Face tracking with automatic model construction

This paper describes an active model with a robust texture model built on-line. The model uses one camera and it is able to operate without active illumination. The texture model is defined by a series of clusters, which are built in a video sequence using previously encountered samples. This model is used to search for the corresponding element in the following frames. An on-line clustering method, named leaderP is described and evaluated on an application of face tracking. A 20-point shape model is used. This model is built offline, and a robust fitting function is used to restrict the position of the points. Our proposal is to serve as one of the stages in a driver monitoring system. To test it, a new set of sequences of drivers recorded outdoors and in a realistic simulator has been compiled. Experimental results for typical outdoor driving scenarios, with frequent head movement, turns and occlusions are presented. Our approach is tested and compared with the Simultaneous Modeling and Tracking (SMAT) [1], and the recently presented Stacked Trimmed Active Shape Model (STASM) [2], and shows better results than SMAT and similar fitting error levels to STASM, with much faster execution times and improved robustness.     

Robust tracking control design for uncertain robotic systems with persistent bounded disturbances

In this study, a robust nonlinear L_∞‐gain tracking control design for uncertain robotic systems is proposed under persistent bounded disturbances. The design objective is that the peak of the tracking error in time domain must be as small as possible under persistent bounded disturbances. Since the nonlinear L_∞ ‐gain optimal tracking control cannot be solved directly, the nonlinear L_∞ ‐gain optimal tracking problem is transformed into a nonlinear L_∞ ‐gain tracking problem by given a prescribed disturbance attenuation level for the L_∞ ‐gain tracking performance. To guarantee that the L_∞ ‐gain tracking performance can be achieved for the uncertain robotic systems, a sliding‐mode scheme is introduced to eliminate the effect of the parameter uncertainties. By virtue of the skew‐symmetric property of the robotic systems, sufficient conditions are developed for solving the robust L_∞ ‐gain tracking control problems in terms of an algebraic equation instead of a differential equation. The proposed method is simple and the algebraic equation can be solved analytically. Therefore, the proposed robust L_∞ ‐gain tracking control scheme is suitable for practical control design of uncertain robotic systems. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

基于改进免疫遗传算法的电网故障诊断研究

针对电网故障的特点,应用一种改进的免疫遗传算法对电网故障进行研究。该算法能够较好地解决传统遗传算法的不足。通过引入新的交叉和变异率,更多考虑了种群的全局特征,采用动态自适应方式提取疫苗,避免了传统遗传算法收敛速度较慢的缺点。改进的算法本着优胜劣汰的思想,删除适值较低的抗体群,取而代之的是随机生成的部分新抗体,保持种群的多样性。建立一个新的目标函数,通过对一个电网的分析,验证了方法的有效性。     

A probabilistic integrated object recognition and tracking framework

This paper describes a probabilistic integrated object recognition and tracking framework called PIORT, together with two specific methods derived from it, which are evaluated experimentally in several test video sequences. The first step in the proposed framework is a static recognition module that provides class probabilities for each pixel of the image from a set of local features. These probabilities are updated dynamically and supplied to a tracking decision module capable of handling full and partial occlusions. The two specific methods presented use RGB color features and differ in the classifier implemented: one is a Bayesian method based on maximum likelihood and the other one is based on a neural network. The experimental results obtained have shown that, on one hand, the neural net based approach performs similarly and sometimes better than the Bayesian approach when they are integrated within the tracking framework. And on the other hand, our PIORT methods have achieved better results when compared to other published tracking methods in video sequences taken with a moving camera and including full and partial occlusions of the tracked object.     

相似点区段负责制的改进区域生长法及其应用

区域生长法被广泛应用于对特定目标的选取,但其生长速度缓慢的特点又限制了其在某些领域的应用.为此,提出一种基于相似点区段负责制的像素点进出堆栈管理方法,有效的提高了区域生长的效率.在此基础上,结合链码法边界跟踪对生长过程中区域内部出现的孔洞实现区域补偿,建立了针对链状藻细胞分析统计的有效应用系统.     

R-M不稳定性数值模拟方法

通常,界面追踪方法都是由界面将计算区域分割为多个部分来分别处理,同时用求解黎曼问题来追踪全部波系的发展。然而在多维情况下,波系间相互作用的黎曼问题将非常复杂且目前尚处于分析阶段,故在实际应用中只能追踪界面本身。提出了一种新的界面追踪方法,该方法只追踪界面的发展而不再追踪波系,使计算量和复杂性大大减少并保持了原界面追踪方法精确捕捉界面的特点,数值结果令人满意。     

基于流场数值模拟的ADS靶件结构的设计优化

采用通用的计算流体力学（CFD）软件PHOENICS 3．3和BFC计算网格生产技术，对加速器驱动次临界系统（ADS）靶件的流场进行数值模拟计算。结果表明：束窗下方导流板起引导流体沿束窗表面流动的作用，消除了束窗两侧下方较大的旋涡，对于改善束窗附近流体的流动结构、提高束窗表面及散裂靶的换热，效果显著。     

逆指令流与指令队列预取反跟踪技术

介绍一种逆指令流的实现方法，同时把它与指令队列预取法结合在一起实现了反跟踪，使其成为一种综合性的威力较强的反动态跟踪技术     

Polarization Phase-Based Method For Material Classification In Computer Vision

A robust and accurate polarization phase-based technique for material classification is presented. The novelty of this technique is three-fold in (i) its theoretical development, (ii) application, and, (iii) experimental implementation. The concept of phase of polarization of a light wave is introduced to computer vision for discrimination between materials according to their intrinsic electrical conductivity, such as distinguishing conducting metals, and poorly conducting dielectrics. Previous work has used intensity, color and polarization component ratios. This new method is based on the physical principle that metals retard orthogonal components of light upon reflection while dielectrics do not. This method has significant complementary advantages with respect to existing techniques, is computationally efficient, and can be easily implemented with existing imaging technology. Experiments for real circuit board inspection, nonconductive and conductive glass, and, outdoor object recognition have been performed to demonstrate its accuracy and potential capabilities.     

互动式教学模式在实践中的运用

论述了互动式教学模式依据的理论基础、涵义以及在课堂实践中的具体实施，旨在唤起和培养学生参与课堂活动意识，创造一种轻松、和谐、互补的教学环境，从而提高学生的语言应用能力。