action-object

action-object的基本解释

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[计][SAA]操作对象

与action-object相关的网络例句 [注：此内容来源于网络，仅供参考]

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。

By measuring missile movement inertia with torsion pendulum, the influences of periodic measurement error, systemic damp, period of swing object and corporative period of t he measured object and swinging object were analyzed. The relation among measurement error of movement inertia, measureme nt period, the period of swing object,corporaˉ tive period of tested object and swing object was proved. The maxi mal ratio between movement inertia for swinging obˉ ject and the measured object under conditions of different errors w as given under typical measurement precision.

通过扭摆测量导弹转动惯量的方法，分析了周期测量误差、系统阻尼、摆动体周期以及被测件和摆动体共摆周期对转动惯量测量精度的影响，得出转动惯量测量误差和周期测量误差、摆动体摆动周期、被测件和摆动体共摆周期之间的关系，给出了在典型的测量精度要求，不同的周期测量误差情况下，摆动体转动惯量和被测件转动惯量之间的最大比值。

Firstly, a signalized point is stuck on a moving object to be tested, a microphone array and two video cameras are arranged, and the video cameras are demarcated to obtain a projection matrix; sound pressure signals of a sound source in the moving object to be tested are obtained by the microphone in an array mode, the dynamic video of the moving object to be tested is obtained and disassembled into an image by the video cameras; the signalized point on the moving object to be tested is identified in the video image and the matched signalized point is treated with three-dimension reconstruction to obtain the spatial location of the moving object to be tested; the sound pressure signals are treated with beam forming treatment to obtain a sound field characteristic function scattergram of the moving object to be tested, the video image is treated with spatial coordinate superposition frame by frame and restored into a dynamic video image.

首先在被测运动物体粘贴标志点，布置传声器阵列和两台摄像机，对摄像机进行标定，得到投影矩阵；传声器阵列获取被测运动物体中声源的声压信号，摄像机获取被测运动物体的动态视频，将动态视频拆解成图像；在视频图像中识别出被测运动物体上的标志点，对匹配后的标志点进行三维重构，获取被测运动物体的空间位置；对声压信号进行波束成型处理，得到被测运动物体的声场特征函数分布图，将其视频图像进行逐帧空间坐标叠加，并还原成动态视频图像。

与action-object相关的网络解释 [注：此内容来源于网络，仅供参考]

retained object：保留宾语 complex object 复合宾语

indirect object 间接宾语 dative verb 与格动词 | retained object 保留宾语 complex object 复合宾语 | subject complement 主语补语 object complement 宾语补语

indirect object：间接宾语 dative verb 与格动词

cognate object 同源宾语 direct object 直接宾语 | indirect object 间接宾语 dative verb 与格动词 | retained object 保留宾语 complex object 复合宾语

cognate object：同源宾语 direct object 直接宾语

2)subordinative conjunction 从属连词 | cognate object 同源宾语 direct object 直接宾语 | indirect object 间接宾语 dative verb 与格动词