Learning-based dynamic coupling of discrete and continuous trackers

We present a data-driven dynamic coupling between discrete and continuous methods for tracking objects of high dofs, which overcomes the limitations of previous techniques. In our approach, two trackers work in parallel, and the coupling between them is based on the tracking error. We use a model-based continuous method to achieve accurate results and, in cases of failure, we re-initialize the model using our discrete tracker. This method maintains the accuracy of a more tightly coupled system, while increasing its efficiency. At any given frame, our discrete tracker uses the current and several previous frames to search into a database for the best matching solution. For improved robustness, object configuration sequences, rather than single configurations, are stored in the database. We apply our framework to the problem of 3D hand tracking from image sequences and the discrimination between fingerspelling and continuous signs in American Sign Language.     

景像匹配区中稳定景物的分割方法研究

研究了景像匹配区中稳定景物的分割方法———强度和法及分形常数法 ,成功地分割了匹配区中的稳定景物 ,为评价区配区景物稳定性提供了依据 .其中分形常数法是分形理论应用在图像分割领域的一个新尝试     

基于Level set方法的医学图像分割

本文引入了一种基于偏微分方程的曲线进化方法—Level set方法,通过与Fast marching方法的结合,可以实现运算速度的大大提高。同时引进了更有效的Kim提出的GMM(Group Marching Method)方法,减少了运算量,并给出了改进方法。最后,把该方法用于仿真图与医学图像分割中,获得了较好的效果。     

基于模糊度测度和改进遗传算法的图像分割

为了利用模糊集理论进行图像分割,本文提出了一种模糊度测度函数,它衡量了背景模糊集和某一个二值图像的相似性:模糊度越小,这种相似程度越大;并且对模糊度的计算只需要进行简单的比较运算和加法运算,便于硬件实现。本文利用遗传算法求取最佳阈值,针对遗传算法的某些不足之处.我们利用精英策略和模拟退火的思想,对其做了一些修正。实验结果表明:相对于Shannon熵方法和模糊熵方法,本文方法取得了较好的分割结果,并且具有较强的抗噪声能力。     

基于复合顺序形态变换的车牌边缘检测

边缘检测是图像分割的重要环节,边缘提取的好坏直接影响了整个图像处理的效果。数学形态学用具有一定形态结构的“结构元素”去度量图像的形态,以解决图像处理和分析问题。文章通过对多种边缘检测方法的分析比较,结合高速公路路口汽车图像噪声大的特点,提出了基于复合顺序形态变换的车牌边缘检测。该方法不但能有效地改善有噪图像边缘检测的效果,鲁棒性好,而且并行快速,便于硬件实现。     

基于二维直方图分析的二元子图微光图像增强处理

提出了基于二维直方图分析的二元子图微光图像增强处理算法，根据原始图像的二维直方图分布特征，依据相邻像素的相关性数据，将图像分割成二元子图像，对每个子图像分别进行直方图均衡增强处理，最后合成得到完整的处理图像，通过用信息容量等图像评价参数对实验结果进行分析，表明此算法克服了对整幅图像进行直方图均衡时难以把握局部细节的缺点，得到了具有较好视觉质量的处理后微光图像。     

Pedestrian detection and tracking in infrared imagery using shape and appearance

In this paper, we present an approach toward pedestrian detection and tracking from infrared imagery using joint shape and appearance cues. A layered representation is first introduced and a generalized expectation-maximization (EM) algorithm is developed to separate infrared images into background (still) and foreground (moving) layers regardless of camera panning. In the two-pass scheme of detecting pedestrians from the foreground layer: shape cue is first used to eliminate non-pedestrian moving objects and then appearance cue helps to locate the exact position of pedestrians. Templates with varying sizes are sequentially applied to detect pedestrians at multiple scales to accommodate different camera distances. To facilitate the task of pedestrian tracking, we formulate the problem of shot segmentation and present a graph matching-based tracking algorithm that jointly exploits the shape, appearance and distance information. Experimental results with both OSU Infrared Image Database and WVU Infrared Video Database are reported to demonstrate the accuracy and robustness of our algorithm.     

A Standard Model-Theoretic Approach to Operational Semantics of Recursive Programs

In this paper we try to introduce a new approach to operational semantics of recursive programsby using ideas in the“priority method”which is a fundamental tool in Recursion Theory.In lieu ofmodelling partial functions by introducing undefined values in a traditional approach,we shall define apriority derivation tree for every term,and by respecting the rule“attacking the subterm of thehighest priority first”we define transition relations,computation sequences etc.directly based on astandard interpretation which includes no undefined value in its domain.Finally,we prove that ournew approach generates the same operational semantics as the traditional one.It is also pointed outthat we can use our strategy to refute a claim of Loeckx and Sieber that the opperational semanticsof recursive programs cannot be built based on predicate logic.     

Class Based Contextual Logic for DOOD

Cntextual logic provides a mechanism to reason about modules.In this paper,this theory of modules if modules is extended to a context theory of classes where class is in the true spirit of object-oriented databases.The logic,referred to as CLOG,is class-based.CLOG supports class,object identity,multiple role of object, monotonic and non-monotonic inheritance of data and method,method factoring,views,derived and query classes.Views and derived classes are queries in themselves.Objects are pure data terms representing the ground instances of facts in the class.Object identity is a first class term in the logic.Inheritance is handled through delegation.     

What is a free name in a process algebra?

There are two popular approaches to specifying the semantics of process algebras: labelled transition semantics and reaction semantics. While the notion of free name is rather unproblematic for labelled transition semantics this is not so for reaction semantics in the presence of a structural congruence for unfolding recursive declarations.We show that the standard definition of free name is not preserved under the structural congruence. We then develop a fixed point approach to the set of free names and show that it is invariant under the structural congruence.