13460900
Reconstruction of sculpture from its profiles with unknown camera positions
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 resulting from the circular motion. We describe a complete and practical system for producing a three-dimensional (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.
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.
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.
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.
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.
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
2993896
An Efficient Iterative Pose Estimation Algorithm
We propose a novel model-based algorithm which finds the 3D pose of an object from an image by breaking down the estimation process into two linear processing stages, namely the depth recovery and the pose calculation. The depth recovery stage determines the new positions of the model point set in 3D space whereas the pose calculation step is a least-square estimation of the transformation parameters between the point set formed from the previous stage and the model set. The estimates are iteratively refined until converged. The advantage of using our algorithm is that the computational cost is much reduced. We test our algorithm by applying it to both synthetic as well as real time head tracking problem with satisfactory results.
11469103
Panoramic video segmentation using color mixture models
Consider a color camera mounted at a fixed point and a target object to be tracked. We propose a method to replace the common "blue screen" technique in performing segmentation of the object. The target object image in the video sequence is separated from the background through a segmentation process employing the color mixture model techniques. The background information is recovered through a similarity search with the panorama of the original background . The foreground segment can then be encoded by traditional compression while the scene background is represented as a panorama. Finally, the foreground object combines with the corresponding panoramic segment or any desired image on-the-fly to reconstruct the video frame. Our system can be used in low bandwidth applications as well as special demonstration in which the demonstrator can appear/disappear at any time he/she wishes.
35278447
An Investigation on Transformation-based Error-driven Learning Algorithm for Chinese Noun Phrase Extraction
Noun phrases are commonly used for generating index terms for information retrieval systems. Therefore, we need an effective noun phrase extraction method. In this paper, we propose an approach to extract maximal noun phrases from Chinese text. Although previous studies have been proposed to extract noun phrases, most of them are only applicable to Western languages. To the best of our knowledge, very few has handled Chinese text. Many existing approaches for Western languages made use of statistical methods. However, due to the complicated structure of maximal Chinese noun phrase, pure statistical approaches are not effective. We attempt to improve the performance of a statistical method by integrating it with the transformation-based error-driven learning (TEL) technique. Our methodology includes two modules. The first module applies a statistical method to extract Chinese noun phrases. The performance of this approach, in terms of precision and recall, is investigated. The second module applies the TEL algorithm to further refine the output of the first module. The TEL algorithm automatically learns a set of transformation rules to fix the errors that are obtained through comparing the output of the first module with the correctly annotated corpus. The learned rules can be applied to sentences in any corpus one by one to correct the errors. The TEL algorithm is shown to be effective in improving the precision.
38414976
An industrial experience in reverse engineering
This paper describes a reverse engineering case studywith an industrial-scale software system. The steps followedin the study involved: establishing a more comprehensivedomain model for representing structural factsabout C/C++ software; adapting a robust C/C++ parserthat focuses on source code before the preprocessing stage;decomposing or clustering the extracted artifacts in variousways for different understanding needs; generating reportsto highlight anomalies in the system; and clarifyingknowledge about its conceptual architecture. Also summarizedare lessons learned from this experience.
12666551
Fused data-centric visualizations for software evolution environments
During software evolution, several different facets of the system need to be related to one another at multiple levels of abstraction. Current software evolution tools have limited capabilities for effectively visualizing and evolving multiple system facets in an integrated manner. Many tools provide methods for tracking and relating different levels of abstraction within a single facet. However, it is less well understood how to represent and understand relationships between and among different abstraction hierarchies, i.e. for inter-hierarchy relations. Often, these are represented and explored independently, making them difficult to relate to one another. As a result, engineers are likely to have difficulty understanding how the various facets of a system relate and interact. We describe preliminary results of a collaborative research project between industry and academia to enhance the inter-hierarchy visualization capabilities of an existing software evolution environment called "KLOCwork Suite". Specifically, we describe our efforts to add a "fused" visualization based on story board diagrams. This visualization integrates - or "fuses" - facets of architecture, behavior and data. We describe how these diagrams bridge currently isolated visualizations of system information, and argue how they can help drive architecture excavation tasks.