12585646
Creating virtual walkthrough environment from vertical panoramic mosaic
In this paper, a novel algorithm for creating virtual indoor environments is described. First, a panoramic mosaic is generated from a series of photos taken with a camera rotates along a horizontal axis. Then, from the panoramic mosaic image, a nonfixed viewing point virtual walkthrough system can be created by defining manually the corners in the vertical panoramic mosaic. The side ratio of the virtual walkthrough system can be obtained from the panning angle subsequently. By applying the cylindrical projection technique, the texture for the sides of the virtual walkthrough environment can be projected in a more realistic way. Real images have been used to verify our proposed algorithm with satisfactory 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.
28364216
Dynamic Programming in the Recognition of Connected Handwritten Script
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.
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.
1805653
Domain-retargetable reverse engineering
A user programmable approach to reverse engineering is described. The approach uses a scripting language that enables users to write their own routines for these activities, making the system domain-retargetable. The environment supported by this programmable approach subsumes existing reverse engineering systems by being able to simulate facets of each one and provides a smooth transition from semi-automatic to automatic reverse engineering.<<ETX>>
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>>
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.
207141336
Hybrid Term Indexing for Weighted Boolean and Vector Space Models
Retrieval effectiveness depends on how terms are extracted and indexed. For Chinese text (and others like Japanese and Korean), there are no space to delimit words. Indexing using hybrid terms (i.e. words and bigrams) were able to achieve the best precision amongst homogenous terms at a lower storage cost than indexing with bigrams. However, this was tested with conjunctive queries. Here, we extended the weighted Boolean models using fuzzy and p-norm measures, as well as the vector space model using the cosine measure, for processing hybrid terms. Our evaluation shows that all IR models using hybrid terms achieve better average precision over those using words. Across different recall values, the weighted Boolean model using fuzzy measures with hybrid terms achieve consistently about 8% higher than those using words. The vector space model using the cosine measures with hybrid terms achieved the best improvement in the average recall and precision.
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.