| 1. | Placement outline projection vector invalid . floor outline projection vector invalid . top outline projection vector invalid . taper vector invalid . invalid translation direction
如果未定义或未使用有效值定义任何矢量，则显示以下消息。 |
| 2. | The projection index values were gave by multiplying projection vector by standardization value of evaluation indexes , which can comprehensively evaluate agricultural resources use efficiency of every unit
通过最佳投影方向与评价指标的线性投影得到投影指标值，通过这一指标可以对样本进行统一评价。 |
| 3. | The outer contour of the silhouette is projected along the midline of the body to obtain the fore - and - aft midline projection vectors , which are then combined into one dimensional vector as the gait feature
将外轮廓沿人体中线投影可以得到前后两个向量,合成1d向量( midlineprojectionvector ,中线投影向量)作为步态特征。 |
| 4. | Project pursuit can be used to project high dimensional data to low dimensional space and find the optimum projection vector of data in one dimension space by data character of research units , which can comprehensively evaluate the value and direction of every index
该方法可以依据样本自身的数据特性寻求最佳投影方向，从而判断各评价指标对综合评价目标的贡献大小和方向。 |
| 5. | The algorithm acquires the quantity of two - dimensional spatial translation by means of projecting each frame apart along horizontal and vertical direction and using multi - resolution spectrum decomposition approach to process the two projection vectors , respectively
该算法首先引入积分投影方法将图像序列中的每帧图像转换成两个一维积分投影向量，再应用多分辨谱分解方法对两个投影向量分别进行处理，从而精确地获取图像在二维空间上的亚像素平移量。 |
| 6. | First we construct a covariance matrix from sample images , then compute the eigenvalues and corresponding eigenvectors of the covariance matrix , construct a feature matrix with the eigenvectors . then every images in database can be projected into the feature matrix and gain a projection vector , so does the input image . then we can judge the resemblance between input image with each image in database by computing the distance between their projection vectors
我们首先根据采集的样本图像构造一个协方差矩阵，然后求取该矩阵的特征值，以这些矩阵特征值对应的特征向量构造出一个特征空间，然后将输入图像向该特征空间映射，将获取的映射系数与样本库中图像的映射系数进行距离计算，根据计算出的距离判定输入图像与样本图像间的匹配程度。 |
| 7. | First we construct a covariance matrix from sample images , then compute the eigenvalues and corresponding eigenvectors of the covariance matrix , construct a feature matrix with the eigenvectors . then every image in database can be projected into the feature matrix and gain a projection vector , so does the input image . then we can judge the resemblance between input image with each image in database by computing the distance between their projection vectors
然后，根据采集的样本图像构造一个协方差矩阵，求取该矩阵的特征值，以这些矩阵特征值对应的特征向量构造一个特征空间，将输入图像向该特征空间映射，计算获取的映射系数与样本库中各类图像的映射系数的欧基里德距离，根据计算出的距离判定输入图像与样本图像间的匹配程度。 |
| 8. | Projection algorithm is presented as follows : first , characterize the reference image and the float image and turn into binary images ; then , project the binary images onto the abscissa and y - axis and get the projection vectors ; last , according to the elements of the vectors , the rotation and translation parameters were calculated separately
投影法通过二值化参考图象和浮动图象，沿x轴、 y轴投影得到投影向量，然后根据投影向量元素的大小和位置，分别检测图象间旋转、平移运动的大小。 |
