Film and television industry cloud exhibition design based on 3D imaging and virtual reality

The three-dimensional virtual scene can provide users with a visual three-dimensional virtual environment, with various multimedia channels such as sound, video, force feedback equipment, etc., to bring users a completely immersive interactive experience. This paper introduces 3D imaging and virtual reality technology in the film and television industry cloud exhibition, and develops a virtual display platform. First of all, this paper divides the registration into two processes: camera calibration and joint calibration of the camera and laser scanner based on the calibration results. Camera calibration can determine the plane model of the calibration board in the camera coordinate system, and the joint calibration uses the RANSAC algorithm to extract the point cloud of the plane model of the calibration board, and then optimizes the distance between the points in the plane model point cloud and the corresponding plane in the camera coordinate system Find the optimal transformation between the two sets of data, and then calculate the registration relationship between the point cloud and the image. Secondly, this article conducts a demand analysis of the film and television industry cloud exhibition platform based on virtual reality technology, including the business goals set by the platform, platform system analysis, overall design, and system operating environment and configuration requirements. This model provides a feasible solution for the visual interaction of the cloud exhibition design of the film and television industry.     

一种基于特征点匹配的图像拼接方法研究

针对图像间因具有旋转及光线强度差异等现象而导致的拼接效果不佳及拼接速度慢的问题,提出一种基于特征点的配准算法;在特征点提取阶段,尺度不变的特征变换方法 (SIFT)具有对图像尺度缩放、旋转、放射变换以及亮度变化保持不变的优点,文章采用了改进的SIFT特征点提取算法;在特征点匹配阶段,采用改进的RANSAC算法对特征点匹配对提纯;最后用加权平均法实现拼接图像的融合;实验证明,该算法有效提高了图像拼接的效率和准确性,拼接精度可以达到亚像素级。     

多尺度空间特征提取的脊柱图像拼接算法

针对脊柱图像视野有限,提出一种基于优化MSFE的脊柱图像自动拼接算法。设计出一种基于尺度因子变化的高斯卷积模板尺寸自适应调整以及双向配对办法;相似性度量采用城市距离;利用RANSAC算法去除错配,从而确定待拼接图像之间的变换参数,最后利用加权平均对图像融合。对实际取得的多幅脊柱图像拼接结果表明该算法具有很好的实时性和鲁棒性。     

可控特征点对以及RANSAC的监视系统外参估算方法

为了提高基于机器视觉的监控系统的精度,立体视觉信息作为一种鲁棒性很高的参数被引入监控算法中.立体视觉信息的引入使得外参求解成为影响监控结果的一个重要环节.现存的应用于监视系统的外参自动估算方法均采用立体视觉中外参求解的方法.这些方法普遍存在特征点的数目完全由场景决定特点.为了解决在大部分监视系统应用的场景中,因为背景较为空旷、基线较长同时相机对之间的旋转量较大,由场景提供的特征点数量非常有限,导致计算结果并不理想这一问题,提出了一种基于视频序列的RANSAC外参求解方法.该方法不仅利用RANSAC算法有效的剔除外点,而且根据可控特征点对的动态性,利用时间上的积累获得了充足的位置可控、数量可控的可控特征点对,并据此得到精度较高的外参结果.根据实验,该方法可以将三维重建误差降低近50%.     

基于K-means聚类和RANSAC的图像配准算法研究

针对图像配准中特征点匹配方法存在实时性不高和精度低的问题,提出了一种基于K means聚类和RANSAC的图像配准算法。该算法根据匹配点对距离和方向特征的视差约束条件,首先利用K means聚类对匹配点对进行预处理,剔除大部分错误匹配点,然后利用RANSAC进行二次优化,实现了图像的快速和精确配准。实验结果表明,该算法不仅提高了图像配准的精确度,而且提高了图像配准的速度。     

一种基于分块匹配的SIFT算法

SIFT算法在图像处理领域具有独特的优势,但是经过不断发展,SIFT算法在特征匹配过程中仍然具有数据处理量大、计算速度慢的问题.基于这些问题,提出了一种基于分块匹配的新型SIFT匹配算法,它通过剔除非重叠区域来降低特征提取和匹配的时间损耗.对于图像的刚性变换,算法的核心在于图像块的切分和重叠区域的计算,首先选取少量的种子点来估算两幅图像的相关变换矩阵;然后将原始图像切分为几块,通过变换矩阵找出在匹配图中的相关块;再检测所有的匹配块上的特征点;最后结合RANSAC算法去除伪匹配点对,来提高匹配的准确率.实验结果表明:与标准SIFT算法相比,基于分块匹配的SIFT算法在实时性和鲁棒性方面得到了进一步的提升,在实际图像匹配中具有一定的应用价值.     

一种新型遥感图像配准方法

提出了一种新型全自动稳健的遥感图像配准算法。首先,在图像二维平面空间和尺度空间中同时检测局部极值作为特征点,并在特征点邻域提取局部不变特征描述子一尺度不变特征变换（SIFT）。然后,利用距离测度进行SIFT特征匹配得到初步的匹配集合。最后,运用稳健的随机采样一致性（RANSAC）算法将匹配点集划分为内点和外点,在内点域上精确地估计出图像变换模型。实验利用仿真数据测试了SIFT特征的可重复性和可匹配性,利用卫星图像验证了该自动配准算法的有效性和稳健性。     

Log-polar height maps for multiple range image registration

We propose a method for coarse registration of multiple range images that uses a log-polar height map (LPHM) as the key for establishing correspondence. The LPHM is a local height map orthogonally mapped on the tangent plane with the log-polar coordinate system. The input range images are roughly represented by signed distance field (SDF) samples. For each SDF sample, an LPHM is generated and is converted to an invariant feature vector. Point correspondence is established by a nearest neighbor search in feature space. The RANSAC algorithm is applied on the corresponding point pairs between each pair of range images, and the pairwise registration of input range images is determined by the extracted inlier point pairs. Finally, the global registration is determined by constructing a view tree, which is the spanning tree that maximizes the total number of inlier point pairs. The result of coarse registration is used as the initial state of the fine registration and modeling. The proposed method was tested on multiple real range image datasets.     

一种新的基于条件数的图像配准算法

提出了一种新的基于条件数的图像配准算法。该方法在Harris算法提取角点的基础上,采用条件数定量地分析了噪声对确定图像间变换关系的影响程度,通过阈值设定筛选出具有良好稳定性的角点,克服了Harris角点检测可能存在的角点位置偏移和易受噪而提取出伪角点等问题。最后选择了Random Sample Consensus(RANSAC)匹配准则来确定匹配点对。经过实验证明了该配准算法具有精确性、抗噪性和鲁棒性。     

基于SR-SURF的岩石显微图像拼接

岩石显微图像拼接是对岩石分析和研究的关键环节, 由于岩石显微图像数量多(成百上千张)内容丰富并且包含大量相似易混淆区域, 导致拼接速率和配准准确率低, 并且多幅图像拼接时会产生误差累积导致拼接错位, 针对此问题提出了一种SR-SURF (similar region-SURF)的岩石显微图像拼接方法. 首先选用哈希指纹快速提取相似区域(similar region), 然后在此区域检测特征点; 之后利用改进的RANSAC (random sample consensus)算法剔除错误匹配点; 再然后选用最佳模板匹配纠正错误配准图像; 最后引入最小二乘法消除单应性矩阵相乘产生的累计误差; 实验结果显示本文的算法消除了多幅图像拼接产生的累计误差, 解决了拼接错位问题, 提高了拼接速率和配准准确率, 具有较高的实用价值, 推动了岩石薄片的数字化存储进程.