基于红外光学原理的便携式甲烷报警仪

提出了基于红外光学原理的便携式甲烷报警仪的设计方案,详细介绍了报警仪的硬件电路设计、软件设计、光学气室结构、外形结构设计及标定技术。该报警仪采用红外光源、高精度干涉滤光片一体化热释电探测器和单光束双波长技术,配合镀金膜气室实现对CH4等气体的实时检测,具有不易老化、响应快、灵敏度好、性能稳定、抗干扰能力强等优点。     

基于CCD的垂线坐标仪的设计

针对矿井井壁变形引起的径向位移测量问题,提出了一种基于CCD的垂线坐标仪的设计方案,给出了垂线坐标仪的结构及其在井壁变形监测系统中的布置,详细介绍了垂线坐标仪的软、硬件设计。该垂线坐标仪利用CCD采集光信号并将其转换为视频信号,采用LPC932对采集的视频信号进行二值化处理及计数,并将处理结果发送至地面计算机进行分析,从而得到矿井井壁变形引起的径向位移量。测试结果验证了该垂线坐标仪的稳定性和精确性。     

便携式安全阀在线校验仪的研制

目前,安全阀在线校验系统普遍存在精度低、安全性和便携性差等缺点.提出了以STC12C5A单片机为核心,基于阀瓣微动技术的便携式安全阀自动校验仪的设计方案,并完成了对该压力校准系统的研制.工程应用表明,该仪器具有精度高、功耗低等特点,能实现数据共享,操作灵活,易于携带,在行业中具有很高的推广价值.     

基于PhotoModeler Scanner的普通数码相机快速检校研究

随着分辨率的不断提高与价格的日益降低,数码相机已成为近景摄影测量的基本设备,而相机的准确检校是保证量测精度的关键因素.借助于PhotoModeler Scanner软件,本文实现了相机的快速准确检校,并对野外检校的稳定性和质量进行了分析,说明该检校方法简便可靠.     

基于转台的线阵激光雷达地面检校方法研究

介绍了一种基于转台的线阵激光雷达地面检校方法,该方法通过布设物方检校控制场,使用指示激光器建立激光测距值与物方控制点之间的对应关系并引入激光测距的加/乘常数与外方位元素一并作为检校参数,通过坐标转换列出误差方程式;最后使用最小二乘平差解算所有的检校参数。文中给出了实测数据的实验结果分析及精度评定,验证了本文方法的可行性。     

光谱响应差异对高精度交叉定标的影响——以FY-3A/MERSI与EOS/MODIS为研究实例

分析了MERSI与MODIS间光谱响应差异对测量表观反射比的影响。正演模拟结果显示,在极区冰雪情况下,MERSI与MODIS测量得到的表观反射比之间的相对差异是关于MODIS所测表观发射比的二次函数。MERSI的前4个通道与对应的MODIS通道之间的相对差异在0~0.8%,0~2%,0.5%~2.5%,-1.8%~-0.8%之间。将正演模拟得到的对光谱响应差异的修正关系应用到具体的SNO测量后,MERSI前3个通道的表观反射比与修正后MODIS的表观反射比之间的相对差异减小到了3%以内。MERSI的1、2通道在红外波段也有响应,这部分响应在极区冰雪条件下对表观反射率的影响在0.5%左右,基本可以忽略。     

SELM: Semi-supervised ELM with application in sparse calibrated location estimation

Indoor location estimation based on Wi-Fi has attracted more and more attention from both research and industry fields. It brings two significant challenges. One is requiring a vast amount of labeled calibration data. The other is real-time training and testing for location estimation task. Traditional machine learning methods cannot get high performance in both aspects. This paper proposed a novel semi-supervised learning method SELM (semi-supervised extreme learning machine) and applied it to sparse calibrated location estimation. There are two advantages of the proposed SELM. First, it employs graph Laplacian regularization to import large number of unlabeled samples which can dramatically reduce labeled calibration samples. Second, it inherits the good property of ELM on extreme training and testing speed. Comparative experiments show that with same number of labeled samples, our method outperforms original ELM and back propagation (BP) network, especially in the case that the calibration data is very sparse.     

Multi-sensor calibration through iterative registration and fusion

In this paper, a new multi-sensor calibration approach, called iterative registration and fusion (IRF), is presented. The key idea of this approach is to use surfaces reconstructed from multiple point clouds to enhance the registration accuracy and robustness. It calibrates the relative position and orientation of the spatial coordinate systems among multiple sensors by iteratively registering the discrete 3D sensor data against an evolving reconstructed B-spline surface, which results from the Kalman filter-based multi-sensor data fusion. Upon each registration, the sensor data gets closer to the surface. Upon fusing the newly registered sensor data with the surface, the updated surface represents the sensor data more accurately. We prove that such an iterative registration and fusion process is guaranteed to converge. We further demonstrate in experiments that the IRF can result in more accurate and more stable calibration than many classical point cloud registration methods.     

Shape Reconstruction and Camera Self-Calibration Using Cast Shadows and Scene Geometries

Recently, various techniques of shape reconstruction using cast shadows have been proposed. These techniques have the advantage that they can be applied to various scenes, including outdoor scenes, without using special devices. Previously proposed techniques usually require calibration of camera parameters and light source positions, and such calibration processes limit the range of application of these techniques. In this paper, we propose a method to reconstruct 3D scenes even when the camera parameters or light source positions are unknown. The technique first recovers the shape with 4-DOF indeterminacy using coplanarities obtained by cast shadows of straight edges or visible planes in a scene, and then upgrades the shape using metric constraints obtained from the geometrical constraints in the scene. In order to circumvent the need for calibrations and special devices, we propose both linear and nonlinear methods in this paper. Experiments using simulated and real images verified the effectiveness of this technique.     

基于校准靶的C形臂相机模型自动校准方法

根据校准靶标志点影像的特点,提出一种自动的离线C形臂相机模型校准方法。应用聚类算法实现标志点信息的自动识别,通过行列索引表简化标志点网格姿态的识别,自动建立标志点在影像坐标系和空间坐标系下坐标的对应关系,经几何变形校正后,实现C形臂相机的校准。实验数据证明,该方法具有良好的鲁棒性,误差小于1 mm,可应用于基于术中C形臂X线影像的手术导航系统。