3D Motion Estimation and Motion Fusion by Affine Region Matching

In this paper,a new method is presented for 3D motion estimation by image region correspondences using stereo cameras.Under the weak perspectivity assumption.we first employ the moment tensor theory (Cyganski and Orr^[11]) to compute the monocular affine transformations relating images taken by the same camera at different time instants and the binocular affine transformations relating images taken by different cameras at the same time instant.We then show that 3D motion can be recovered from these 2D transformations.A space-time fusion strategy is proposed to aim at robust results.No knowledge of point correspondences if requred in the above processes and the computations involved are linear.To find corresponding image regions,new affine invariants,which show stronger invariance,are derived in term of tensor contraction theory.Experiments on real motion images are conducted to verify the proposed method.     

The visual control of reaching and grasping: Binocular disparity and motion parallax.

The primary visual sources of depth and size information are binocular cues and motion parallax. Here, the authors determine the efficacy of these cues to control prehension by presenting them in isolation from other visual cues. When only binocular cues were available, reaches showed normal scaling of the transport and grasp components with object distance and size. However, when only motion parallax was available, only the transpont component scaled reliably. No additional increase in scaling was found when both cues were available simultaneously. Therefore, although equivalent information is available from binocular and motion parallax information, the latter may be of relatively limited use for the control of the grasp. Binocular disparity appears selectively important for the control of the grasp. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于损失自注意力机制的立体匹配算法研究

针对现有的立体匹配算法在阴影、物体边缘和光照反射等区域匹配困难且存在大量错误结果的问题,设计了一种可拆卸的损失自注意力网络（loss self-attention net,LSAnet）查找图像中的匹配困难区域。LSAnet的网络各层相互稠密连接,应用了空洞卷积来扩大感受野,并以立体匹配算法生成的损失分布为标签,能够动态地进行有监督训练,最终生成匹配困难区域掩膜辅助立体匹配网络进行更好的优化;同时,改进了立体匹配网络中经典的特征匹配代价卷结构,降低了后续3D卷积的计算负荷,提高了匹配效率。实验结果表明,该算法相比于基准算法精度更高,并且可以提高算法对于匹配困难区域的鲁棒性。     

基于 OpenCV 的双目摄像机标定技术研究

摄像机标定技术作为双目立体视觉领域的一个基础性研究课题,具有很大的理论研究价值和实际应用价值。论文围绕双目立体视觉中的双目摄像机标定技术,分析基于OpenCV的双目摄像机标定的方法。基于OpenCV的双目摄像机标定比传统的定标技术更为灵活,并且具有不错的定标精度。     

Aging and availability of binocular disparity and pictorial depth cues in 3D graphics contents

Some stereoblind observers do not perceive depth of 3D stimuli that depends on binocular disparity. These individuals, who have no disabilities, comprise over 5% of the general population. In addition, 17–30% of nonstereoblind young and young–middle people do not use disparity information in certain 3D environments, a phenomenon known as pseudo‐stereoblindness. This study aimed to investigate the relationship between aging and the proportion of pseudo‐stereoblindness in the general population. In an experiment, 134 nonstereoblind participants, ranging in age from 17 to 83 years, judged subjective depth of 3D stimuli containing binocular disparity and pictorial depth cues. Results showed that the proportion of pseudo‐stereoblindness among young (17–24 years old) and young–middle aged observers (25–39 years old) was 29%, in both cases. However, the proportion of pseudo‐stereoblind observers increased in older populations: 65% and 82% in the middle (40–54 years old) and senior (55–83 years old) age groups, respectively. These results suggest that a number of people, especially in elderly populations, have trouble perceiving depth from binocular disparity in 3D graphic contents despite their essential ability to use disparity information.     

基于SIFT特征点的双目视觉定位

提出了一种结合了SIFF特征点的双目立体视觉定位方法.介绍了对尺度、旋转、视角等变化具有良好鲁棒性的SIFT特征向量,利用SIFT特征向量匹配算法在双目视觉系统采集的左、右图片中分别检测目标、获取匹配的目标SIFT特征点.经过空间匹配点选择、标定点坐标计算等步骤获取左、右图片中具有空间位置一致性的目标标定点,并在摄像机坐标系中恢复目标标定点三维信息.实验结果表明,利用该方法进行目标定位具有较强的适应性.有一定的实用价值.     

双目视差测距望远光学系统设计

双目视差测距望远镜主要应用于对动态目标的测量,特别是飞机飞行距离的测量。双目视差测距望远系统,不对外发射信号,属于被动式测距仪,因此具有被动接收式和非接触式的特点,可测量500~5000m大范围距离。主要探讨了双目视差望远系统的主要光学原理,并利用Zemax光学设计软件对双目视差望远光学系统进行设计与优化,并对本光学系统进行了误差分析。使用CMOS自动调焦技术,提高了双目望远镜的成像质量。双目视差测距望远系统的测距理论误差在0.91%以下,满足测距理论误差小于1%的要求。     

双球面投影几何可量测全景模型的构建

针对全景影像难以提供空间度量的问题,提出一种基于双球面投影几何的可量测立体全景模型构建方法.该方法依据球面全景投影关系与多视几何原理,采用对应变换与本质变换求取旋转及平移参数,并推导出双球面核线约束;在此基础上,建立起双球面投影几何的立体全景模型,解决了球面全景的量测问题.实验结果表明,文中方法可使全景影像在真实呈现户外场景的同时,提供满足一定应用需求的量测分析功能.     

基于双目视觉测距技术的导弹筒箱精确对接方法

当前导弹筒箱对接工作中普遍采用人工操作方法,通过目视指挥操作实现卡口对接,精确性差,步骤繁琐,效率低下。针对此问题,基于双目视觉测量技术提出了一种自动对接方法,利用双摄像头测量对接卡口的成像偏差,计算筒弹调整的距离和角度,实现筒弹支脚和对接卡口的准确对准。然后研究了系统测量误差,利用非线性回归拟合方法分析了误差计算公式,利用等距标尺设计了测量误差标定实验方案,并针对摄像头安装不便的问题,给出了中点延长安装方法和计算补偿方法,最后设计了筒弹自动化对接系统的基本结构。试验结果表明,该方法能够有效获取筒弹对接偏差距离和角度,为位置调整系统提供有效输入,从而实现导弹筒箱的自动对接。     

基于双目视觉的机器人目标定位与机械臂控制

为了更好地与复杂多变的非结构化环境进行交互,完成对目标物体的识别和抓取,提出了一种应用于服务机器人平台的基于双目视觉的仿人机械臂控制方法.文中首先用D-H方法对机械臂进行建模,并对这个模型做了改进,给出了一种更加简便的3+1自由度仿人机械臂的逆解算法,采用基于双目视觉与颜色分割的目标识别方法;然后根据识别出的目标三维坐标信息控制机械臂完成抓取任务;最后,本方法在家庭服务机器人上得到了验证,机器人能够完成对目标物体的识别和抓取动作.