1578831
Pose estimation for augmented reality applications using genetic algorithm
This paper describes a genetic algorithm that tackles the pose-estimation problem in computer vision. Our genetic algorithm can find the rotation and translation of an object accurately when the three-dimensional structure of the object is given. In our implementation, each chromosome encodes both the pose and the indexes to the selected point features of the object. Instead of only searching for the pose as in the existing work, our algorithm, at the same time, searches for a set containing the most reliable feature points in the process. This mismatch filtering strategy successfully makes the algorithm more robust under the presence of point mismatches and outliers in the images. Our algorithm has been tested with both synthetic and real data with good results. The accuracy of the recovered pose is compared to the existing algorithms. Our approach outperformed the Lowe's method and the other two genetic algorithms under the presence of point mismatches and outliers. In addition, it has been used to estimate the pose of a real object. It is shown that the proposed method is applicable to augmented reality applications.
2219807
Computing Pose Sequences Directly from Videos
An innovative extended Kalman filter (EKF) algorithm for pose tracking has been proposed in this paper. It has the advantages of both structure and motion-based (SAM-based) and traditional model-based pose estimation algorithms. With no prior information about the scene, the pose sequence can be computed directly from images while the updating of the 3-D structure is not necessary. To achieve the goal, a constant velocity motion model is used as the dynamic system and the trifocal tensor point transfer function is applied to the measurement model of the filter. The resulting algorithm is stable, accurate and efficient. An empirical comparison with existing EKFs which deal with the same problem has been made and shows that our approach outperformed the others. The proposed method has been tested with various video sequences to demonstrate its performance in real situations.
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.
3120289
Recursive Recovery of Position and Orientation from Stereo Image Sequences without Three-Dimensional Structures
Traditional vision-based 3-D motion estimation algorithms for robots require given or calculated 3-D models while the motion is being tracked. We propose a high-speed extended-Kalman-filter-based approach that recovers position and orientation from stereo image sequences without prior knowledge as well as the procedure for the reconstruction of 3-D structures. Empowered by the use of the trifocal tensor, the computation step of 3-D models can be eliminated. The algorithm is thus more flexible and can be applied to a wide range of domains. The twist motion model is also adopted to parameterize the 3-D motion such that the motion representation in the proposed algorithm is robust and minimal. As the number of parameters to be estimated is reduced, our algorithm is more efficient, stable and accurate compared to traditional approaches. The proposed method has been verified using a real image sequence with ground truth.
14489674
Automatic lyrics alignment for Cantonese popular music
From lyrics-display on electronic music players and Karaoke videos to surtitles for live Chinese opera performance, one feature is common to all these everyday functionalities temporal: synchronization of the written text and its corresponding musical phrase. Our goal is to automate the process of lyrics alignment, a procedure which, to date, is still handled manually in the Cantonese popular song (Cantopop) industry. In our system, a vocal signal enhancement algorithm is developed to extract vocal signals from a CD recording in order to detect the onsets of the syllables sung and to determine the corresponding pitches. The proposed system is specifically designed for Cantonese, in which the contour of the musical melody and the tonal contour of the lyrics must match perfectly. With this prerequisite, we use a dynamic time warping algorithm to align the lyrics. The robustness of this approach is supported by experiment results. The system was evaluated with 70 twenty-second music segments and most samples have their lyrics aligned correctly.
33950497
An Effective Method for Chinese Grammar Rule Learning
A new method of Chinese grammar rules learning is put forward in this paper. The key point of this method is to use part-of-speech (POS), semantic and contextual information together in learning and expressing Chinese grammar rules. In this way, not only Context Free Grammar (CFG) rules can be learnt, but also the ambiguous structures in POS can be identified automatically. Furthermore, non-ambiguous semantic rules and forbidden rules can be produced from ambiguous rules by using semantic and contextual information. Experimental results demonstrate that the complexity of Chinese parsing is greatly reduced using the different rules learnt by our method.
3091024
On integrating visualization techniques for effective software exploration
This paper describes the SHriMP visualization technique for seamlessly exploring software structure and browsing source code, with a focus on effectively assisting hybrid program comprehension strategies. The technique integrates both pan+zoom and fisheye-view visualization approaches for exploring a nested graph view of software structure. The fisheye-view approach handles multiple focal points, which are necessary when examining several subsystems and their mutual interconnections. Source code is presented by embedding code fragments within the nodes of the nested graph. Finer connections among these fragments are represented by a network that is navigated using a hypertext link-following metaphor. SHriMP combines this hypertext metaphor with animated panning and zooming motions over the nested graph to provide continuous orientation and contextual cues for the user. The SHriMP tool is being evaluated in several user studies. Observations of users performing program understanding tasks with the tool are discussed.
42165633
On the business value and technical challenges of adopting Web services
This paper provides a balanced perspective of the business value and technical challenges of adopting Web services. Technology adoption is a continual challenge for both tool developers and enterprise users. Web services are a prime example of an emerging technology that is fraught with adoption issues. Part of the problem is separating marketing hype from business reality. Web services are network-accessible interfaces to application functionality. They are built using Internet technologies such as XML and standard protocols such as SOAP. The adoption issues related to Web services are complex and multifaceted. For example, determining whether this technology is a fundamental advance, rather than something old under a new name, requires technical depth, business acumen, and considerable historical knowledge of past developments. A sample problem from the health care industry is used to illustrate some of the adoption issues.
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.
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.