基于结构分析的手势识别

该文从分割和表示(建模)两方面着手,提出了一种新颖的手势分割和整体及局部手势特征提取算法.用模糊集合来描述视频流中空域和时域上的背景、颜色、运动等信息,通过对它们执行模糊运算,分割出人手;使用结构分析的方法来表示手势,根据人手不同部分在几何尺寸上的变化,从低到高逐次分析图像金字塔中各种分辨率的图像,以获取手势的整体和局部结构特征;将人手划分成手掌和手指几个部分,使用手掌和各手指的中心点的坐标和从手掌中心到所有手指的中心的方向(作为手势方向)来表示一个2D手势.实验结果证明,该文算法具有很好的鲁棒性,对手势分割中间结果的精确性要求不高,因此能适应环境的变化.

research on user-centered design and recognition pen gestures

Pen-based user interface has become a hot research field in recent years. Pen gesture plays an important role in Pen-based user interfaces. But it’s difficult for UI designers to design, and for users to learn and use. In this purpose, we performed a research on user-centered design and recognition pen gestures. We performed a survey of 100 pen gestures in twelve famous pen-bases systems to find problems of pen gestures currently used. And we conducted a questionnaire to evaluate the matching degree between commands and pen gestures to discover the characteristics that a good pen gestures should have. Then cognition theories were applied to analyze the advantages of those characteristics in helping improving the learnability of pen gestures. From these, we analyzed the pen gesture recognition effect and presented some improvements on features selection in recognition algorithm of pen gestures. Finally we used a couple of psychology experiments to evaluate twelve pen gestures designed based on the research. It shows those gestures is better for user to learn and use. Research results of this paper can be used for designer as a primary principle to design pen gestures in pen-based systems.

一种面向实时交互的变形手势跟踪方法

变形手势跟踪是基于视觉的人机交互研究中的一项重要内容.单摄像头条件下,提出一种新颖的变形手势实时跟踪方法.利用一组2D手势模型替代高维度的3D手模型.首先利用贝叶斯分类器对静态手势进行识别,然后对图像进行手指和指尖定位,通过将图像特征与识别结果进行匹配,实现了跟踪过程的自动初始化.提出将K-means聚类算法与粒子滤波相结合,用于解决多手指跟踪问题中手指互相干扰的问题.跟踪过程中进行跟踪状态检测,实现了自动恢复跟踪及手势模型更新.实验结果表明,该方法可以实现对变形手势快速、准确的连续跟踪,能够满足基于视觉的实时人机交互的要求.

一种肤色干扰下的变形手势跟踪方法

介绍了一种基于单目视觉的肤色干扰下的变形手势跟踪方法.根据跟踪过程中所用到的基本手势特征,提出了一种基于PGH(成对几何直方图)的静态手势识别方法.为了解决跟踪过程中的肤色干扰问题,实现了基于Kalman滤波器的手势预测跟踪.为了解决跟踪过程中的初始化问题,提出了一种基于层次结构的跟踪初始化解决方案.实验结果表明,该方法能够在肤色干扰的情况下有效地对变形手势进行跟踪,并能够满足基于视觉的实时人机交互的要求.

基于手势的视觉用户界面研究

随着人机交互技术的发展，各种新的交互手段不断涌现，使人机交互朝着更加自然、高效和智能化的方向前进。基于手势的视觉用户界面是post-WIMP时代的一种重要的界面形式，与传统的WIMP交互方式相比视觉手势交互能够使用户摆脱鼠标键盘的束缚而采用一种更加自然、无约束的交互方式，从而提供给用户更大的交互空间、更多的交互自由度和更逼真的交互体验，具有较高的应用价值和良好的应用前景，因此被国内外越来越多的研究者所关注，迅速成为了人机交互领域一个热门的研究方向，并被广泛应用于虚拟/增强现实、普适计算、智能空间以及基于计算机的互动游戏等多个领域。 视觉交互是自然人机交互的核心和热点研究内容之一，视觉交互可以通过手势、目光、头部运动或者面部表情等多种方式进行。其中，手势是人类进行视觉交互的主要手段，手势所能表达的语义信息十分丰富。在人机交互中使用视觉手势完成交互任务不仅自然、直观和方便，而且从计算机的角度出发来看系统实现起来也较为容易。因此，基于手势的视觉用户界面得到了广泛的关注并取得了许多研究成果。从目前的研究现状来看，在基于手势的视觉用户界面研究中，仍然存在着以下的问题： （1）传统的WIMP界面模型已经不适合描述视觉手势界面这种post-WIMP界面的特点，需要对传统的用户界面模型加以扩展，构造适于描述视觉交互特征的界面模型帮助用户清晰、准确地分析和表达界面功能及其变化，描述出用户与系统的交互过程，指导软件系统的设计和实现； （2）具体的交互设计过程中还存在着许多关键技术没有解决好，例如手势的正确理解问题、算法的鲁棒性问题以及手势的可扩展性问题等； （3）传统视觉工具箱复杂难用的问题。需要降低开发难度，开发出便捷、易用、可扩展的软件界面开发工具及相应的开发方法，支持领域内非专家用户快速开发出视觉手势原型系统。 本文正是从以上问题出发，围绕着视觉手势界面交互技术，从理论、方法与应用等几个方面展开了深入的研究。首先论述了用户界面的发展历程，继而对视觉界面研究现状进行了综述。在充分研究和对比国内外相关研究成果的基础上提出了一种基于手势的视觉用户界面模型UIDT。接下来针对视觉手势交互中存在的难题，以认知心理学为理论依据提出了一种可扩展的手势交互状态转移模型，并在此基础上构建了视觉手势处理框架。随后对该框架中的关键技术进行了针对性的研究。针对非专家用户在构建具有个性化视觉手势界面过程中所遇到的问题，设计开发了一个支持视觉手势交互的开发工具IEToolkit并给出了一套基于该工具的通用的软件开发方法。最后，将上述成果应用于互动娱乐领域，取得了满意的效果。 本文的创新点主要表现在以下几个方面： 1. 提出了一种基于手势的视觉用户界面模型UIDT 在充分分析视觉交互特征的基础上，以传统的用户界面模型为基础提出了一种基于手势交互的视觉界面模型UIDT。该模型从用户模型、任务模型、设备模型和交互模型等几个方面对视觉手势交互进行了深入分析和描述，给出了各个模型的形式化定义，介绍了模型的各个组成模块以及它们之间的相互关系，讨论了视觉手势界面设计中应该遵循的设计规范。评估结果表明，该模型具有较强的通用性，有助于设计者对VBI的任务、用户、设备以及交互的不同层次进行抽象描述，使用户界面满足可用性要求，提高界面设计和原型开发的效率。 2. 提出了一个可扩展的视觉手势交互模型及一种新的视觉手势识别处理框架，围绕着该框架提出了一种新的视觉手势跟踪和识别方法 首先，提出了一个可扩展的视觉手势交互模型。根据认知心理学原理将视觉手势交互处理过程细分为选择性处理、分配性处理和集中处理三个不同的阶段，有效解决了Midas Touch问题；基于该模型提出了一个视觉手势识别框架，并结合认知心理学从手势检测、跟踪和识别三个方面对该框架的各个组成模块的关键技术进行了阐述。其中手势检测模块和识别管理模块能够辅助系统在复杂的背景中滤除掉不相关信息而选择性地搜索人手并根据上下文信息对手势识别任务重定向，从而避免了系统时刻都处于激活状态并对所有的手势动作都进行识别分析，有效解决了Midas Touch问题；为了提高系统的性能，提出了一种鲁棒的面向实时交互的变形手势跟踪方法和基于小样本学习的模板匹配方法用于动态手势识别。评估结果表明，上述技术有效地提高了系统的实时性、准确性和鲁棒性。 3. 设计开发了一个支持快速原型开发的视觉手势工具箱系统 针对目前大多数视觉手势工具箱复杂难用的问题，设计开发了一个简单、易用、可扩展的手势工具箱系统IEToolkit，实现了本文所述的各种关键交互技术。它包含了构造一个基于视觉手势的交互系统所需要的方方面面，从事件模型、交互模型、数据流模型等几个方面对工具箱的组成结构进行了描述，并给出了一个基于IEToolkit的通用的软件系统开发流程，开发人员可以将更多的精力集中在具体的高层逻辑语义处理上，而不需要过多考虑底层的技术细节与支撑结构。应用实例及评估结果表明IEToolkit能够降低开发门槛，较好地支持基于视觉手势交互的应用系统的快速构造，具有较高的应用价值。 4. 基于上述研究成果设计开发了一系列典型的视觉手势交互系统 将上述理论模型与具体的交互技术进行有效结合，在视觉手势开发工具平台基础上开发了一系列典型的互动娱乐系统，在实践中对本文的研究成果进行了有效性验证。

structuring and manipulating hand-drawn concept maps

Concept maps are an important tool to knowledge organization,representation, and sharing. Most current concept map tools do not provide full support for hand-drawn concept map creation and manipulation, largely due to the lack of methods to recognize hand-drawn concept maps. This paper proposes a structure recognition method. Our algorithm can extract node blocks and link blocks of a hand-drawn concept map by combining dynamic programming and graph partitioning and then build a concept-map structure by relating extracted nodes and links. We also introduce structure-based intelligent manipulation technique of hand-drawn concept maps. Evaluation shows that our method has high structure recognition accuracy in real time, and the intelligent manipulation technique is efficient and effective.

On the Gas-Liquid Two-Phase Flow Regimes and their Recognition Methods

气液两相流体系是一个复杂的多变量随机过程体系,流型的定义、流型过渡准则和判别方法等方面的研究是多相流学科目前研究的重点内容。本文就与气液两相流流型及其判别有关的研究状况进行了回顾和评述,力图反映近年来气液两相流流型及其判别问题研究的状态和趋势。

Pattern Recognition With Weighted Complex Networks

In this paper we introduce a weighted complex networks model to investigate and recognize structures of patterns. The regular treating in pattern recognition models is to describe each pattern as a high-dimensional vector which however is insufficient to express the structural information. Thus, a number of methods are developed to extract the structural information, such as different feature extraction algorithms used in pre-processing steps, or the local receptive fields in convolutional networks. In our model, each pattern is attributed to a weighted complex network, whose topology represents the structure of that pattern. Based upon the training samples, we get several prototypal complex networks which could stand for the general structural characteristics of patterns in different categories. We use these prototypal networks to recognize the unknown patterns. It is an attempt to use complex networks in pattern recognition, and our result shows the potential for real-world pattern recognition. A spatial parameter is introduced to get the optimal recognition accuracy, and it remains constant insensitive to the amount of training samples. We have discussed the interesting properties of the prototypal networks. An approximate linear relation is found between the strength and color of vertexes, in which we could compare the structural difference between each category. We have visualized these prototypal networks to show that their topology indeed represents the common characteristics of patterns. We have also shown that the asymmetric strength distribution in these prototypal networks brings high robustness for recognition. Our study may cast a light on understanding the mechanism of the biologic neuronal systems in object recognition as well.

Visual pattern recognition network: Its training algorithm and its optoelectronic architecture

A visual pattern recognition network and its training algorithm are proposed. The network constructed of a one-layer morphology network and a two-layer modified Hamming net. This visual network can implement invariant pattern recognition with respect to image translation and size projection. After supervised learning takes place, the visual network extracts image features and classifies patterns much the same as living beings do. Moreover we set up its optoelectronic architecture for real-time pattern recognition. (C) 1996 Optical Society of America

Ultrafast temporal pattern generation and recognition

Ultrafast temporal pattern generation and recognition with femtosecond laser technology is presented, analyzed, and experimentally implemented. Ultrafast temporal pattern generation and recognition are realized by taking advantage of two well-known techniques: the space-time conversion technique and the ultrafast pulse measurement technique. Here the temporal pattern for the designed multiple pulses, optimized with a preassumed Gaussian spectral distribution of an ultrashort pulse, is described. With the simulation of a Gaussian spectral distribution, we realize that the uniformity of the generated multiple ultrafast temporal pulses is relevant to the repeated number of modulation periods in the mask in the spectral plane. Moreover, the change of Gaussian spectral phases with the wavelengths in the modulated phase plate is considered. Experiments of ultrafast temporal pattern recognition by the frequency-resolved optical gating (FROG) characterization technique are also given. (C) 2004 Society of Photo-Optical Instrumentation Engineers.

Effects of morphine and its withdrawal on Y-maze spatial recognition memory in mice

Effects of morphine on acquisition and retrieval of memory have been proven in the avoidance paradigms. In present study, we used a two-trial recognition Y-maze to test the effects of acute morphine and morphine withdrawal on spatial recognition memory. T

Effect of Co-administration of Morphine and Cholinergic Antagonists on Y-maze Spatial Recognition Memory Retrieval and Locomotor Activity in Mice

吗啡和胆碱能系统的相互作用已在多项研究中提到,本实验想查明吗啡是否能和胆碱能拮抗剂、东莨菪碱以及阿托品共同作用对小鼠的Y迷宫空间识别记忆提取产生影响.采用测试前腹腔给药的方法,选用3种剂量的吗啡(5、1.5、0.5mg/kg),两种剂量的东莨菪碱(1、0.1mg/kg),以及两种剂量的阿托品(0.5、0.1mg/kg),剂量由高到低相配对作为联合给药的手段.其结果表明:1)0.5mg/kg低剂量吗啡与0.1 mg/kg低剂量的东莨菪碱,或与0.1 mg/kg低剂最的阿托品联合给药的小鼠,在记忆提取测试中, 空间探查行为(各臂停留时间百分比)对新异臂没有偏好,而新奇探索行为(各臂访问次数百分比)仍保持了对新异臂的偏好,而相应剂最药物单独给药的小鼠记忆提取均没有被损害;2)吗啡能和东莨菪碱相互作用使小鼠的活动性显著增强.暗示吗啡和胆碱能拮抗剂对小鼠空间记忆提取的破坏存在一定程度的相互作用.

Improved spatial recognition memory in mice lacking adenosine A(2A) receptors

Adenosine receptors play an important role in learning and memory as their antagonists have been found to facilitate learning and memory in various tasks in rodents. However, few studies have examined the effect of adenosine A(2A) receptor deficiency on c

Morphine and propranolol co-administration impair consolidation of Y-maze spatial recognition memory

In the present study, the interaction between morphine and the beta-adrenergic receptor antagonist, propranolol (PROP), in memory consolidation was investigated in a two-trial recognition Y-maze task. Four sets of Y-maze experiments were carried out in mi

Long-term exposure to extremely low-frequency magnetic fields impairs spatial recognition memory in mice

1. In the present study, we investigated the short- and long-term effects of extremely low-frequency (ELF) magnetic fields on spatial recognition memory in mice by using a two-trial recognition Y-maze that is based on the innate tendency of rodents to exp