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.
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.
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.
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
53788593
A fast recursive 3D model reconstruction algorithm for multimedia applications
A recursive two-step method to recover structure and motion from image sequences based on Kalman filtering is described in this paper. The algorithm consists of two major steps. The first step is an extended Kalman filter for the estimation of the object's pose. The second step is a set of extended Kalman filters, one for each model point, for refining the positions of the model features in the 3D space. The initial guess is a planar model formed under the assumption of orthographic projection on the first image. These two steps alternate from frames to frames. The planar model converges to the final structure as the image sequence is scanned sequentially. The performance of the algorithm is demonstrated with both synthetic data and real world objects. Comparisons with different approaches have been performed and show that our method is more efficient.
690242
Improving Quality of Email Categorization with Tournament Methods
The tournament text classification methods are proposed in this article to perform the task of email categorization, in which the essence is to break down the multi-class categorization process into a set of binary classification tasks. We implement the methods of elimination and Round Robin tournament to classify emails within 15 folders. Substantial experiments are conducted to compare the effectiveness and robustness of the tournament methods against the n-way classification method and the voting method. The experimental results show that the tournament methods outperform the n-way method by 11.7% and the voting method by 4.1% regarding precision, and the Round Robin performs slightly better than the Elimination tournament on average.
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.
35087745
A Study on Word-Based and Integral-Bit Chinese Text Compression Algorithms
31921180
Fast elliptic scalar multiplication using new double-base chain and point halving
The fast implementation of elliptic curve cryptosystems relies on the efficient computation of scalar multiplication. Based on the double-base chain representation of scalar using powers of 2 and 3, we propose a new representation with powers of 1/2 and 3 instead. Thus the efficient point halving operation can be incorporated in the new double-base chain to achieve fast scalar multiplication. Experimental results show that our approach leads to a lower complexity which contributes to the efficient implementation of elliptic curve cryptosystems.
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.