Augmented reality-based border management

Virtual Reality - A proficient border management has typically been tied to its capability to support information structuring and to make exchanges from the distributed sources. The lack of a...     

Augmented reality-based training system for hand rehabilitation

This study designs a training system for hand rehabilitation on the basis of augmented reality technology, which enables patients to simultaneously interact with real and virtual environments. The system framework is introduced, and four rehabilitation programs, namely, trajectory training, shelf training, batting training, and spile training, are presented. As a requirement of hand rehabilitation training, a color marker that is suitable for hand rehabilitation training is adopted. Following the Hamming coding principle, this marker is designed as a 7?×?7 square that is filled up by four designated colors with a binary bit of “0” or “1”. The check code in each row of the color marker is applied to restore the occluded binary bits, solve the occlusion issue of color markers, and complete the tracking registration of the color markers. The effectiveness of the developed system is evaluated via a usability study and questionnaires. The evaluation provides positive results. Therefore, the developed system has potential as an effective rehabilitation system for upper limb impairment.     

Augmented reality-based design customization of footwear for children

This paper presents a systematic framework for design customization of footwear for children and identifies three modules related to shoe styling: shoe surface, shoe bottom, and accessory. A new module, shoe cloth, is created to allow a quick change of shoe appearance. Consumers can specify various design attributes in each module, including color, texture, embroidery, and shape. A prototype design system is implemented using augmented reality and sensing technologies based on the framework. This system consists of novel functions that support customization, design evaluation, and pattern development. The user can virtually put a customized shoe model on his/her foot in a video stream. The proposed framework not only facilitates evaluating products that are highly interactive with users, but also helps engage them in the design process. This work realizes the concept of human-centric design for mass customization.     

Augmented reality-based remote coaching for fast-paced physical task

Virtual Reality - One popular application of augmented reality (AR) is the real-time guidance and training in which the AR user receives useful information by a remote expert. For relatively...     

Augmented reality-based robot teleoperation system using RGB-D imaging and attitude teaching device

Augmented reality (AR)-based programming using the demonstration method has been widely studied. However, studies on AR-based programming for remote robots are lacking because of the limitation of human–computer interaction. This paper proposes an AR-based robot teleoperation system and method using RGB-D imaging and an attitude teaching device. By sending the color and depth images of the remote robot environment to the local side, the operators can complete the teleoperation of the robot at the local side. First, the operators select key positions on the motion path of the robot endpoint from color images via a mouse, and the computer calculates the 3D coordinates of these key points in the robot base coordinate system to complete the position teaching process. In the robot attitude teaching process, the AR technology is used to superimpose the virtual robot model onto the color images of the robot teleoperation environment, so as to make the virtual robot endpoint to move along the teaching path. An operator can use the portable attitude teaching device designed in this study to control the robot movement parameters, such as the attitude and motion speed, during the movement of the virtual robot. After the position and attitude teaching processes, the robot movement trajectory can be generated. To make the base coordinate system of the virtual model consistent with that of the physical robot, we propose an online AR registration method, which does not require manually placing the AR registration marker. The proposed AR-based robot teleoperation system can quickly and easily complete robot teleoperation at the local side.     

ChildAR: an augmented reality-based interactive game for assisting children in their education

Universal Access in the Information Society - This paper presents an augmented reality (AR)-based game for childhood education. The developed AR game teaches children by giving them tasks and...     

基于静态贝叶斯博弈的攻击预测模型

提出了基于静态贝叶斯博弈的攻击预测模型.该模型通过模拟攻击者和防御者的攻防行为选择,能预测出理性的攻击者和防御者为最大化各自的收益会选择攻击和防御的概率.预测结果为网络安全管理员进行安全配置提供了有价值的参考依据,从而使被动的检测变为主动的有针对性的防御成为可能.最后介绍了相应的实验过程和结果分析,验证了模型的有效性.     

数据预测技术及其在网络游戏中的应用

在网络游戏中采用数据预测技术，即使在数据传输过程中发生堵塞延迟等情况，仍然能使游戏流畅运行。根据网络游戏中的实际情况，提出了一种基于吸引子原理的角色行为预测算法。它是以网络游戏中的统计规律作为依据，更好地预测了角色在游戏中的行为，从而在网络情况不佳的情况下，仍然保证了游戏的基本流畅。     

Sparse HDLSS discrimination with constrained data piling

Regularization is a key component in high dimensional data analyses. In high dimensional discrimination with binary classes, the phenomenon of data piling occurs when the projection of data onto a discriminant vector is dichotomous, one for each class. Regularizing the degree of data piling yields a new class of discrimination rules for high dimension–low sample size data. A discrimination method that regularizes the degree of data piling while achieving sparsity is proposed and solved via a linear programming. Computational efficiency is further improved by a sign-preserving regularization that forces the signs of the estimator to be the same as the mean difference. The proposed classifier shows competitive performances for simulated and real data examples including speech recognition and gene expressions.     

RTS游戏中用户行为的神经网络预测模型

即时战略游戏(简称RTS游戏)中,用户的行为由于游戏自身庞大的决策空间而难以预测.针对这个问题,提出了通过对RTS游戏的对战记录进行分析,建立5种结构的神经网络模型来预测用户行为的方法.模型考虑了不同时间片的状态对于决策行为的影响,设计了单时间片输入和双时间片输入的神经网络,并与基于动态贝叶斯网络的模型进行了比较.实验结果表明,基于单时间片输入的神经网络模型能够更加快速地完成训练过程并达到满意的预测准确度.     

Chaotic time series prediction for the game, Rock-Paper-Scissors

Two players of Rock-Paper-Scissors are modeled as adaptive agents which use a reinforcement learning algorithm and exhibit chaotic behavior in terms of trajectories of probability in mixed strategies space. This paper demonstrates that an external super-agent can exploit the behavior of the other players to predict favorable moments to play against one of the other players the symbol suggested by a sub-optimal strategy. This third agent does not affect the learning process of the other two players, whose only goal is to beat each other. The choice of the best moment to play is based on a threshold associated with the Local Lyapunov Exponent or the Entropy, each computed by using the time series of symbols played by one of the other players. A method for automatically adapting such a threshold is presented and evaluated. The results show that these techniques can be used effectively by a super-agent in a game involving adaptive agents that exhibit collective chaotic behavior.     

基于序列到序列结构的MOBA游戏局势趋势预测模型

多人在线战术竞技(MOBA)游戏是当前世界最流行的电子游戏类型之一,该类游戏涉及的知识领域相当复杂.随着电子竞技产业的飞速发展,数据分析对MOBA游戏的影响也越来越大,在对该类游戏的实时局势进行评价时,一般是选择过程变量作为指标,例如经济差、经验差,但目前缺少趋势预测的相关研究.针对该问题,提出一种基于序列到序列结构的MOBA游戏趋势预测模型(MOBA-Trend).在预处理阶段,针对该类游戏数据的特点,设计一种数据缩放算法体现数据间的重要度,并使用低通滤波器消除数据噪声;之后将双方阵容与历史战斗信息作为输入特征,构建带有注意力机制的序列模型,同时预测经济差、经验差;最后将模型应用于Dota 2,构建并发布相关数据集.实验结果表明,所提出的模型能够有效地预测序列的变化趋势.     

基于不完全信息多阶段博弈的入侵路径预测

随着入侵的推进入侵者掌握的信息会逐步增加,依据新信息入侵者会找到更好的入侵路径并作出调整。为了使防御方能准确预测入侵路径,首先基于超图理论建立动态防御图并提出动态防御图更新方法,对入侵者的信息更新进行预测;然后建立不完全信息多阶段博弈模型对不同阶段入侵者的入侵路径调整进行预测;最后设计基于博弈的动态防御图路径预测算法,对完整的入侵路径进行预测。实验给出对入侵路径进行预测的典型实例,对实例结果的分析说明了模型的合理性与准确性。     

Flexible prediction block decomposition with multi-channel filter banks for video coding

A flexible prediction block decompostion method is presented with three transform tools in terms of a multi-channel filter bank system for the latest video coding standard H.264/AVC. The 4 X 4 and 8 X 8 integer discrete cosine transforms of H.264/AVC are subsituted by these new tools such that the transform is quite well adapted to variable prediction blocks. As a result, block artefacts are reduced without much effect on the sharpness of the content, and the spatial relativity is utilised quite efficiently for prediction blocks of bigger size. Consequently, the subjective quality as well as the objective quality is improved.     

An embedding technique based upon block prediction

This paper presents a novel data hiding scheme for VQ compression images. This scheme first uses SMVQ prediction to classify encoding blocks into different types, then uses different codebooks and encoding strategies to perform encoding and data hiding simultaneously. In using SMVQ prediction, no extra data is required to identify the combination of encoding strategies and codebook, which helps improve compression performance. Furthermore, the proposed scheme adaptively combines VQ and SMVQ encoding characteristics to provide higher image quality of stego-images while size of the hidden payload remains the same. Experimental results show that the proposed scheme indeed outperforms other previously proposed schemes in image quality of the stego-images and compression performance.     

基于机器学习的RTS游戏实时胜率预测

游戏胜负预测可用于自适应游戏AI的设计,策略层面强化学习的反馈参数等。使用SC2LE公开的数据集,首先通过游戏时间、MMR和AMP指标进行数据预处理,得到质量较高的数据集;然后使用pysc2解析,提取游戏数据;最后进行特征分析,得到基础特征和统计特征,完成游戏特征数据集的构建。最终采用机器学习方法XGB分类模型,利用10次十折交叉验证法进行模型评估与优选。结果表明使用基础特性与统计特性的组合,可以使得实时胜率预测准确率在不同匹配对局情况下均超过80%。     

Augmented reality camera tracking with homographies

To realistically integrate 3D graphics into an unprepared environment, camera position must be estimated by tracking natural image features. We apply our technique to cases where feature positions in adjacent frames of an image sequence are related by a homography, or projective transformation. We describe this transformation's computation and demonstrate several applications. First, we use an augmented notice board to explain how a homography, between two images of a planar scene, completely determines the relative camera positions. Second, we show that the homography can also recover pure camera rotations, and we use this to develop an outdoor AR tracking system. Third, we use the system to measure head rotation and form a simple low-cost virtual reality (VR) tracking solution.     

基于实时战略游戏重放记录数据编码和机器学习的游戏获胜者预测

对实时战略(RTS)游戏仿真平台μRTS自带的RTS游戏AI机器人之间进行游戏比赛产生的重放记录数据进行采样,用独热编码对采样点数据中的游戏玩家在游戏中的状态和动作信息进行编码,利用卷积神经网络、支持向量机和K-近邻等机器学习算法对RTS游戏AI机器人在游戏比赛中的获胜者进行预测.实验结果表明,结合给出的编码方法和机器...     

基于混合高斯隐马尔可夫模型的带式输送机堆煤时刻预测方法

提出了一种基于混合高斯隐马尔可夫模型的带式输送机堆煤时刻预测方法。该方法根据传感器采集的带式输送机功率时序数据建立带式输送机运行状态的混合高斯隐马尔可夫模型,基于该模型采用基于图的状态序列遍历算法和基于切普曼-柯尔莫哥罗夫方程的概率转移算法对带式输送机堆煤时刻进行预测:基于图的状态序列遍历算法通过寻找当前状态到堆煤状态的通路确定剩余时间;基于切普曼-柯尔莫哥罗夫方程的概率转移算法通过粒子群优化算法及切普曼-柯尔莫哥罗夫方程交叉验证来获取训练样本上失败状态的概率阈值,并计算当前的状态迁移到超过失败状态概率阈值的转移次数来确定剩余时间。基于煤矿生产实际数据集的实验验证了该方法可有效预测带式输送机的堆煤发生时刻。     

Rendering Wave Effects with Augmented Light Field

Ray–based representations can model complex light transport but are limited in modeling diffraction effects that require the simulation of wavefront propagation. This paper provides a new paradigm that has the simplicity of light path tracing and yet provides an accurate characterization of both Fresnel and Fraunhofer diffraction. We introduce the concept of a light field transformer at the interface of transmissive occluders. This generates mathematically sound, virtual, and possibly negative‐valued light sources after the occluder. From a rendering perspective the only simple change is that radiance can be temporarily negative. We demonstrate the correctness of our approach both analytically, as well by comparing values with standard experiments in physics such as the Young's double slit. Our implementation is a shader program in OpenGL that can generate wave effects on arbitrary surfaces.