基于HEIV模型的摄像机一维标定

多摄像机系统广泛应用于文化创意产业,其高精度标定是迫切需要解决的一个关键问题. 新近出现的摄像机一维标定方法能够克服标定物自身遮挡,特别适合标定多摄像机系统. 然而,现有的摄像机一维标定研究主要集中在降低一维标定物的运动约束,而标定精度较低的问题未受到应有的关注. 本文提出一种基于变量含异质噪声 （Heteroscedastic error-in-variables,HEIV）模型的高精度摄像机一维标定方法. 首先,推导出摄像机一维标定的计算模型;其次,利用该计算模型详细分析了一维标定中的噪声,得出摄像机一维标定可以视为一个HEIV问题的结论;最后给出了基于HEIV模型的摄像机一维标定算法. 与现有的算法相比,该方法可以显著改善一维标定的精度,并且受初始值影响小,收敛速度快. 实验结果验证了该方法的正确性和可行性.     

基于自由运动一维标定物的多摄像机参数标定方法与实验

一维标定方法易于实现且标定效率高,为了克服现有一维标定方法的一些不足,本文提出一种用一维标定物标定多摄像机内外参数的方法,首先进行两两标定,在此过程中,假定主点坐标近似已知而仅考虑畸变、焦距、旋转和平移等参数,接着利用基本矩阵及一维标定物上特征点之间的几何约束,估计两摄像机的内外参数,两两标定完成后,采用Dijkstra最短路径法和捆绑调整对多摄像机系统进行全局标定(含主点坐标),仿真和真实实验表明本文的方法是切实有效的.     

基于多视角信息融合的棒材识别计数方法

棒材出厂前要按根数打捆,基于单视角视觉识别计数方法难以处理多个目标之间的互遮挡等问题。文章提出多视角信息融合方法,从2个视角分别捕获目标图像,分别识别,再进行融合,对单视角目标识别信息的补偿与纠错,达到消除互遮挡、准确计数的目的。实践证明,该方法能很好地解决单视角的遮挡目标识别问题,对于因存在遮挡和光照条件限制而难以处理的多目标识别和跟踪问题具有一定的普适性。     

分布式环境下的多摄像机标定

针对分布式环境下多摄像机的标定问题,我们提出了一种切实可行的多摄像机标定方法。标定过程仅需要各摄像机拍摄下包含激光点的图像即可。在整个标定过程中利用了所有图像的信息,因此比以往的方法具有更好的鲁棒性。整个标定操作过程方便,易于实现。实验结果表明,该方法是一种有效的多摄像机标定方法。     

M2Tracker: A Multi-View Approach to Segmenting and Tracking People in a Cluttered Scene

When occlusion is minimal, a single camera is generally sufficient to detect and track objects. However, when the density of objects is high, the resulting occlusion and lack of visibility suggests the use of multiple cameras and collaboration between them so that an object is detected using information available from all the cameras in the scene.In this paper, we present a system that is capable of segmenting, detecting and tracking multiple people in a cluttered scene using multiple synchronized surveillance cameras located far from each other. The system is fully automatic, and takes decisions about object detection and tracking using evidence collected from many pairs of cameras. Innovations that help us tackle the problem include a region-based stereo algorithm capable of finding 3D points inside an object knowing only the projections of the object (as a whole) in two views, a segmentation algorithm using bayesian classification and the use of occlusion analysis to combine evidence from different camera pairs.The system has been tested using different densities of people in the scene. This helps us determine the number of cameras required for a particular density of people. Experiments have also been conducted to verify and quantify the efficacy of the occlusion analysis scheme.     

基于多判据的多目视觉手势立体姿态检测系统研究

为了精确识别人手姿态用于机器手控制,文中讨论一种基于计算机视觉的手势立体姿态检测的新方法.该方法利用多目视觉之间的配合,有效地解决了检测识别时手部关键节点互相遮档的关键问题.采用了自适应阈值分割、harris角点检测、外极线约束等几种合理、有效的点的匹配算法,对不同摄像机拍摄到的手部关键节点进行排序,这样不仅解决了特征...     

基于多目摄像机的鲁棒眼动跟踪技术研究

为改进单个远程传感器采集眼动数据时存在视场小、容易被遮挡物遮挡的缺点,研究了一种多目摄像机眼动跟踪技术,以更好地采集眼动数据。应用多个摄像机对人体头部姿态和眼球信息进行采集,通过分割视频帧提取瞳孔图像和计算被测用户头部姿态角度,将瞳孔图像放入卷积神经网络进行训练得到注视点坐标,并基于头部姿态信息计算每个摄像机的注视点权重,从而加权融合得到更精确的注视点信息。研究结果表明：在头部姿态角较大时,多目眼动追踪技术的精度比单目传感器的精度高30%~50%。该技术具有灵活性和通用性,在驾驶舱设计、用户用眼习惯评估和驾驶学员眼动绩效分析中具有重要的应用和推广价值。     

Multi-camera interface with novel copositioning

This article reports a multi-camera system to determine the position of an object. By using novel copositioning and cameras in a wide range of orientations and viewing angles, the system solved the problem of dead zones and camera switching errors. When an object was close to a charge-coupled device camera, the system switched to that camera to become the focus by the algorithm. When an object left the optimum range of one camera, the system selected the next suitable camera to be the main detector. The position of the target and the grey level thresholds were continuously recorded and the changes were calculated. This interface system had the advantages of high positioning accuracy, fast response time, reduced noise in the light field, and no dead zones.     

Electronic speckle pattern interferometry based on spatial fringe analysis method using two cameras

A new speckle measurement method is proposed by applying a spatial phase shifting method to multi-camera technology in order to perform a high resolution, high speed, and large deformation measurement. It is confirmed that the alignment of optical elements in this method is easier than the ordinary multi-camera methods because the optical system uses only two cameras. The validity of principle of the method is discussed by the results of experiments. It is shown that measurement precision of this method is about 1/50 wavelength in a small deformation measurement. Furthermore, the method is improved for a large deformation measurement method by accumulating the results of the small continuous deformation measurement. The optimum sampling process of the large deformation of an object is proposed in order to detect the phase map of the large deformation. It is confirmed that the large deformation can be precisely measured by this method.