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1.
视频分割技术的发展   总被引:27,自引:1,他引:26  
随着MPEG-4和MPEG-7的研究发展以及最近几年数字视频图书馆技术的崛起,基于内容编码和面向对象的存取和操纵技术日益受到人们的重视,视频分割技术迅速成为当前视频研究领域的热点。视频分割是新一代视频编码、视频检索、互联网多媒体交互等新兴领域的关键技术。介绍了视频分割的主要技术,对其算法和性能进行了比较和评述,并分析了当前视频分割技术的研究现状、尚存在的问题和研究前景。  相似文献
2.
Reliable Estimation of Dense Optical Flow Fields with Large Displacements   总被引:23,自引:5,他引:18  
In this paper we show that a classic optical flow technique by Nagel and Enkelmann (1986, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 8, pp. 565–593) can be regarded as an early anisotropic diffusion method with a diffusion tensor. We introduce three improvements into the model formulation that (i) avoid inconsistencies caused by centering the brightness term and the smoothness term in different images, (ii) use a linear scale-space focusing strategy from coarse to fine scales for avoiding convergence to physically irrelevant local minima, and (iii) create an energy functional that is invariant under linear brightness changes. Applying a gradient descent method to the resulting energy functional leads to a system of diffusion–reaction equations. We prove that this system has a unique solution under realistic assumptions on the initial data, and we present an efficient linear implicit numerical scheme in detail. Our method creates flow fields with 100 % density over the entire image domain, it is robust under a large range of parameter variations, and it can recover displacement fields that are far beyond the typical one-pixel limits which are characteristic for many differential methods for determining optical flow. We show that it performs better than the optical flow methods with 100 % density that are evaluated by Barron et al. (1994, Int. J. Comput. Vision, Vol. 12, pp. 43–47). Our software is available from the Internet.  相似文献
3.
运动目标检测算法的探讨   总被引:22,自引:0,他引:22  
万缨  韩毅  卢汉清 《计算机仿真》2006,23(10):221-226
运动目标检测是实现目标跟踪、交通监控、行为分析等任务的基础。但由于运动目标的提取易受到背景、光线变化、阴影、运动速度等因素的影响而造成失败,所以如何更好的实现运动目标检测具有相当重要的意义。该文从运动目标检测的基本概念出发,探讨了运动目标检测的广泛用途、目前所面临的主要问题与困难、实现运动目标检测算法的基本分类,并结合近几年公开发表的一些算法与实现对当前主流运动目标检测实现方法的基本思想和最新进展进行了分类综述,讨论了各类方法的主要优缺点,并展望了该领域未来的发展趋势。  相似文献
4.
基于形变模型的三维人脸重建方法及其改进   总被引:16,自引:0,他引:16  
形变模型(morphable model)是近几年出现的三维人脸建模新方法.该方法使用原型人脸的组合表示新的人脸,对于特定人脸图像,通过模型匹配实现了三维人脸的自动重建.虽然形变模型具有自动化、真实感好等优点,但现有形变模型的建立依赖于不稳定的人脸图像对应光流算法,模型匹配只考虑了一般光照环境下的人脸重建问题,且建模计算量大.针对以上问题,文章对形变模型进行了改进:提出了网格重采样的方法,实现了模型人脸数据的精确对应;建立了多分辨率的三维人脸模型;在模型匹配过程中采用了多光源光照模型,使模型可适用于复杂光照环境下的人脸重建.实验结果表明,上述改进可以有效提高模型匹配的效率和准确性以及模型对光照的适应性.  相似文献
5.
This paper describes an approach for tracking rigid and articulated objects using a view-based representation. The approach builds on and extends work on eigenspace representations, robust estimation techniques, and parameterized optical flow estimation. First, we note that the least-squares image reconstruction of standard eigenspace techniques has a number of problems and we reformulate the reconstruction problem as one of robust estimation. Second we define a subspace constancy assumption that allows us to exploit techniques for parameterized optical flow estimation to simultaneously solve for the view of an object and the affine transformation between the eigenspace and the image. To account for large affine transformations between the eigenspace and the image we define a multi-scale eigenspace representation and a coarse-to-fine matching strategy. Finally, we use these techniques to track objects over long image sequences in which the objects simultaneously undergo both affine image motions and changes of view. In particular we use this EigenTracking technique to track and recognize the gestures of a moving hand.  相似文献
6.
Nonquadratic variational regularization is a well-known and powerful approach for the discontinuity-preserving computation of optic flow. In the present paper, we consider an extension of flow-driven spatial smoothness terms to spatio-temporal regularizers. Our method leads to a rotationally invariant and time symmetric convex optimization problem. It has a unique minimum that can be found in a stable way by standard algorithms such as gradient descent. Since the convexity guarantees global convergence, the result does not depend on the flow initialization. Two iterative algorithms are presented that are not difficult to implement. Qualitative and quantitative results for synthetic and real-world scenes show that our spatio-temporal approach (i) improves optic flow fields significantly, (ii) smoothes out background noise efficiently, and (iii) preserves true motion boundaries. The computational costs are only 50% higher than for a pure spatial approach applied to all subsequent image pairs of the sequence.  相似文献
7.
纹理约束下的人脸特征点跟踪   总被引:13,自引:0,他引:13       下载免费PDF全文
宋刚  艾海舟  徐光祐 《软件学报》2004,15(11):1607-1615
将Lucas-Kanade光流跟踪算法与人脸特征点定位的统计模型DAM(direct appearance model)在Bayesian框架下结合起来,提出了视频中人脸特征点定位与跟踪的一种混合模型方法.利用Lucas-Kanade算法预测人脸特征点的位置,充分利用了帧间的相关信息,提高了跟踪的速度.通过DAM中纹理对形状的约束,在提高跟踪精度的同时增强了整个算法的鲁棒性.实验表明,这种方法可以很好地适应人脸的多种运动,可用于人脸识别或3D人脸建模.  相似文献
8.
9.
图象光流场计算技术研究进展   总被引:12,自引:2,他引:10  
时变图象光流场计算技术是计算机视觉中的重要研究内容,也是当今研究的热点问题。为了使人们对该技术有一个较全面的了解,因而对时变图象光流场计算技术的研究和进展做了较系统的论述,首先分别列举了灰度时变图象和彩色时变图象的光流场计算方法,并对这些方法进行了分类,然后总结了出目前图象光流场计算中存在的几个问题,最后对光流场计算技术的研究发展及其应用前景指出了一些可能的方向。  相似文献
10.
Differential methods belong to the most widely used techniques for optic flow computation in image sequences. They can be classified into local methods such as the Lucas–Kanade technique or Bigün's structure tensor method, and into global methods such as the Horn/Schunck approach and its extensions. Often local methods are more robust under noise, while global techniques yield dense flow fields. The goal of this paper is to contribute to a better understanding and the design of novel differential methods in four ways; (i) We juxtapose the role of smoothing/regularisation processes that are required in local and global differential methods for optic flow computation. (ii) This discussion motivates us to describe and evaluate a novel method that combines important advantages of local and global approaches: It yields dense flow fields that are robust against noise. (iii) Spatiotemporal and nonlinear extensions as well as multiresolution frameworks are presented for this hybrid method. (iv) We propose a simple confidence measure for optic flow methods that minimise energy functionals. It allows to sparsify a dense flow field gradually, depending on the reliability required for the resulting flow. Comparisons with experiments from the literature demonstrate the favourable performance of the proposed methods and the confidence measure.  相似文献
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