3D mapping of underwater caves

Wakulla Springs-a group of deep, underground, water-filled caves south of Tallahassee, FL, USA-is an example where mapping has proved challenging. The Wakulla 2 expedition of the US Deep Caving Team Inc. had one primary goal-to automatically build the first fully 3D cave map. To make the map, divers had to survive the hostile environment. The divers' attention mostly focuses on staying alive, so the more automatic the surveying, the better. The critical piece of equipment for the Wakulla 2 expedition was the Digital Wall Mapper (DWM). The device was designed specifically for the project to gather survey data to make the 3D map. 32 sonar transducers were spirally arrayed around the nose of the 2-m long, 150-kg instrument. Thus, four times a second, the DWM sends and receives 32 equally spaced radial readings. The distance to the walls was important but not useful unless we knew the DWM's exact position and orientation. To record this information, we used an inertial measurement unit (IMU), which is located in the center of the DWM     

水下便携式三维声纳实时成像系统设计

针对传统三维声纳装置体积庞大、设备沉重,在水下难以灵活作业的问题,设计了水下便携式三维声纳实时成像系统。通过现场可编程门阵列（ FPGA）控制多路信号同步采样,优化波束形成算法大幅提高声纳信号处理速度,同时采用基于低功耗的数字媒体处理器以并行处理方式实时完成三维建模和图像显示。实验结果表明：系统续航时间可达4 h,水下零重量,可在40 m范围内实现角度分辨率1.2°的三维成像,图像刷新率可达25帧/s。     

基于公共特征点的三维测量数据拼接方法

针对大型物体和回转体的三维形貌视觉测量,提出了一种基于公共特征点的三维数据拼接方法.该方法首先把测量对象的表面划分成若干个子区域,并且确保相邻的子区域含有重合区域,然后采用一套双目立体视觉测量系统对各个子区域进行单独测量,利用重合区域的公共特征点计算前后两次测量的空间变换矩阵,将三维点坐标转换到一个坐标系下完成拼接.变换矩阵的计算引入了Rodrigues参数,简化了运算过程,且具有较高的精度.该方法操作简单,非常适合于实际应用,实验结果证明了此方法的有效性.     

3D PEE mapping based reversible data hiding for color images

Multimedia Tools and Applications - The performance of prediction-error expansion (PEE) for reversible data hiding (RDH) is excellent. 2D and 3D PEE has a great improvement than the conventional...     

结合图像特征的多视拼接数据的消冗处理

在不丢失非重叠区域数据的情况下, 对多视拼接重合区域的三维点云数据进行消冗处理是三维拼接中的一个难题。针对这一难题, 提出了一种结合二维图像信息查找和消除冗余数据的新方法。算法首先查找位于拼接重叠区域的三维点云数据, 结合三维点的K近邻约束和对应像素特征描述的相似度, 对重叠区域的点云数据进行冗余查找和消除。实验表明, 该方法能够准确判断并消除冗余点, 没有造成更改或丢失非重叠区域三维数据点的不良效果, 消冗速度也有所提高。     

Numerical differentiation of 2D functions from noisy data

In this paper, we present a method for the numerical differentiation of bivariate functions when a set of noisy data is given. We suppose we have a sample coming from an independent process with unknown covariance matrix.We construct the gradient estimator using a multiresolution analysis and the usual difference operators. The asymptotic properties of the estimator are studied and convergence results are provided. The method is suitable for any data configuration.     

基于分层策略的三维非刚性模型配准算法

在三维非刚性模型分析中,通常需要对不同姿态下的模型进行配准。针对传统配准算法存在复杂度高、计算量大、精确度低等问题,提出一种新的基于分层策略的三维非刚性模型配准算法。首先,定义热核签名函数为模型的标量域,使用同源聚类算法提取模型的特征点和特征区域,进而提出三维几何模型的树形表示方法:它的根节点为三维几何模型,内部节点为模型的特征区域,叶节点为包含在相应区域的特征点。然后,根据三维几何模型的树形表示提出模型的分层配准算法。在SHREC 2010模型配准数据集上对比分析了分层配准算法、推广的多维尺度变换算法（GMDS）和博弈论方法在等距变换、孔洞、小孔洞、尺度变换、局部尺度变换、重采样、噪声、散粒噪声以及拓扑变换等情况下的性能。实验结果表明,在以上三维几何模型数据受干扰的情况下,分层配准算法的准确性明显优于GMDS方法和博弈论方法,同时具有较低的计算复杂度。     

Multi-contour initial pose estimation for 3D registration

Reliable manipulation of everyday household objects is essential to the success of service robots. In order to accurately manipulate these objects, robots need to know objects’ full 6-DOF pose, which is challenging due to sensor noise, clutters, and occlusions. In this paper, we present a new approach for effectively guessing the object pose given an observation of just a small patch of the object, by leveraging the fact that many household objects can only keep stable on a planar surface under a small set of poses. In particular, for each stable pose of an object, we slice the object with horizontal planes and extract multiple cross-section 2D contours. The pose estimation is then reduced to find a stable pose whose contour matches best with that of the sensor data, and this can be solved efficiently by cross-correlation. Experiments on the manipulation tasks in the DARPA Robotics Challenge validate our approach. In addition, we also investigate our method’s performance on object recognition tasks raising in the challenge.     

A multi-level 3D data registration approach for supporting reliable spatial change classification of single-pier bridges

The reliability of condition assessment of bridges using 3D imagery data, such as 3D laser scanning point clouds, relies on inspectors’ structural engineering knowledge and skills of 3D data processing. A challenge of 3D-data-based structural condition assessment lies in the difficulties of reliably comparing 3D imagery data sets collected at different times for analyzing spatial changes of the structures and finding anomalous deformations. Spatial changes of structures could occur at multiple levels of details and be of different types: (1) rigid body motions (e.g., translations and rotations) at the structure or structural element levels; (2) deformations (e.g., bending of girders) at the levels of structural elements. Unfortunately, existing 3D imagery data-based change analysis methods only produce deviations between two 3D data sets without distinguishing deviations caused by various changes at multiple levels. Significant rigid body motions of structures and structural elements often cause large deviations that “overwhelm” deviation patterns caused by smaller element-level deformations so that engineers could hardly recognize local deformations. Unreliable deformation analysis of structural elements can lead to incorrect condition assessments.This paper presents a new multi-level 3D data registration and spatial change classification approach that automate the analysis of both element-level deformations and interactions between the motions of multiple elements based on deviations calculated between two 3D data sets. This approach uses a multi-level data registration method augmented by formalized knowledge for representing spatial changes using deviation maps between two 3D datasets. This knowledge will guide pattern analysis methods to reveal how various changes of structures collectively lead to structural systems behaviors. More specifically, this 3D data registration and spatial change classification approach eliminates deviations caused by rigid body motions before assessing deformations of structural elements. The authors conducted annual 3D imagery data collection for two single pier bridges in July 2015 and June 2016, and use those 3D data to characterize the performance of the new approach in identifying relative motions between and deformations of structural elements. The results indicate that the new approach can reliably identify relative motions between and deformations of bridge elements, such as angular changes between elements, and torsions of girders. Finally, the authors validated the change analysis results generated by the developed approach against the traditional change analysis results obtained by a knowledgeable structural engineering researcher and change analyses in multiple single-pier bridge research studies.     

Real-time 3D registration using GPU

3D registration is a computer vision technique of aligning multi-view range images with respect to a reference coordinate system. Aligning range images is an important but time-consuming task for complete 3D reconstruction. In this paper, we propose a real-time 3D registration technique by employing the computing power of graphic processing unit (GPU). A point-to-plane 3D registration technique is completely implemented using CUDA, the up-to-date GPU programming technique. Using a hand-held stereo-vision sensor, we apply the proposed technique to real-time 3D scanning of real objects. Registration of a pair of range images, whose resolution is 320 × 240, takes about 60 ms. 3D scanning results and processing time analysis are shown in experiments. To compare the proposed GPU-based 3D registration with other CPU-based techniques, 3D models of a reference object are reconstructed. Reconstruction results of three different techniques in eight different scanning speed are evaluated.     

基于参数化的三维颅面配准

针对颅面配准问题,提出通过对颅面进行参数化将其转换成二维参数域的对应问题。首先,根据人类的生理特征标定6个特征点,利用这些特征点将颅面转换到一个统一的坐标系以实现姿态和大小的统一;其次,以两个外眼角为约束对参考颅面进行最小二乘保角映射,计算出6个特征点的参数值;然后,以这六个生理特征点的参数值为约束,利用最小二乘保角映射将任一待配准模型映射到二维参数域;最后,根据二维参数域确定三维颅面上的对应点,从而实现三维数据配准。为了验证所提方法,以对应点为控制点,利用薄板样条(TPS)变换把参考颅面变形到目标颅面,以变形后两个模型上对应点之间的几何距离的平均为度量,将所提算法和基于主轴分析的迭代最近点(ICP)配准以及基于随机采样控制点的迭代TPS配准方法进行了比较,实验结果表明,所提算法的配准效果优于其他两种方法。     

GPU-accelerated elastic 3D image registration for intra-surgical applications

Local motion within intra-patient biomedical images can be compensated by using elastic image registration. The application of B-spline based elastic registration during interventional treatment is seriously hampered by its considerable computation time. The graphics processing unit (GPU) can be used to accelerate the calculation of such elastic registrations by using its parallel processing power, and by employing the hardwired tri-linear interpolation capabilities in order to efficiently perform the cubic B-spline evaluation. In this article it is shown that the similarity measure and its derivatives also can be calculated on the GPU, using a two pass approach. On average a speedup factor 50 compared to a straight-forward CPU implementation was reached.     

Extraction of 3D information from sonar image sequences

This paper describes a set of methods that make it possible to estimate the position of a feature inside a three-dimensional (3D) space by starting from a sequence of two-dimensional (2D) acoustic images of the seafloor acquired with a sonar system. Typical sonar imaging systems are able to generate just 2D images, and the acquisition of 3D information involves sharp increases in complexity and costs. The front-scan sonar proposed in this paper is a new equipment devoted to acquiring a 2D image of the seafloor to sail over, and allows one to collect a sequence of images showing a specific feature during the approach of the ship. This fact seems to make it possible to recover the 3D position of a feature by comparing the feature positions along the sequence of images acquired from different (known) ship positions. This opportunity is investigated in the paper, where it is shown that encouraging results have been obtained by a processing chain composed of some blocks devoted to low-level processing, feature extraction and analysis, a Kalman filter for robust feature tracking, and some ad hoc equations for depth estimation and averaging. A statistical error analysis demonstrated the great potential of the proposed system also if some inaccuracies affect the sonar measures and the knowledge of the ship position. This was also confirmed by several tests performed on both simulated and real sequences, obtaining satisfactory results on both the feature tracking and, above all, the estimation of the 3D position.     

数字孪生水下三维实景数据底板获取技术研究

为了获取高精度的水下三维模型细节纹理结构,满足数字孪生建设对水下三维实景数据底板获取的需求,实现对水下构筑物的实时可视化动态监测,基于GNSS技术、USBL技术研究构建了水陆一体化定位技术,融合水陆一体化定位技术、有缆ROV和水下摄影测量设备等研发了水下摄影测量系统,实现了数字孪生水下三维实景数据底板的获取,并采用多波束测深系统、水下三维全景成像声纳系统等对水下摄影测量系统获取的三维实景模型数据成果精度进行了验证,结果表明：水下摄影测量系统获取的三维实景模型精度满足规范要求,可用于数字孪生流域、工程等水下基础数据底板的建设,也可为水下高精度三维场景重构再现和水利工程水下构筑物实时动态监测提供技术支撑。     

Spectral unmixing of airborne hyperspectral data for baseline mapping of mine tailings areas

The Kam Kotia mine tailings areas near Timmins in Ontario, Canada have been generating and discharging acidic mine drainage (AMD) into the surrounding areas for more than 35 years, killing large areas of forest and polluting the local water system. This paper presents results from the remote sensing monitoring programme in the Kam Kotia mine. Hyperspectral TRW (Thompson Ramo Wooldridge Inc.) Imaging Spectrometer III data were acquired over the Kam Kotia mine and tailings areas. This paper describes (1) the data pre‐processing (noise removal, atmospheric correction, spectral smile correction, scene‐based calibration) needed to radiometrically calibrate the images and (2) a novel procedure which combines constrained spectral mixture analysis and threshold‐based classification. With this developed procedure one can retrieve fraction maps of major mine tailings‐related surface materials and hence generate a surface map separating green vegetation, transition zones, dead vegetation, and oxidized tailings, and calculate the extent (surficial area) of each of the zones. The four zones are correlated with the extent and degree of vegetation cover affected by tailings material and are interpreted to span respectively from very low to medium, high, and very high AMD pollution. This procedure can be used to monitor changes in the course of the boundary between affected zones and finally quantify the rehabilitation process in mine tailings areas with high vegetation cover.     

Novel methods for noisy 3D point cloud based object recognition

Multimedia Tools and Applications - 3D point cloud based object recognition becomes increasingly important in the last few years, as the widely use of point cloud over the low-cost 3D sensors have...     

Robust reconstruction of 2D curves from scattered noisy point data

In this paper, a robust algorithm is proposed for reconstructing 2D curve from unorganized point data with a high level of noise and outliers. By constructing the quadtree of the input point data, we extract the “grid-like” boundaries of the quadtree, and smooth the boundaries using a modified Laplacian method. The skeleton of the smoothed boundaries is computed and thereby the initial curve is generated by circular neighboring projection. Subsequently, a normal-based processing method is applied to the initial curve to smooth jagged features at low curvatures areas, and recover sharp features at high curvature areas. As a result, the curve is reconstructed accurately with small details and sharp features well preserved. A variety of experimental results demonstrate the effectiveness and robustness of our method.