光栅式双目立体视觉传感器的立体匹配方法

光栅式双目立体视觉传感器的难点之一在于立体匹配问题,为此,提出了一种基于极线约束和空间点最小距离搜索的立体匹配方法.该方法将光栅式双目立体视觉传感器看作两个光栅结构光传感器,分别标定后可测定光条中心点关于某个结构光模型的三维坐标,若两点匹配,则其三维坐标间的距离理论上为零.引入极线约束,在左摄像机成像光条上找一个特征点,在右摄像机所成像中便可计算出一条极线与之对应,在极线与各光条中心的交点中寻找匹配点.该方法在三维空间进行匹配,计算量小,能够实现点与点的唯一匹配.仿真实验表明了该方法的有效性.     

Stereo object tracking with fusion of texture,color and disparity information

A novel method for visual object tracking in stereo videos is proposed, which fuses an appearance based representation of the object based on Local Steering Kernel features and 2D color–disparity histogram information. The algorithm employs Kalman filtering for object position prediction and a sampling technique for selecting the candidate object regions of interest in the left and right channels. Disparity information is exploited, for matching corresponding regions in the left and right video frames. As tracking evolves, any significant changes in object appearance due to scale, rotation, or deformation are identified and embodied in the object model. The object appearance changes are identified simultaneously in the left and right channel video frames, ensuring correct 3D representation of the resulting bounding box in a 3D display monitor. The proposed framework performs stereo object tracking and it is suitable for application in 3D movies, 3D TV content and 3D video content captured by consuming stereo cameras. Experimental results proved the effectiveness of the proposed method in tracking objects under geometrical transformations, zooming and partial occlusion, as well as in tracking slowly deforming articulated 3D objects in stereo video.     

基于图像绘制技术的红外场景模拟

红外场景模拟可为目标识别、跟踪提供必要的图像样本,对算法的训练、评估和可靠性检验具有十分重要的意义,基于建模的红外模拟方法不一定反映场景的客观情况,并且,计算量大、耗时,难于模拟出有真实感的红外图像。基于图像绘制技术,提出无需建模的基于图像的绘制方法来模拟红外场景图像,根据红外图像的特点,给出了计算基本矩阵的非线性迭代算法和基于特征约束的动态规划立体匹配算法。由于参考图集是实际图像,因此,模拟图像更符合景物的真实情况,并且,该方法无需很复杂的建模过程,利于实时模拟。实验结果表明,该方法可有效地模拟出真实感的红外图像。     

An improved augmented reality system based on AndAR

AndAR is a project applied to develop Mobile Augmented Reality (MAR) applications on the android platform. The existing registration technologies of AndAR are still base on markers assume that all frames from all videos contain the target objects. With the need of practical application, the registration based on natural features is more popular, but the major limitation of the registration is that many of them are based on low-level visual features. This paper improves AndAR by introducing the planar natural features. The key of registration based on planar natural features is to get the homography matrix which can be calculated with more than 4 pairs of matching feature points, so a 3D registration method based on ORB and optical flow is proposed in this paper. ORB is used for feature point matching and RANSAC is used to choose good matches, called inliers, from all the matches. When the ratio of inliers is more than 50% in some video frame, inliers tracking based on optical flow is used to calculate the homography matrix in the latter frames and when the number of inliers successfully tracked is less than 4, then it goes back to ORB feature point matching again. The result shows that the improved AndAR can augment not only reality based on markers but also reality based on planar natural features in near real time and the hybrid approach can not only improve speed but also extend the usable tracking range.     

基于局部特征匹配的目标跟踪研究

针对目标跟踪中的特征提取和匹配问题进行分析,提出了一种基于局部特征匹配的目标跟踪方法,该算法基于Shape Context进行特征提取。首先,对现有特征提取算法进行简单介绍,并详细介绍Shape Context的基本思想,基于此提出基于局部特征的跟踪算法。其次,详细阐述了目标跟踪算法：采用目标点的χ2-test直方图距...     

针对间断纹理环境中的图像特征追踪和匹配算法研究

针对同时定位与地图构建(SLAM)中的特征匹配关键环节,提出一种融合特征点和特征区域的图像追踪与匹配算法,以解决交替出现纹理丰富和纹理缺失的间断纹理环境中图像特征易丢失、误匹配率较高的问题。首先,利用ORB算法和半稠密直接法分别对图像提取特征点和特征区域。其次,使用渐进一致采样法(PROSAC)剔除ORB算法的误匹配特征点,并计算特征点的正确匹配率。最后,针对纹理缺失环境中特征点丢失严重的问题,以特征点的正确匹配率作为判断依据,对低匹配率图像,则基于特征区域使用半稠密直接法实现图像的追踪,同时对追踪结果进行非线性优化,提高了特征区域追踪的准确性和稳定性。实验结果表明,该算法适用于间断纹理环境,在纹理丰富和纹理缺失条件下均可提高图像匹配的准确率。     

基于动态目标结构特征的姿态实时定位方法

针对动态目标的三维姿态不断变化，研究了在单站跟踪模式下，如何利用光测手段快速准确地对飞行目标的姿态进行实时定位的问题。在对目标结构有一定先验知识的前提下，提出了一种基于动态目标结构特征的姿态实时定位方法。方法在跟踪闭环的基础上，对光电摄像机实时采集的目标图像进行二维特征提取，并将此二维特征与目标自身的三维结构特征相对应，通过解算对应的数学关系模型，实现对动态目标姿态的实时定位。通过3 dmax建立场景，模拟飞机的动态飞行过程，开展了仿真实验。方法对动态飞机目标姿态定位准确，且每帧定位所需时间不大于0.02 s，处理频率达到50 Hz，满足了实时性需求。结果表明，该方法对动态目标的姿态实时定位上具有一定的有效性。     

基于摄影测量和ERA改进算法的叶片模态辨识方法

在风力机叶片表面排列编码目标,基于双目立体成像原理和图像特征匹配与跟踪方法,可以动态、实时地获得编码目标的空间运动信息。针对噪声污染影响模态辨识的问题,通过奇异值分解(SVD)和Cadzow算法构造了无噪声污染的Hankel矩阵,有效减少由噪声引起的虚假模态。针对模态定阶过程容易出现虚假模态的问题,提出一种改进的特征系统实现算法(ERA)。相比于传统的ERA模态辨识方法,该方法在固有频率的识别上提高了3.6%的精度,获取了更清晰的稳定图。     

基于特征的扫描电镜立体对三维重建

应用扫描电子显微镜地成像技术和图像处理，计算机视不方法建立了一套微结构形貌三维自动重建系统。在Ｂａｒｎａｒｄ算法基础上根据ＳＥＭ立体对成像的特点提出了一种基于边界特征和对应占匹配概论松弛迭代方法。     

基于特征点匹配和广义Hough变换的扩展目标跟踪方法

针对扩展目标在跟踪过程中存在的因旋转、尺度变化和目标部分区域离开视场时引起的漂移等问题,提出了一种在特征点匹配的基础上结合广义Hough变换的扩展目标跟踪方法.采用ORB特征处理相邻两帧图像,得到初始匹配特征点,然后再用随机采样一致处理筛选出匹配正确率高的特征点作为基础特征点,利用这些基础特征点进行广义Hough变换,提取出一个相对位置固定的跟踪点对目标进行跟踪.实验表明,该方法具有能保持跟踪点的相对位置固定的特性.     

Adaptive multi-modal stereo people tracking without background modelling

Detecting and tracking persons in the sequences of monocular images are the important and difficult problems in computer vision and have been well studied in these two decades. Recently, the methods based on stereo vision have attracted great attentions since 3D information can be exploited. This paper presents an approach for multiple-people detection and tracking using stereo vision. Tracking is carried out using a multiple particle filtering approach that combines depth, colour and gradient information. We modify the degree of confidence assigned to depth information, according to the amount of it found in the disparity map, using a novel confidence measure. The greater the amount of disparity information found, the higher the degree of confidence assigned to depth information in the final particles weights is. In the worst case (total absence of disparity), the proposed algorithm makes use of the information available (colour and gradient) to track, thus performing as a pure colour-based tracking algorithm. People are detected combining an adaboost classifier with stereo information. In order to test the validity of our proposal, it is evaluated in several sequences of colour and disparity images where people interact in complex situations: walk at different distances, shake hands, cross their paths, jump, run, embrace each other and even swap their positions quickly trying to confuse the system. The experimental results show that the proposal is able to deal with occlusions and to effectively determine both the 3D position of the people being tracked and their 2D head locations in the camera image, and everything is realized in real time. Besides, as the proposed method does not require the use of a background model, it can be considered particularly appropriate for applications that must run on mobile devices.     

基于分块SURF特征提取的图像目标跟踪算法

由于基于特征的目标跟踪需要对前后两帧图像中的目标进行特征匹配,而传统的基于SURF(speeded up robust features)特征的匹配算法存在匹配时间较长,无法满足目标跟踪条件下实时性要求的情况。本文针对此缺点对SURF特征提取提出了具体的分块并行的解决方案,其中包括自适应地设置分块重叠区域,去除冗余特征点和距离门限法去除离散点的处理;同时通过模板的实时更新以及自适应的抗遮挡处理,保证了短时抗遮挡性能。并通过实验,将传统的基于SURF特征的跟踪算法与本文算法在相同条件下进行跟踪误差和运行时间对比;实验表明针对视频中的待跟踪目标,本文算法较基于传统SURF的图像跟踪算法在降低跟踪运行时间的同时保证了跟踪准确度。并通过遮挡实验,说明抗遮挡处理在本文算法中的实用性和必要性。     

基于图像尺度变化的一种特征点匹配算法

通过对灰度相关法特征点匹配算法的理论研究和实验分析,提出了一种能够克服图像尺度变化的特征点匹配算法。该算法主要根据图像特征点间欧氏距离的关系,结合传统的特征点灰度相关法和特征点的梯度相关法进行精确匹配。实验证明,该算法容易理解,易于实现,匹配结果较精确,误匹配点较少。     

基于散斑立体匹配的快速三维人脸重建

本文提出一种高效的人脸三维重建方法。该方法将 散斑投影至人脸表面以增加其特征信息,并采用一种由粗到精的时空立体匹配算法来提高三 维人脸重建的精度。进一步,该算法利用 时空积分图对立体匹配的代价函数进行加速计算,进而提高了重建效率。此外,所提出方法 通过人脸检测 去除无关背景,使后续的三维重建算法能够高效地作用在人脸区域上。实验表明,所提出方 法对3D打印人 脸(精度为0.01 mm)模型的重建平均误差为0.32 mm,对哑铃规球心测距和直径测距(精度皆为0.01 mm)其 误差皆低于1个百分点,以上结果优于同类产品。与现有立体匹配算法相比,本文方法所得 视差图面部无 空洞且视差变化均匀,更真实地反映出被测人脸的三维形状。     

基于压缩特征的鱼眼视频目标跟踪算法研究

该文针对畸变严重的鱼眼图像中的目标跟踪,提出一种能适应尺度变化、姿态变化以及形状畸变的鱼眼视频目标跟踪的方法。该方法首先将灰度特征和相对梯度特征相结合得到目标的高维特征,然后对其平均降维得到目标的压缩特征。并根据鱼眼成像模型得到投影点的运动特性,确定目标的运动范围。为了适应尺度变化,在块匹配运动估计思想的基础上,对目标跟踪框的顶点分别进行由粗到精的定位,并在此过程中根据跟踪框的尺度相应改变压缩特征的尺度。实验结果表明:该算法在目标畸变、尺度变化、姿态变化以及局部遮挡等情况下,判断指标均优于其他对比算法。     

近红外导航术中器械定位的立体匹配

为确定近红外导航术中手术器械的空间位置,利用近红外双目视觉系统拍摄发光点的左右图像提取其亚像素坐标,根据系统的内外部参数求取发光点在系统坐标系下的光线方程。空间同一发光点的两条光线相交,且由此得到的发光点坐标满足手术器械上发光点间的距离关系,从而实现对不同位置发光点的正确匹配。5个手术器械上15个发光点的匹配实验表明,本文方法可自动匹配手术器械的发光点,能用于术中定位、跟踪手术器械,可为手术导航提供定位支持。     

面向室内动态场景的VSLAM

传统VSLAM算法基于静态场景实现,其在室内动态场景下定位精度退化,三维稀疏点云地图也会出现动态特征点误匹配等问题.文中在ORB-SLAM2框架上进行改进,结合Mask R-CNN进行图像的语义分割,剔除位于动态物体上的动态特征点,优化了相机位姿,得到了静态的三维稀疏点云地图.在公开的TUM数据集上的实验结果表明,结合...     

远距离运动目标三维测量中图像匹配的研究

采用两个摄像机光轴平行的双目立体视觉测量系统,检测远距离运动物体的三维物体轮廓.阐述了该三维轮廓测量系统中的两个关键技术:提取出合适的图像特征;建立特征间的对应关系.将同一空间物理点在不同图像中的映象点对应起来,由此得到相应的视差图像,实现立体匹配,恢复出物体的三维轮廓.仿真实验结果表明,该三维轮廓测量方法容易实现、对硬件要求不高、精度较高和具有较高稳定性,能够满足远距离运动物体姿态和速度测量的要求.     

Real-time Stereo Face Recognition by Fusing Appearance and Depth Fisherfaces

Reported 3D face recognition techniques assume the use of active 3D measurement for 3D facial capture. However, active method employ structured illumination (structure projection, phase shift, gray-code demodulation, etc) or laser scanning, which is not desirable in many applications. A major problem of using passive stereo is its lower 3D face resolution and thus no passive method for 3D face recognition has been reported. In this paper, a real-time passive stereo face recognition system is presented. Entire face detection, tracking, pose estimation and face recognition are investigated. We used SRI Stereo engine that outputs sub-pixel disparity automatically. An investigation is carried out in combining 3D and 2D information for face recognition. The straightforward two-stage principal component analysis plus linear discriminant analysis is carried out in appearance and depth face images respectively. A probe face is identified using sum of the weighted appearance and depth linear discriminant distances. We investigate the complete range of linear combinations to reveal the interplay between these two paradigms. The improvement of the face recognition rate using this combination is verified. The recognition rate by the combination is higher than that of either appearance alone or depth alone. We then discuss the implementation of the algorithm on a stereo vision system. A hybrid face and facial features detection/tracking approach is proposed which collects near-frontal views for face recognition. Our face detection/tracking approach automatically initializes without user intervention and can be re-initialized automatically if the tracking of the 3D face pose is lost. The experiments include two parts. Firstly, the performance of the proposed algorithm is verified on XM2VTS database; Secondly, the algorithm is demonstrated on a real-time stereo vision system. It is able to detect, track and recognize a person while walking toward a stereo camera.

一种优化的特征点匹配算法

为提高三维重建的性能,提出一种优化特征点匹配算法.首先,通过组合算法对特征点进行初匹配;其次,通过随机抽样一致算法剔除误匹配获得目标的精确匹配点,并将精确匹配点通过区域生长算法,经多次迭代实现稠密匹配;最后,经过二次剔除误匹配点得到精确稠密匹配结果.同时,搜索窗的大小通过局部二值模式来自适应调整,提高区域生长后新增种子点的精度,从而更有利于三维重建.实验证明该方法能提高匹配效率和精度.