基于似然比测试的语音激活检测算法

针对低信噪比和噪声变化情况下语音激活检测算法性能下降的问题,提出一种新的参数更新和取值算法。该算法采用Laplacian-Gaussian混合模型对带噪语音频谱的概率分布进行建模,模型参数从带噪语音中估计得到,噪声功率参数通过跟踪语音的音节间隙进行平滑。实验结果表明,该算法在-5dB信噪比情况下,可以达到95％以上的检测率,具有优越的跟踪性能。     

冷床区钢坯自动跟踪系统关键技术的研发

安钢中板厂的炉号跟踪系统中,冷金属检测器CMD用来检测冷床区钢坯的运动,但是CMD只能检测出辊道上是否有钢坯经过,而不能判断钢坯在冷床区具体上到哪个冷床,因此,目前冷床部分的钢坯跟踪是靠人工手动完成的.针对该问题,提出一种新的运用数字图像处理技术完成冷床区钢坯自动跟踪的方法.该方法利用运动目标检测方法检测出辊道上有钢坯运动,然后经过最佳阈值分割、改进的区域生长算法、质心标记、数据库程序等步骤完成钢坯运动轨迹的标记,实现自动跟踪.     

Sliding mode control for multi-agent systems under a time-varying topology

This paper addresses the tracking problem of a class of multi-agent systems under uncertain communication environments which has been modelled by a finite number of constant Laplacian matrices together with their corresponding scheduling functions. Sliding mode control method is applied to solve this nonlinear tracking problem under a time-varying topology. The controller of each tracking agent has been designed by using only its own and neighbours’ information. Sufficient conditions for the existence of a sliding mode control tracking strategy have been provided by the solvability of linear matrix inequalities. At the end of this work, numerical simulations are employed to demonstrate the effectiveness of the proposed sliding mode control tracking strategy.     

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.     

用于半自动视频对象提取的自适应网格图像分割

随着MPEG－4标准的发展和基于内容的视频处理研究,视频对象平面（VOP）的有效产生成为一个关键问题。本文提出一种基于区域的自适应网格彩色图像分割方法,可用于获得半自动视频对象跟踪和提取所需的初始VOP。该方法利用CIE L＊a*b＊色彩空间的特征量,对视频序列的第一帧进行三角形网格的分裂与合并。对MPEG－4标准测试序列的分割实验取得了较好的结果。     

智能信息平台Jasmine ii研究及应用

介绍新一代Internet智能信息平台Jasmine ii的结构和特点,包括Jasmine ii的对象模型、访问技术,同时介绍了在该对象平台上开发成功的电子商务套装应用软件E－Mart Suite for Jasmine。最后,比较和分析了该软件的特点和优势。     

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     

Response to ‘Comments on: A cohesion measure for object‐oriented classes’

Indicating that CBMC does not satisfy the monotonic property in terms of the number of interactions, Xu and Zhou proposed an augmented definition of CBMC by adopting cut set instead of glue methods. The augmented CBMC clearly satisfies the monotonic property. However, CBMC is designed to overcome the problem with respect to the number of interactions and, therefore, focuses on the interaction pattern, especially, member connectivity. Consequently, it does not make sense to mention the monotonic property of CBMC with respect to interaction number. Moreover, the notion of glue methods allows several interpretations on the design quality of a class. However, that meaningful interpretation is not possible for the augmented definition due to the removal of the notion of glue methods. Copyright © 2001 John Wiley & Sons, Ltd.     

试论卓越会计人才培养模式的构建

全球经济一体化和会计准则国际趋同,客观上要求培养具有国际视野的卓越会计管理人才.在阐述卓越会计人才培养内涵的基础上,探析了卓越会计人才培养目标定位,明确了卓越会计人才培养的基本理念,提出了构建卓越会计人才培养模式的实现途径.     

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.