Human Action Recognition in Videos Using Kinematic Features and Multiple Instance Learning

We propose a set of kinematic features that are derived from the optical flow for human action recognition in videos. The set of kinematic features includes divergence, vorticity, symmetric and antisymmetric flow fields, second and third principal invariants of flow gradient and rate of strain tensor, and third principal invariant of rate of rotation tensor. Each kinematic feature, when computed from the optical flow of a sequence of images, gives rise to a spatiotemporal pattern. It is then assumed that the representative dynamics of the optical flow are captured by these spatiotemporal patterns in the form of dominant kinematic trends or kinematic modes. These kinematic modes are computed by performing Principal Component Analysis (PCA) on the spatiotemporal volumes of the kinematic features. For classification, we propose the use of multiple instance learning (MIL) in which each action video is represented by a bag of kinematic modes. Each video is then embedded into a kinematic-mode-based feature space and the coordinates of the video in that space are used for classification using the nearest neighbor algorithm. The qualitative and quantitative results are reported on the benchmark data sets.     

基于小波的综合特征图像检索

针对单一视觉特征图像检索效果不够理想的问题，本文以小波变换为基础，提出了一种综合利用纹理，形状和空间特征共同进行检索的方法。实验结果表明，综合特征检索要比单一特征检索更符合人的视觉感受要求，因而检索效果更好。     

多维度特征的用户查询意图自动分类

为了提高搜索引擎查询结果的质量,越来越关注于对用户提交的网络查询意图的识别。基于查询session对用户提交的查询进行多维度特征提取,尽量能全面系统地描述查询分类特征,并使用SVM进行分类。实验结果表明通过结合查询的多个特征有助于识别查询意图,在人工标注的测试集中对查询意图分类的正确率达到80%。     

Sharing Multicast Videos Using Patching Streams

The access patterns of most information systems follow the 80/20 rules. That is, 80% of the requests are for 20% of the data. A video server can take advantage of this property by waiting for requests and serving them together in one multicast. This simple strategy, however, incurs service delay. We address this drawback in this paper by allowing clients to receive the leading portion of a video on demand, and the rest of the video from an ongoing multicast. Since clients do not have to wait for the next multicast, the service latency is essentially zero. Furthermore, since most services require the server to deliver only a small leading portion of the video, the server can serve many more clients per time unit. We analyze the performance of this approach, and determine the optimal condition for when to use this strategy. We compare its performance to a hardware solution called Piggybacking. The results indicate that more than 200% improvement is achievable.     

Adaptive Visual Servoing Using Point and Line Features With an Uncalibrated Eye-in-Hand Camera

This paper presents a novel approach for image-based visual servoing of a robot manipulator with an eye-in-hand camera when the camera parameters are not calibrated and the 3-D coordinates of the features are not known. Both point and line features are considered. This paper extends the concept of depth-independent interaction (or image Jacobian) matrix, developed in earlier work for visual servoing using point features and fixed cameras, to the problem using eye-in-hand cameras and point and line features. By using the depth-independent interaction matrix, it is possible to linearly parameterize, by the unknown camera parameters and the unknown coordinates of the features, the closed-loop dynamics of the system. A new algorithm is developed to estimate unknown parameters online by combining the Slotine–Li method with the idea of structure from motion in computer vision. By minimizing the errors between the real and estimated projections of the feature on multiple images captured during motion of the robot, this new adaptive algorithm can guarantee the convergence of the estimated parameters to the real values up to a scale. On the basis of the nonlinear robot dynamics, we proved asymptotic convergence of the image errors by the Lyapunov theory. Experiments have been conducted to demonstrate the performance of the proposed controller.      

多特征组合和图切割支持的物体/背景分割方法

运动物体分割是计算机视觉应用领域中的一个基本问题,阴影和亮度变化均易造成分割结果错误.通过组合多种图像特征,实现了一种新的检测运动物体方法.一方面,组合图像的颜色、梯度和纹理特征,利用梯度和纹理信息时亮度变化不敏感的特性,提高运动物体分割的准确性;另一方面,使用图切割算法对物体/背景进行分割,在不影响整体分割结果前提下修正局部判别错误的像素点,分割结果噪声少且稳定性强.对不同场景的分割结果表明,该方法是高效的和实用的.     

基于动态贝叶斯网络的音视频双模态说话人识别

动态贝叶斯网络在描述具有多个通道的复杂随机过程方面具有优异的性能．基于动态贝叶斯网络进行音视频双模态说话人识别的工作．分析了音视频联合建模的层级结构,利用动态贝叶斯网络对不同层级的音视频关联关系建立模型,并基于该模型进行音视频说话人识别的实验．通过对不同层级的建模过程及说话人识别实验的结果进行分析,结果表明,动态贝叶斯网络为描述音视频间的时序相关性和特征相关性提供了有效的建模方法,在不同语音信噪比的情况下均能提高说话人识别的性能．     

使用模板快速创建框架一致的屏幕录像

利用模板能更加快速地创建影片,以Macromedia Captivate为例,介绍模板的设计、制作及使用方法.能节省时间,统一风格,极大地提高工作效率.     

The Synchronization of Multiple Manipulators in Kali

This paper presents a strategy in multi-manipulator synchronization that treats the motions as finite state machines. We use the concept of a motion-system as a convenient abstraction for programming explicitly coupled motions. Motions, treated as processes, can communicate/affect one another through the use of control signals and the dynamics of the system are taken into account during the transitions between different motion states. Using examples, we show that such a scheme is general enough to cover diverse situations as two cooperating arms in a multi-manipulator environment, synchronizing motion of the feet of a legged robot for simple gaits and synchronizing the fingers of an anthropomorphic end-effector for simple grasping strategies.     

An AI-based Approach for Improved Sign Language Recognition using Multiple Videos

Multimedia Tools and Applications - People with hearing and speaking disabilities face significant hurdles in communication. The knowledge of sign language can help mitigate these hurdles, but most...     

An Evaluation of Equity Premium Prediction Using Multiple Kernel Learning with Financial Features

Neural Processing Letters - This paper introduces and extensively explores a forecasting procedure based on multivariate dynamic kernels to re-examine—under a non-linear, kernel methods...     

过程数字化技术在数码相机开发中的应用

利用UGⅡ软件强大的参数化建模功能和Wave Geometry Link模块实现了数码相机产品全参数化设计和更改;并结合MPI软件,利用STEP 203格式传递数据,实现了产品CAD／CAE／CAM一体化．仅用三个月时间就完成了数码相机从概念设计到模具样机的开发．     

多船舶的神经网络自适应同步控制

为了实现多艘船舶的同步运动,提出了多艘船的自适应同步控制策略.由于船舶模型参数不确定,采用了径向基神经网络来逼近不确定项,建立船舶的数学模型;其次,利用了数学图论来描述船舶之间的信息交流;接着为每艘船预先设定期望路径,并且将船舶的同步误差引入到控制器,控制船舶的运动使其不但沿各自期望路径运动,而且与多艘船舶保持同步;利用李雅普诺夫稳定性理论,证明了所设计的自适应同步控制器的稳定性;通过对三艘船舶的仿真表明,所提出神经网络自适应同步控制可以很好地解决多艘船同步控制问题.     

Scene Detection in Videos Using Shot Clustering and Sequence Alignment

Video indexing requires the efficient segmentation of video into scenes. The video is first segmented into shots and a set of key-frames is extracted for each shot. Typical scene detection algorithms incorporate time distance in a shot similarity metric. In the method we propose, to overcome the difficulty of having prior knowledge of the scene duration, the shots are clustered into groups based only on their visual similarity and a label is assigned to each shot according to the group that it belongs to. Then, a sequence alignment algorithm is applied to detect when the pattern of shot labels changes, providing the final scene segmentation result. In this way shot similarity is computed based only on visual features, while ordering of shots is taken into account during sequence alignment. To cluster the shots into groups we propose an improved spectral clustering method that both estimates the number of clusters and employs the fast global k-means algorithm in the clustering stage after the eigenvector computation of the similarity matrix. The same spectral clustering method is applied to extract the key-frames of each shot and numerical experiments indicate that the content of each shot is efficiently summarized using the method we propose herein. Experiments on TV-series and movies also indicate that the proposed scene detection method accurately detects most of the scene boundaries while preserving a good tradeoff between recall and precision.     

巧用电教媒体开拓课改的新渠道

全文主要从四个方面,来论述电教媒体在新课程改革中的作用：一、创设情境,激趣诱读;二、引人入境。熟读精思;三、凭借情境,学会积累;四、运用情景,激趣导说;巧妙地运用网络及多媒体优化组合,创设情景;在教师的点拨下,让学生自读、自悟、自练、自说;利用信息技术手段开拓学生自学的渠道,为新课程改革开拓新渠道。     

Adobe Camera Raw之高级使用技巧

RAW格式已经被越来越多的数码相机用户所接受,讨论了使用Adobe Camera Raw后期处理RAW格式图像的一些高级技巧:调整画笔的选择性调整功能、渐变滤镜、色调曲线中Ctrl键的使用、彩色照片转黑白、实现HDR效果、以智能对象打开图像、同时处理多张照片等。     

在嵌入式Linux平台上使用USB摄像头

分析并改进V4L标准，编写相应的USB摄像头驱动和应用程序；以FrameBuffer驱动为基础，实现LCD上的实时视频流显示。