针对传统视觉位姿测量方法依赖场景内目标的已知结构信息或者人为标记的问题,设计了一种基于特征匹配的相对位姿测量方法和系统,在进行相对位姿测量时无需知道场景内目标的先验信息,且有较高的测量精度。首先,使用双目相机对场景内目标...针对传统视觉位姿测量方法依赖场景内目标的已知结构信息或者人为标记的问题,设计了一种基于特征匹配的相对位姿测量方法和系统,在进行相对位姿测量时无需知道场景内目标的先验信息,且有较高的测量精度。首先,使用双目相机对场景内目标进行序列图像采集,计算机采用AKAZE算法对图像进行特征提取。然后,采用改进的KNN与RANSAC算法对相邻图像进行特征匹配并剔除误匹配点,得到正确的匹配点对后,采用三角法测量和光束法平差优化获得特征点的三维坐标,利用三维坐标与二维图像特征向量建立三维特征点库。之后,位姿测量时先使用单目相机对场景目标进行图像采集,再对待测图像进行AKAZE特征提取,将得到的特征点与特征点库进行匹配,采用EP n P+Gauss-Newton方法求解出待测图像对应的相机位姿。实验中,利用高精度转台转动摄像机并拍摄多幅图像进行测量,结果表明,位姿测量系统在[-20°,20°]范围内最大测量误差不超过0.2°,可以满足应用需求。展开更多
In many automatic face recognition systems, posture constraining is a key factor preventin g them from application. In thi5.paper, a series of strategles. will be described to achieve a system which enables face recog...In many automatic face recognition systems, posture constraining is a key factor preventin g them from application. In thi5.paper, a series of strategles. will be described to achieve a system which enables face recognition under varying pose. These approaches include the multi-view face modeling, the threshold image based face feature detection, the affine transformation based face posture normalization and the template matching based face idelltification. Combining all of these strategies, a face recognition system with the pose invariance is designed successfully. Using a 75MHZ Pentium PC and with a database of 75 individuals, 15 images for each person, and 225 test images with various postures, a very good recognition rate of 96.89% is obtained.展开更多
A binocular stereo vision positioning method based on the scale-invariant feature trans- form （SIFT） algorithm is proposed. The SIFT algorithm is for extracting distinctive invariant features from images. First, ima...A binocular stereo vision positioning method based on the scale-invariant feature trans- form （SIFT） algorithm is proposed. The SIFT algorithm is for extracting distinctive invariant features from images. First, image median filtering is used to eliminate image noise. Then, according to the characteristics of the target satellite, image map is used to extract the middle part of the target satel- lite. At last, the feature match point under the SIFT algorithm is extracted, and the three-dimension- al position and orientation are calculated. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The experimental result shows that the al- gorithm works well and the maximum relative error is within 0. 02 m and 2.5 o展开更多
基金Aeronautical Science Foundation of China (No.ASFC-201951048002)。
文摘针对传统视觉位姿测量方法依赖场景内目标的已知结构信息或者人为标记的问题,设计了一种基于特征匹配的相对位姿测量方法和系统,在进行相对位姿测量时无需知道场景内目标的先验信息,且有较高的测量精度。首先,使用双目相机对场景内目标进行序列图像采集,计算机采用AKAZE算法对图像进行特征提取。然后,采用改进的KNN与RANSAC算法对相邻图像进行特征匹配并剔除误匹配点,得到正确的匹配点对后,采用三角法测量和光束法平差优化获得特征点的三维坐标,利用三维坐标与二维图像特征向量建立三维特征点库。之后,位姿测量时先使用单目相机对场景目标进行图像采集,再对待测图像进行AKAZE特征提取,将得到的特征点与特征点库进行匹配,采用EP n P+Gauss-Newton方法求解出待测图像对应的相机位姿。实验中,利用高精度转台转动摄像机并拍摄多幅图像进行测量,结果表明,位姿测量系统在[-20°,20°]范围内最大测量误差不超过0.2°,可以满足应用需求。
文摘In many automatic face recognition systems, posture constraining is a key factor preventin g them from application. In thi5.paper, a series of strategles. will be described to achieve a system which enables face recognition under varying pose. These approaches include the multi-view face modeling, the threshold image based face feature detection, the affine transformation based face posture normalization and the template matching based face idelltification. Combining all of these strategies, a face recognition system with the pose invariance is designed successfully. Using a 75MHZ Pentium PC and with a database of 75 individuals, 15 images for each person, and 225 test images with various postures, a very good recognition rate of 96.89% is obtained.
文摘A binocular stereo vision positioning method based on the scale-invariant feature trans- form （SIFT） algorithm is proposed. The SIFT algorithm is for extracting distinctive invariant features from images. First, image median filtering is used to eliminate image noise. Then, according to the characteristics of the target satellite, image map is used to extract the middle part of the target satel- lite. At last, the feature match point under the SIFT algorithm is extracted, and the three-dimension- al position and orientation are calculated. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The experimental result shows that the al- gorithm works well and the maximum relative error is within 0. 02 m and 2.5 o
