- 更多网络例句与目标识别相关的网络例句 [注：此内容来源于网络，仅供参考]
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In this paper, the theory, algorithm, and experiment of automatic object detection and tracking are studied in depth. It is firstly pointed out that the essential of Mean Shift method is a special Newton-Gaussian method. A new method named Fast Mean Shift is established to stretch the conservative step of Mean Shift method. The convergence and validity of this new method are proved in theory. And it is also proved that the convergence speed of Fast Mean Shift is faster than that of Mean Shift. The contrast experiments of searching the maximum possibility density of random of data sets in plane and 3D space are done. The results show that this new method can reduce the iterations greatly. A new object tracking method based on Fast Mean Shift is built to improve the object tracking performance, which is shown in the face tracking experiment with the tennis sequence provided by the Ohio State University, and the car tracking experiment with the car sequence provided by Kalsruhe University. The face trcking experiment with highly noised images show that the object tracking method based on Fast Mean Shift has strong anti-jamming ability. A new fast color object detection technology based on characteristic color is established, which use characteristic color distribution to compute the characteristic color vector of any area in an image quickly. With the high performance search method, the fast object detection is achieved. At last, using object tracker based on Fast Mean Shift and color object detector based on characteristic color with the Kalman filter, PID controller, searial communication and other technologies, automatic object detection and tracking system with control system is built. The availability and anti-jamming ability of this system are verified by some object detection and tracking tests in different scenes.
本文对目标自动识别与跟踪进行了理论、计算、试验三方面的深入研究，主要包括：首次指出了目标跟踪技术中常用的均值迁移方法的本质为一种特殊的高斯-牛顿方法，改进了均值迁移方法步长取值保守的弱点，建立了快速均值迁移方法，证明了该方法的收敛性、有效性以及收敛速度优于均值迁移方法；进行了平面和3维随机分布数据集的最大概率密度搜索对比试验，试验结果表明，快速均值迁移方法大大减少了迭代次数；建立了基于快速均值迁移的目标跟踪方法，利用俄亥俄州立大学提供的乒乓球序列图像和卡斯鲁厄大学的汽车序列图像，对人脸和汽车目标跟踪性能分别进行了对比试验，并进行了高噪声人脸图像目标跟踪试验，结果表明，基于快速均值迁移的目标跟踪方法有效提高了目标跟踪性能，具有很强的抗干扰能力；建立了一种新型彩色目标自动识别方法，采用特征色彩分布函数实现了对任意图像区域特征色彩矢量的快速计算，建立了高效的搜索方法，实现了彩色目标的快速识别；将基于快速均值迁移方法的目标跟踪方法、基于特征色彩的目标识别方法与卡尔曼滤波、PID控制、串行通讯等技术结合，建立了带有控制系统的快速目标自动识别与跟踪系统，并在不同场景下进行了目标自动识别与跟踪试验，验证了快速目标自动识别与跟踪系统的有效性和抗干扰能力。
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Oilcan is a kind of typical rigid target with big backscattering coefficient, which takes on point figure if the resolution of SAR image is not very high; these point targets to be recognized gather together, and form a target region with some distribution area; the center of the region appears as a beeline, and the speckle noise appears scattered, therefore, considering the different grey distributions between point target and speckle noise region and the space geometry distribution, these point targets can be recognized by this algorithm.
由于在高分辨率情况下，合成孔径雷达图像中油罐个体的散射分别体现为由若干高亮度点围成的椭圆，待识别油罐目标的模糊边缘呈不连续的椭圆状，因此从二值化后的SAR图像中识别出拟目标的不连续边缘，判断其是否满足目标边缘特性来识别出最终结果，采用该方法解决了这类高分辨率下椭圆状目标的识别问题。本文运用了基于Gauss核函数支持向量机的SAR图像典型目标识别方法。
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In this chapter, three kinds of target recognition methods are performed, which are:①Target recognition method based on the description of polarization parameter plane. The echo polarization states of target are projected onto the polarization state plane described by the ellipticity ε and the tilt angle τ of the polarization ellipse, the change of parameter following ferquency becomes the chart. According to the changing trait of the chart, the multidimensional polarization feature space of target has been contructed. Furthermore, a series of polarization feature parameters used in designing the structure of target recognition device are extracted, and they are insensible to the posture of target.②Target recognition method based on the description of Poincare polarization sphere. The echo polarization states of target expressed by Stokes vector are projected onto the Poincare polarization sphere. The conception of polarization ferquency stability, which is used in describing the dynamic distribution characteristics of the target echo polarization states on Poincare polarization sphere, has been defined. A group of polarization feature parameters used in designing the structure of target recognition device are extracted, and they are insensible to the posture of target.③Target recognition method based on the description of frequency sensitivity. In accordance with the conception of the polarization state distance defined on Poincare polarization sphere, the frequency sensibility of the physical structure property of target has been investigated, the frequency distribution feature curves in PSD domain are obtained, and targets'features are extracted by means of the curve-fitting method with Least Square Criterion.
这章具体研究了基于三种极化散射特性描述的相应的目标识别方法：①基于极化参数平面描述的目标识别方法，将目标回波极化状态投影到以极化椭圆参数，即椭圆率角ε和倾角τ表征的极化状态平面上，参数随观测频率的变化就形成了图，根据图的变化特点构造了目标的多维极化特征空间，并提取了不敏感目标姿态变化的极化特征参数组来设计目标的识别器结构；②基于Poincare极化球面描述的目标识别方法，采用Stokes矢量表征目标回波的极化状态，并将其投影到描述极化状态的Poincare极化球面上，定义了极化频率稳定度的概念用以刻画目标回波极化状态在Poincare极化球面上的动态分布信息，提取了准方位不变性的目标极化特征，最后设计了目标的识别器结构；③基于频率敏感性描述的目标识别方法，通过在Poincare极化球面上所定义的极化状态距离的概念，研究的是复杂目标物理结构特性对探测信号频率的敏感程度问题，获得了在极化状态距离下的频率分布特性曲线，采用最小二乘估计曲线拟合方法，它既用于极化特征的降维，同时又直接将拟合参数作为目标的分类特征。
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With the limitation of the line detection based on traditional Hough transform that the information of the length and the end points of the line is unavailable, a new algorithm which makes use of the accessional strategy based on precognition information is put forward to meet the demand for more information of the line, simulation results show this method is effective. Finally, the whole process of airport target recognition is presented and the result images are also given.
使用分形方法提取目标的特征，在知识指导下，提出了一种基于目标特征模型的降维的形态学分形维数计算方法，对传统分形方法进行了改进，从理论上推证了算法的合理性，并对算法进行了仿真分析；针对传统Hough变换无法获得线段端点和长度信息的局限性，提出了一种基于目标特征先验知识的Hough变换融合策略，通过引入目标先验知识，可以有效地获得直线信息；对信息多而复杂的机场目标采用基于知识的目标识别方法，使用置信度模摘要型实现不确定推理，对目标进行识别判断，将知识贯穿于整个识别过程中，对目标进行了有效地识别。
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Based on the analysis to the particularity of the cruise missile attacking, a complete recognition method based on the knowledge is developed. A new fractal-based infrared image feature extraction method is presented and the detailed theoretic analysis and implement procedure of this algorithm is submitted and tested in some experiments. With the limitation of the line detection based on traditional Hough transform that the information of the length and the end points of the line is unavailable, a new algorithm which makes use of the accessional strategy based on precognition information is put forward to meet the demand for more information of the line, simulation results show this method is effective. Finally, the whole process of airport target recognition is presented and the result images are also given.
使用分形方法提取目标的特征，在知识指导下，提出了一种基于目标特征模型的降维的形态学分形维数计算方法，对传统分形方法进行了改进，从理论上推证了算法的合理性，并对算法进行了仿真分析；针对传统Hough变换无法获得线段端点和长度信息的局限性，提出了一种基于目标特征先验知识的Hough变换融合策略，通过引入目标先验知识，可以有效地获得直线信息；对信息多而复杂的机场目标采用基于知识的目标识别方法，使用置信度模型实现不确定推理，对目标进行识别判断，将知识贯穿于整个识别过程中，对目标进行了有效地识别。
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In degraded PSM matching classification, errors modification method of degraded PSM is presented and the matching tensor of every canonical scattering centers is given. In Chapter 4, the theory of wideband millimeter-wave radar target identification is introduced. It is indicated that, for HR radar target identification, description of temoral relations among features and pattern recogntion adaptive to variation of target angles are of key importance. A rule-based pattern recogniton method of sequential reasoning is proposed, which uses a series of rules to describe relations of features variation caused by target angles variation and has the advantages of adaption to unrandom variation and false probability control in classification over traditional statistical pattern recognitiop method. Feature extraction is crucial step in target identification. In range profiles identification application, features are extracted by means of range domain pre-processing algorithm, spacial and amplitude visual computation directly from range profiles and transform algorithm based on range profiles. Visual or transformed features are either sufficiently convinced or necessarily convinced and both of them are effective and robust to range profiles identification.
在第四章，首先对宽带毫米波体制背景下目标识别方法的一些特点进行了阐述并指出，在毫米波雷达目标识别中，特征之间动态关系的描述以及能适应目标姿态角变化的模式识别方法的研究乃是要解决的关键问题；进而提出了一种基于规则库的序贯推理模式识别新方法，在这种方法的研究中，主要包括序贯推理规则库的规则排列与特征选用顺序以及规则库的收敛等问题；这种方法克服了传统的统计模式识别方法特征利用效率不高、难以适应特征值的非随机性变化的缺点，把姿态角变化所引起的特征的变化用一系列规则加以表示，其优点是能适应特征值的非随机性动态变化，并能控制分类过程中的差错概率α；特征抽取是目标识别中的关键步骤，在基于目标距离像的特征抽取方法研究中，提出了距离空间域的预处理算法、距离空间域与幅度域的直观特征抽取方法以及基于目标距离像变换分析的特征抽取方法。
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A character-codes model based pattern recognition method by using amplitude data of targets frequency response is proposed after the establishment of high frequency response equation of radar targets. The method uses the same unvariant character-codes to express the same target of different angles and uses sequential separating of regions of target's reference variables to obtain multiple coding vectors of all regions for every target. The category and pose of target can be determined after a two-staged classification processing such as coding processing of target range profile data and errors correcting processing of coded data. The two-stage classification results are used to target identification as posterior hypothesis to be tested by sufficient convincing and necessary convincing. The character-codes model based pattern recognition method is also adaptive to variation of target angles and controllable in error probability. Time-consuming and complicated iterative computation is not necessary in the train process of pattern recognition.
首先建立了雷达目标的高频频率响应方程，这种方程将目标多散射中心理论与目标局部谐振理论有机地结合起来；进而提出了目标多频响应结构成像方法，这种方法将瑞利区频率响应或谐振区频率响应曲线的不同部位用各种不同的近似方法去逼近，通过特征谱估计方法将目标的局部频响特征与宽带距离响应特征结合起来；然后提出了一种基于姿态角变化区域的序贯划分与多模匹配的特征编码识别方法，这种方法具有能适应目标姿态角的变化以及能控制识别的差错概率α等优点，在目标识别时只需要目标在少数有限个频率激励下的幅频响应数据。
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The experiment comparisons based on the measured data show that proposed method combined with these three features achieves good classification performance and is low sensitive to Gausses white noise.
三类目标外场实测数据的识别试验结果显示，相对于单一特征的目标识别，综合上述三个特征的识别不但能获得更好的目标识别率，而且识别结果对高斯白噪声不敏感。
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In chapter 5, in allusion to the shortcoming of the existing high resolution radar target detection algorithm, taking the problem of high resolution radar target detection as the problem of true-false target recognition, and borrowing ideas from the dealing with novelty problem, this paper introduces one-class SVM into high resolution radar true-false target recognition for the first time. That can provide a new idea for solving high resolution radar true-false target recognition problem.
第五章针对现有的高分辨雷达目标检测算法的缺陷，将高分辨雷达目标检测问题等效为真假目标识别问题，并借鉴处理异常值问题的思想，首次将1类支持向量机引入高分辨雷达真假目标识别之中，为解决高分辨雷达真假目标识别问题提供了一条崭新的思路。
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The omni-vision system for RoboCup middle-size league soccer robot-NuBot and its method for object recognition are introduced firstly in the paper,and then a simple front vision system is used to improve the accuracy of recognition of the ball in front,and meantime an easy and effective calibration method for front vision system is presented,and finally the realization mechanism for the two vision systems working together is introduced,in which the processing speed of robot's object recognition can be accel...
为了快速正确地进行机器人的目标识别，首先介绍了RoboCup中型组足球机器人NuBot使用的全向视觉系统及其目标识别方法；然后通过引入一套简单的前向视觉系统来弥补全向视觉的不足，以提高机器人对其前方目标球的感知识别精度，同时给出了一种简单有效的前向视觉系统标定方法；最后介绍两套视觉系统共同工作的实现机制，以提高机器人的目标识别处理速度。
- 更多网络解释与目标识别相关的网络解释 [注：此内容来源于网络，仅供参考]
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discern：识别
房地产投资风险管理机构的任务应该是围绕风险管理目标,即实现房地产投资利益最大化或风险最小,对房地产投资风险进行识别(Discern)-分析(Analy-sis)-决策(Decision)-控制(Control)-处理(Dis-pose)的有机过程.
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distinguish from sketch：草图识别
品种鉴定:Cultivars distinguish | 草图识别:distinguish from sketch | 目标识别:Target Distinguish
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object distance：目标距离
oat 氧化物对准晶体管工艺 | object distance 目标距离 | object identification 目标识别
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object language program：目标语言程序
对象识别符型式 object identifier type | 目标语言,目标语言 object language | 目标语言程序 object language program
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speech recognition：语音识别
+ '''语音识别'''(Speech recognition)技术,也被称为'''自动语音识别'''(Automatic Speech Recognition,简称ASR),其目标是将人类的语音中的词汇内容转换为计算机可读的输入,例如按键、二进制编码或者字符序列.
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targe point：目标点
target column 目标列 | targe point 目标点 | target recognition 目标识别(辨认)
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targeting：目标市场
现代企业营销战略的核心被称为"STP 营销",即细分市场(segmenting)、选择目 标市场(Targeting)和产品定位(positioning). "STP"营销即目标市场营销能够帮助企 业更好地识别市场机会,从而为每个目标市场提供适销对路的产品.
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unclassified track：未识别的目标回波
unclassified technical order 一般性技术规程 | unclassified track 未识别的目标回波 | unclean bill of lading 不清洁提单
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IFF：敌我识别
预警由八部脉冲多普勒D-波段MPQ-49型"前方区域警戒雷达"(FAAR)提供,探测距离1到15公里(对于雷达横断面0.2平方米目标);使用综合AN/TPX-50(Mk XII)"敌我识别"(IFF)系统;由ADA指挥部雷达排控制,通过无线电数据链传送目标座标到TADDS.
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IFF：敌我识别系统
1988年,美国参议院武装委员会就提出了要研发"非合作目标识别"(NCTR)技术,作为已有"敌我识别系统"(IFF)的辅助设备甚至取而代之. 现有的询问-应答式敌我识别系统并不保险,例如,友军飞机的IFF设备可能出故障或编码失效,