estimated. The techniques presented in this paper have been implemented and tested with both synthetic and real data. Experiment results show that the camera calibration method presented here is both practical and accurate.
9524579
Epipolar geometry from profiles under circular motion
Addresses the problem of motion estimation from profiles (apparent contours) of an object rotating on a turntable in front of a single camera. A practical and accurate technique for solving this problem from profiles alone is developed. It is precise enough to reconstruct the shape of the object. No correspondences between points or lines are necessary. Symmetry of the surface of revolution swept out by the rotating object is exploited to obtain the image of the rotation axis and the homography relating epipolar lines in two views robustly and elegantly. These, together with geometric constraints for images of rotating objects, are used to obtain first the image of the horizon, which is the projection of the plane that contains the camera centers, and then the epipoles, thus fully determining the epipolar geometry of the image sequence. The estimation of this geometry by this sequential approach avoids many of the problems found in other algorithms. The search for the epipoles, by far the most critical step, is carried out as a simple 1D optimization. Parameter initialization is trivial and completely automatic at all stages. After the estimation of the epipolar geometry, the Euclidean motion is recovered using the fixed intrinsic parameters of the camera obtained either from a calibration grid or from self-calibration techniques. Finally, the spinning object is reconstructed from its profiles using the motion estimated in the previous stage. Results from real data are presented, demonstrating the efficiency and usefulness of the proposed methods.
18572162
Structure and motion estimation from apparent contours under circular motion
In this paper we address the problem of recovering structure and motion from the apparent contours of a smooth surface. Fixed image features under circular motion and their relationships with the intrinsic parameters of the camera are exploited to provide a simple parameterization of the fundamental matrix relating any pair of views in the sequence. Such a parameterization allows a trivial initialization of the motion parameters, which all bear physical meanings. It also greatly reduces the dimension of the search space for the optimization problem, which can now be solved using only 2 epipolar tangents. In contrast to previous methods, the motion estimation algorithm introduced here can cope with incomplete circular motion and more widely spaced images. Existing techniques for model reconstruction from apparent contours are then reviewed and compared. Experiment on real data has been carried out and the 3D model reconstructed from the estimated motion is presented.
13225873
Model reconstruction and pose acquisition using extended Lowe's method
Finding the pose and structure of an unknown object from an image sequence has many applications in graphics, virtual reality, and multimedia processing. In this paper, we address this problem by using a two-stage iterative method. Starting from an initial guess of the structure, the first stage estimates the pose of the object. The second stage uses the estimated pose information to refine the structure. This process is repeated until the difference between the observed data and data re-projected from the estimated model is minimized. This method is a variation of the classical bundle adjustment method, but is faster in execution and is simpler to implement. We used the Kanade-Lucas-Tomasi feature tracker for obtaining the image features. Synthetic and real data have been tested with good results.
466097
Merging artificial objects with marker-less video sequences based on the interacting multiple model method
Inserting synthetic objects into video sequences has gained much interest in recent years. Fast and robust vision-based algorithms are necessary to make such an application possible. Traditional pose tracking schemes using recursive structure from motion techniques adopt one Kalman filter and thus only favor a certain type of camera motion. We propose a robust simultaneous pose tracking and structure recovery algorithm using the interacting multiple model (IMM) to improve performance. In particular, a set of three extended Kalman filters (EKFs), each describing a frequently occurring camera motion in real situations (general, pure translation, pure rotation), is applied within the IMM framework to track the pose of a scene. Another set of EKFs,one filter for each model point, is used to refine the positions of the model features in the 3-D space. The filters for pose tracking and structure refinement are executed in an interleaved manner. The results are used for inserting virtual objects into the original video footage. The performance of the algorithm is demonstrated with both synthetic and real data. Comparisons with different approaches have been performed and show that our method is more efficient and accurate.
14708115
Distributed computing systems and checkpointing
This paper examines the performance of synchronous checkpointing in a distributed computing environment with and without load redistribution. Performance models are developed, and optimum checkpoint intervals are determined. The analysis extends earlier work by allowing for multiple nodes, state dependent checkpoint intervals, and a performance metric which is coupled with failure-free performance and the speedup functions associated with implementation of parallel algorithms. Expressions for the optimum checkpoint intervals for synchronous checkpointing with and without load redistribution are derived and the results are then used to determine when load redistribution is advantageous.<<ETX>>
45470054
A Type Driven Hardware Engine For Prolog Clause Retrieval Over A Large Knowledge Base
Whereas existing Prolog systerns are very effective at handling small knowledge bases, they are not very efficient at and often incapable of handling large sets of clauses. Large knowledge bases which may comprise millions of clauses and are shared by a number of users, may need to reside in secondary memory. In such cases exhaustive search is inordinately slow. Various approaches have been put forward for handling the problem, most of whichinvolve coupled systems (loosely or tightly coupled). A Prolog data/knowledge based system which provides an integrated solution to the problem is being developa An essential element in this system is the CLAuse Retrieval Engine, CLARE, which is a special purpose hardware engine designed to perform selective retrieval of data from disk in order to identify all potential clauses which will be required for full unification during a query. 'Me engine consists of two separate hardware components, which together form a two-stage filtering configuration. This paper concentrates on the second stage filter which is concerned with partial test unification.
62724310
3D model reconstruction by constrained bundle adjustment
The accuracy of the reconstruction of 3D objects using vision-based techniques depends ultimately on an optimization technique known as bundle adjustment. However, direct application of bundle adjustment fails to make full use of the constraints inherent in the objects' motion. Most of the scanner systems available today use a turntable to rotate an object so as to capture images of the object from different view points. For these systems, the motion of the object is constrained to rotate around a fixed axis. By incorporating this constraint into the traditional bundle adjustment method, we show that a more accurate reconstructed model can be obtained. This "constrained" bundle adjustment method must be useful in the design of low-cost, yet accurate, 3D scanners for use in manufacturing and entertainment industry.