3D Motion Segmentation from Straight-Line Optical Flow
We present a closed form solution to the problem of segmenting multiple 3D motion models from straight-line optical flow. We introduce the multibody line optical flow constraint(MLOFC), a polynomial equation relating motion models and line parameters. We show that the motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences are also presented.

title: Camera Calibration from a Single Frame of Planar Pattern
abstract: A method to calibrate camera from a single frame of planar pattern is presented in this paper. For a camera model with four intrinsic parameters and visible lens distortion, the principal point and distortion coefficients are firstly determined through analysis of the distortion in an image. The distortion is then removed. Finally, the other intrinsic and extrinsic parameters of the camera are obtained through direct linear transform followed by bundle adjustment. Theoretically, the method makes it possible to analyze the calibration result at the level of a single frame. Practically, such a method provides a easy way to calibrate a camera used in industrial vision system on line and used in desktop vision system. Experimental results of both simulated data and real images validate the method.

title: Motion Segmentation by Multibody Trifocal Tensor Using Line Correspondence
abstract: We present a geometric approach to multibody motion segmentation from line correspondences. Given three perspective views containing multiple moving objects, we demonstrate that after applying a polynomial embedding to the line correspondences, they became related by the so-called multibody trilinear constrain and its associated multibody trifocal tensor. We show how to obtain the individual trifocal tensor from the second order derivatives of the multibody trilinear constraint. Given trifocal tensors, we obtain the clustering of the motions and correspondences. Experimental results on synthetic and real dynamic scenes are presented

title: Motion segmentation of multiple translating objects using line correspondences
abstract: We present an algebraic approach to multibody motion segmentation from line correspondences. Given three perspective views containing multiple linearly moving objects, we demonstrate that after applying a polynomial embedding to the line correspondences, they became related by the so-called multibody line constraint of translational motions. We show how to linearly estimate the multibody trifocal epipole from line-line-line correspondences. The individual trifocal epipoles are then obtained from the derivatives of the multibody line constraint (up to an unknown factor). Given normalized trifocal epipoles, we can use any special clustering technique to obtain the clustering of the motions and the correspondences. The limitations of the proposed algorithm are also discussed. Experimental results on synthetic and real dynamic scenes are presented.

title: A new calibration model of camera lens distortion
abstract: Lens distortion is one of the main factors affecting camera calibration. In this paper, a new model of camera lens distortion is presented, according to which lens distortion is governed by the coefficients of radial distortion and a transform from ideal image plane to real sensor array plane. The transform is determined by two angular parameters describing the pose of the real sensor array plane with respect to the ideal image plane and two linear parameters locating the real sensor array with respect to the optical axis. Experiments show that the new model has about the same correcting effect upon lens distortion as the conventional model including all the radial distortion, decentering distortion and prism distortion. Compared with the conventional model, the new model has fewer parameters to be calibrated and more explicit physical meaning.

title: A Hand-Eye Robotic Model for Total Knee Replacement Surgery
abstract: This paper presents a hand-eye robotic model for total knee replacement (TKR) surgery. Unlike existent robot assisted TKR surgery, the proposed model is a surgical robot that combines with a movable hand-eye navigation system, which would use the full potential of both computer-assisted systems. Without using CT images and landmark pins in the patient's bones, it can directly measure the mechanical axis with high precision. This system provides a new approach of the minimally invasive surgery. Experiment results show that the proposed model is promising in the future application.

title: Model Retrieval Based on Flattened Shape Comparison in 3D Databases
abstract: A method that flatten surface of 3D model is presented. It can flatten the surface of model into a 2D shape as well as automatically cut and partition. The method avoids global and local self-intersections and minimizes the total length of the introduced seams. Then, a 3D models retrieval methodology based on the shape comparison is proposed. By using the flattened surface, pole mapped version normalization and Fourier transform, the shape similarity comparison is performed. The method is effective in capturing characteristics of surface shape. Finally, the experiment results show that our method is better than other methods.

title: Simplifying the Reconstruction of 3D Models using Parameter Elimination
abstract: Reconstructing large models from images is a significant challenge for computer vision, computer graphics, and related fields. In this paper, we present an approach for simplifying the reconstruction process by mathematically eliminating external camera parameters. This results in less parameters to estimate and in an overall significantly more robust and accurate reconstruction. We reformulate the problem in such a manner as to be able to identify invariants, eliminate superfluous parameters, and measure the performance of our formulation under various conditions. We compare a two-step camera orientation-free method, where the majority of the points are reconstructed using a linear equation set, and a camera position-and- orientation free method, using a degree-two equation set. Both approaches use a full perspective camera and are applied to synthetic and real-world datasets.

title: Speechalator: Two-Way Speech-to-Speech Translation in Your Hand
abstract: This demonstration involves two-way automatic speech-to-speech translation on a consumer off-the-shelf PDA. This work was done as part of the DARPA-funded Babylon project, investigating better speech-to-speech translation systems for communication in the field. The development of the Speechalator software-based translation system required addressing a number of hard issues, including a new language for the team (Egyptian Arabic), close integration on a small device, computational efficiency on a limited platform, and scalable coverage for the domain.

title: An Automatic Voice Query System for Bank Based on Telephone Network
abstract: Automatic voice query system for bank by phone was a hi-tech product based on computer technology, electronic communication technology and speech synthesis technology. The hardware design of this system adopted modularization design scheme, which centered on SCM AT89C51, and controlled the phone transceiver chip MT8870 and voice chip ISD4004, realizing voice query for bank account by phone remote control. This paper mainly analyzed and designed several circuits such as ringing detection circuit, on-hook and off-hook control circuit, amplified-filter circuit, receiving circuit, voice circuit and the connection circuit between PC and SCM; it finally gave the realization process of the systempsilas software.

title: Semantic Information Extraction of Video Based on Ontology and Inference
abstract: In this paper, a new ontology-based composite concept detection method is proposed, which adopts Bayesian network to construct the ontology and uses the inference rules to perform the composite concept detection providing the concrete concepts in a phrase of video. Furthermore, the probability instead of binary value is gained through the inference pattern of Bayesian network, which can obtain more precise results. The main contribution of this paper is that semantic concept ontology is constructed using Bayesian network and the constructed ontology represents the hierarchical relationship between the concepts which can be used for inference. The method narrows the influence of "Semantic Gap" in some extent and achieves good performance in composite concept detection.