8164588
Reconstruction and Motion Estimation from Apparent Contours under Circular Motion
In thispaperweaddresstheproblemof recoveringstructureandmotionfrom thecontoursof a smooth-curvedsurface.A novel andsimplertechniquefor computingthestructureof anobjectfrom its profilesis introduced.Experimentswith real datashow encouragingresults,which are comparableto thoseobtainedfrom muchmore sophisticatedtechniques.Furthermore,a new methodfor motion estimationfrom sequencesof profilesis proposed. Preliminaryresultsdemonstratethefeasibilityof thealgorithm.
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.
14026170
Camera Calibration from Images of Spheres
This paper introduces a novel approach for solving the problem of camera calibration from spheres. By exploiting the relationship between the dual images of spheres and the dual image of the absolute conic (IAC), it is shown that the common pole and polar with regard to the conic images of two spheres are also the pole and polar with regard to the IAC. This provides two constraints for estimating the IAC and, hence, allows a camera to be calibrated from an image of at least three spheres. Experimental results show the feasibility of the proposed approach
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.
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.
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.
1770470
Pose estimation using four corresponding points
Abstract In this paper, a novel model-based pose estimation system is developed. In this system, correspondences between four points on a rigid solid object and four points in an image are used to estimate the new position and orientation of that rigid object under full perspective projection. Synthetic and real data have been used to verify our method.
6330846
Component-based software engineering: technologies, development frameworks, and quality assurance schemes
Component-based software development approach is based on the idea to develop software systems by selecting appropriate off-the-shelf components and then to assemble them with a well-defined software architecture. Because the new software development paradigm is very different from the traditional approach, quality assurance (QA) for component-based software development is a new topic in the software engineering community. In this paper, we survey current component-based software technologies, describe their advantages and disadvantages, and discuss the features they inherit. We also address QA issues for component-based software. As a major contribution, we propose a QA model for component-based software which covers component requirement analysis, component development, component certification, component customization, and system architecture design, integration, testing and maintenance.
33091738
SHAPES: A Novel Approach for Learning Search Heuristics in Under-Constrained Optimization Problems
Although much research in machine learning has been carried out on acquiring knowledge for problem-solving in many problem domains, little effort has been focused on learning search-control knowledge for solving optimization problems. This paper reports on the development of SHAPES, a system that learns heuristic search guidance for solving optimization problems in intractable, under-constrained domains based on the Explanation-Based Learning (EBL) framework. The system embodies two new and novel approaches to machine learning. First, it makes use of explanations of varying levels of approximation as a mean for verifying heuristic-based decisions, allowing heuristic estimates to be revised and corrected during problem-solving. The provision of such a revision mechanism is particularly important when working in intractable and under-constrained domains, where heuristics tend to be highly over-generalized, and hence at times will give rise to incorrect results. Second, it employs a new linear and quadratic programming-based weight-assignment algorithm formulated to direct search toward optimal solutions under best-first search. The algorithm offers a direct method for assigning rule strengths and, in so doing, avoids the need to address the credit-assignment problem faced by other iterative weight-adjustment methods.
35666520
Automatic Lyrics Alignment on Popular Music
17549193
Accurate 3-D Motion Tracking with an Application to Super-Resolution
Many of the existing image processing applications, in particular the construction of super-resolution videos, require an accurate high-speed motion tracking algorithm. This paper proposes an efficient recursive approach that recovers 3D motion from a stereo image sequence with high precision based on the trifocal tensor. In the computation process, neither the 3D structure of the scene nor its reconstruction is necessary. The validity of the proposed algorithm is demonstrated by applying it to upgrade the resolution of real stereo images. Empirical comparisons show that our novel approach outperformed traditional work in terms of both the accuracy of motion estimation and the quality of super-resolved images