7574414
Camera Calibration from Surfaces of Revolution
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 is both practical and accurate.
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.
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.
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
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.
7779937
Fundamental Properties of the Core Matching Functions for Information Retrieval
Traditional benchmarking methods for information retrieval (IR) are based on experimental performance evaluation. Although the metrics precision and recall can measure the performance of a system, it cannot assess the functionality of the underlying model. Recently, a theory of “aboutness” has been studied and used for reasoning about functional of IR models. Latest research shows the functionality of an IR model is largely determined by its retrieval mechanism, i.e., the matching function; in particular, containment and overlapping (either with or without a threshold value) are core IR matching functions. The objective of this paper is to model the containment and overlapping matching functions within an aboutness-based framework, reason and analyze the inherent functionality of them from an abstract and theoretical viewpoint. Separate aboutness relations for containment, pureoverlapping (i.e. without threshold) and threshold-overlapping are defined, and the sets of properties supported by them are derived and analyzed respectively. These three relations can be used to explain the functionality supported by an IR system and their effects to its performance; and moreover, they provide the design guidelines for new IR systems.
33806006
On migrating a legacy application to the palm platform
Handheld computing devices such as personal digital assistants (PDAs) and the latest mobile phones are becoming widespread, so migrating desktop applications to these platforms is of great interest to developers. However, little information is available to guide the novice especially for the palm OS, the,most popular platform in the PDA and smartphone arena. This paper highlights the migration challenges involved and potential directions in easing this reengineering process. To explore the practical understanding and reengineering issues, a large legacy application was partially migrated to palm OS.
13402065
JRefleX: towards supporting small student software teams
The success of a software development project depends on the technical competency of the development team, the quality of the tools they use, and the project-management decisions they make during the software lifecycle. Instructors of software-engineering courses that involve small project teams are often overwhelmed with the task of monitoring the progress of multiple teams. Without adequate monitoring and advice on best practices, problems in the team's process or the developed product may go unnoticed until it is too late to be easily fixed. This paper introduces the JRefleX environment, with components built upon Eclipse, to support the education of small software teams.
2118584
Resolution Improvement from Stereo Images with 3D Pose Differences
Resolution improvement from several images is typically restricted to simple planar rotations and translations. In this paper, a super-resolution algorithm that allows 3D ego-motion of the camera system is proposed. By exploiting the trifocal tensor constraint of a stereo camera system, the intermediate step of scene structure recovery is effectively skipped. 3D motion is estimated recursively through an extended Kalman filter and used by a novel image warping procedure to perform resolution enhancement. Real image experiment with comparison to well known Irani-Peleg approach confirms the validity of the algorithm.
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