Automated Alignment of Robotic Pan-Tilt Camera Units Using Vision

In this paper we show how to carry out an automatic alignment of a pan-tilt camera platform with its natural coordinate frame, using only images obtained from the cameras during controlled motion of the unit. An active camera in aligned orientation represents the zero position for each axis, and allows axis odometry to be referred to a fixed reference frame; such referral is otherwise only possible using mechanical means, such as end-stops, which cannot take account of the unknown relationship between the camera coordinate frame and its mounting. The algorithms presented involve the calculation of two-view transformations (homographies or epipolar geometry) between pairs of images related by controlled rotation about individual head axes. From these relationships, which can be calculated linearly or optimised iteratively, an invariant line to the motion can be extracted which represents an aligned viewing direction. We present methods for general and degenerate motion (translating or non-translating), and general and degenerate scenes (non-planar and planar, but otherwise unknown), which do not require knowledge of the camera calibration, and are resistant to lens distortion non-linearity.Detailed experimentation in simulation, and in real scenes, demonstrate the speed, accuracy, and robustness of the methods, with the advantages of applicability to a wide range circumstances and no need to involve calibration objects or complex motions. Accuracy of within half a degree can be achieved with a single motion, and we also show how to improve on this by incorporating images from further motions, using a natural extension of the basic algorithm.     

磁场与视觉共融的多模态胶囊机器人人机交互控制

为了实现磁驱动胶囊内窥镜基于定点悬停调姿的全景观察,提出一种欠驱动双半球胶囊机器人,突破了悬停调姿与滚动行走双重工作模态转换关键技术．为了在肠道弯曲环境内实现滚动行走,提出与视觉相融合的空间万向旋转磁场人机交互控制策略．理论上,依据正交变换推得经纬坐标系下以磁场轴线的侧摆角与俯仰角为独立变量的三相电流形式空间万向旋转磁场叠加公式,完成控制变量降维与解耦,实现磁场轴线沿侧摆或俯仰方向的单独调整;实践上,通过磁矩随动效应带动双半球形胶囊机器人摄像头分别实现侧摆与俯仰2个方向的独立扫描,使机器人轴线对准各段肠道弯曲方向,沿弯曲方向施加滚动磁矩实现胶囊机器人滚动转弯．最后,采用离体猪大肠模拟环境验证人机交互性能．试验表明,通过结合弯曲肠道图像与磁场方位的人机交互控制,既能实现双半球形胶囊机器人在被动模态下的姿态任意调整与全景观察,也能实现在主动模态下沿弯曲环境的滚动行走．     

A geostatistical algorithm to reproduce lateral gradual facies transitions: Description and implementation

Valid representations of geological heterogeneity are fundamental inputs for quantitative models used in managing subsurface activities. Consequently, the simulation of realistic facies distributions is a significant aim. Realistic facies distributions are typically obtained by pixel-based, object-based or process-based methods. This work presents a pixel-based geostatistical algorithm suitable for reproducing lateral gradual facies transitions (LGFT) between two adjacent sedimentary bodies. Lateral contact (i.e. interfingering) between distinct depositional facies is a widespread geometric relationship that occurs at different scales in any depositional system. The algorithm is based on the truncation of the sum of a linear expectation trend and a random Gaussian field, and can be conditioned to well data. The implementation introduced herein also includes subroutines to clean and geometrically characterize the obtained LGFT. The cleaned sedimentary body transition provides a more appropriate and realistic facies distribution for some depositional settings. The geometric measures of the LGFT yield an intuitive measure of the morphology of the sedimentary body boundary, which can be compared to analogue data. An example of a LGFT obtained by the algorithm presented herein is also flow simulated, quantitatively demonstrating the importance of realistically reproducing them in subsurface models, if further flow-related accurate predictions are to be made.     

多通道/多波束星载SAR实现高分辨宽测绘带成像综述

传统单发单收星载SAR受最小天线面积限制,不能同时实现高分辨率和大测绘带,采用多通道接收可以有效解决该问题。本文阐述了多种结构的多通道SAR系统的实现原理,分析比较了多种系统在品质因子、数据量、信噪比、信号处理复杂度以及是否存在盲区等方面的优劣和异同,并给出整体性能评价。这些结论对实际系统设计提供了理论指导和有力支撑,具有一定的参考价值。     

基于均匀圆阵的闭环式单基站测向算法研究

为了估算基于均匀圆阵列(UCA)的三维(3D)单基站测向(方位角、仰角和区间),提出了一种改进的适用于三维场景的闭环式算法。该算法是一种计算过程较简单的通用算法,无需使用均匀圆阵列的中心对称性,没有任何传感器数量的限制,只需要一个单独的最小平方程序用于估算基站的位置,并可以估算所有的三维测向参数。实验结果表明,相比多种类似算法,所提算法的性能可与三维MUSIC算法的性能相媲美,且计算复杂度更低,实现速度更快。     

Polarization-singular structure of laser images of stratified phase-inhomogeneous layers for the diagnostics and classification of their optical properties

Presented in this work are the results of investigation aimed at analysis of coordinate distributions for azimuths and ellipticity of polarization (polarization maps) in laser images of three types of phase-inhomogeneous layers, namely: rough, ground and bulk scattering layers. To characterize polarization maps for all the types of phase-inhomogeneous layers, the authors have offered to use three groups of parameters: statistical moments of the first to the fourth orders, autocorrelation functions and logarithmic dependences for power spectra related to distributions of azimuths and ellipticity of polarization inherent to phase-inhomogeneous layers laser images. Ascertained are the criteria for diagnostics and classification of phase-inhomogeneous layers optical properties.     

Recognizing solid objects by alignment with an image

In this paper we consider the problem of recognizing solid objects from a single two-dimensional image of a three-dimensional scene. We develop a new method for computing a transformation from a three-dimensional model coordinate frame to the two-dimensional image coordinate frame, using three pairs of model and image points. We show that this transformation always exists for three noncollinear points, and is unique up to a reflective ambiguity. The solution method is closed-form and only involves second-order equations. We have implemented a recognition system that uses this transformation method to determine possible alignments of a model with an image. Each of these hypothesized matches is verified by comparing the entire edge contours of the aligned object with the image edges. Using the entire edge contours for verification, rather than a few local feature points, reduces the chance of finding false matches. The system has been tested on partly occluded objects in highly cluttered scenes.     

运动视频对象分割的一种快速算法

为了能够实时地对运动视频对象进行分割,提出了一种对视频序列图象中的运动对象进行快速分割提取的算法,该算法首先对图象进行滤波,并求出连续两帧图象之间的差分,然后应用“同化填充”技术和基于对象的“整体运动估计”来对差分图象进行修正,进而得到对象模板,同时利用模板缓冲区的帧间迭代来维持模板的完整性,该算法不仅不依赖于固定背景,而且能够消除差分图中的显露背景,还能得到运动目标较为精确的形状,并且算法简单,快速,鲁棒性好。     

Multiple Axis‐Aligned Filters for Rendering of Combined Distribution Effects

Distribution effects such as diffuse global illumination, soft shadows and depth of field, are most accurately rendered using Monte Carlo ray or path tracing. However, physically accurate algorithms can take hours to converge to a noise‐free image. A recent body of work has begun to bridge this gap, showing that both individual and multiple effects can be achieved accurately and efficiently. These methods use sparse sampling, GPU raytracers, and adaptive filtering for reconstruction. They are based on a Fourier analysis, which models distribution effects as a wedge in the frequency domain. The wedge can be approximated as a single large axis‐aligned filter, which is fast but retains a large area outside the wedge, and therefore requires a higher sampling rate; or a tighter sheared filter, which is slow to compute. The state‐of‐the‐art fast sheared filtering method combines low sampling rate and efficient filtering, but has been demonstrated for individual distribution effects only, and is limited by high‐dimensional data storage and processing. We present a novel filter for efficient rendering of combined effects, involving soft shadows and depth of field, with global (diffuse indirect) illumination. We approximate the wedge spectrum with multiple axis‐aligned filters, marrying the speed of axis‐aligned filtering with an even more accurate (compact and tighter) representation than sheared filtering. We demonstrate rendering of single effects at comparable sampling and frame‐rates to fast sheared filtering. Our main practical contribution is in rendering multiple distribution effects, which have not even been demonstrated accurately with sheared filtering. For this case, we present an average speedup of 6× compared with previous axis‐aligned filtering methods.     

基于数据矩阵的多个窄带信号频率和波达方向同时估计

以矩阵奇异值分解的性能研究为基础,针对等矩线阵提出了一种多个窄带信号波达方向和频率的同时估计方法。该方法用采集到的数据矩阵在最小二乘意义下低秩近似无噪数据矩阵,并根据信号的窄带假设构造了可用ESPRIT型方法求解待测参数的矩阵结构,频率和方向可自动配对,计算量较小。计算机模拟实验证实了该方法所作近似的有效性,显示了其高分辨率特性和在短数据条件下的鲁棒性。     

A truncated Levenberg-Marquardt algorithm for the calibration of highly parameterized nonlinear models

We propose a modification to the Levenberg-Marquardt minimization algorithm for a more robust and more efficient calibration of highly parameterized, strongly nonlinear models of multiphase flow through porous media. The new method combines the advantages of truncated singular value decomposition with those of the classical Levenberg-Marquardt algorithm, thus enabling a more robust solution of underdetermined inverse problems with complex relations between the parameters to be estimated and the observable state variables used for calibration. The truncation limit separating the solution space from the calibration null space is re-evaluated during the iterative calibration process. In between these re-evaluations, fewer forward simulations are required, compared to the standard approach, to calculate the approximate sensitivity matrix. Truncated singular values are used to calculate the Levenberg-Marquardt parameter updates, ensuring that safe small steps along the steepest-descent direction are taken for highly correlated parameters of low sensitivity, whereas efficient quasi-Gauss-Newton steps are taken for independent parameters with high impact. The performance of the proposed scheme is demonstrated for a synthetic data set representing infiltration into a partially saturated, heterogeneous soil, where hydrogeological, petrophysical, and geostatistical parameters are estimated based on the joint inversion of hydrological and geophysical data.     

3D shape metamorphosis based on T-spline level sets

We propose a new method for 3D shape metamorphosis, where the in-between objects are constructed by using T-spline scalar functions. The use of T-spline level sets offers several advantages: First, it is convenient to handle complex topology changes without the need of model parameterization. Second, the constructed objects are smooth (C² in our case). Third, high quality meshes can be easily obtained by using the marching triangulation method. Fourth, the distribution of the degrees of freedom can be adapted to the geometry of the object. Given one source object and one target object, we firstly find a global coordinate transformation to approximately align the two objects. The T-spline control grid is adaptively generated according to the geometry of the aligned objects, and the initial T-spline level set is found by approximating the signed distance function of the source object. Then we use an evolution process, which is governed by a combination of the signed distance function of the target object and a curvature-dependent speed function, to deform the T-spline level set until it converges to the target shape. Additional intermediate objects are inserted at the beginning/end of the sequence of generated T-spline level sets, by gradually projecting the source/target object to the initial/final T-spline level set. A fully automatic algorithm is developed for the above procedures. Experimental results are presented to demonstrate the effectiveness of our method.     

A novel spaceborne SAR wide-swath imaging approach based on Poisson disk-like nonuniform sampling and compressive sensing

Since the range swath width in the conventional single channel spaceborne synthetic aperture radar(SAR)is restricted by the system parameters,there is a trade-off between the azimuth resolution and the swath width in order to satisfy the Nyquist sampling criterion.In this paper,we propose a novel spaceborne SAR wide-swath imaging scheme based on compressive sensing(CS)for the sparse scene.The proposed method designs a Poisson disk-like nonuniform sampling pattern in the azimuth direction,which meets the demand of wider swath by restricting the smallest time interval between any two azimuth samples,with the conventional sampling pattern preserved in the range direction.By a similar way to the processing procedure of spectral analysis(SPECAN)algorithm,the linear range migration correction(RMC)is realized while carrying out range compression,which can meet the demand for focusing with middle level resolution.To reduce the computation load of CS reconstruction,we propose a novel fast reconstruction algorithm based on nonuniform fast Fourier transform(NUFFT),which greatly reduces the computation complexity from O(2M N)to O(4N log N).Experiment results validate the effectiveness of the proposed methods via the point target simulation and the Radarsat-1 raw data processing in F2 mode.     

Measurement of ocean surface slopes and wave spectra using polarimetric SAR image data

Methods have been investigated which use fully polarimetric synthetic aperture radar (SAR) image data to measure ocean slopes and wave spectra. Independent techniques have been developed to measure wave slopes in the SAR azimuth and range directions. The azimuth slope technique, in particular, is a more direct measurement than conventional, intensity based, backscatter cross-section measurements.In the azimuth direction, wave-induced perturbations of the polarimetric orientation angle are used to sense the wave slopes. In the range direction, a new technique involving the alpha parameter from the Cloude-Pottier H-A-? (Entropy, Anisotropy, and (averaged) Alpha) polarimetric scattering decomposition theorem is used to measure slopes. Both measurement types are sensitive to ocean wave slopes and are directional. Taken together, they form a means of using polarimetric SAR (POLSAR) image data to make complete measurements of either ocean wave slopes, or directional wave spectra.These measurements must still contend with fundamental nonlinearities in the SAR image processing (i.e., azimuth direction “velocity bunching”) that are due to wave velocity and acceleration effects.NASA/JPL/AIRSAR L-, and P-band data from California coastal waters were used in the studies. Wave parameters measured using the new methods are compared with those developed using both conventional SAR intensity based methods, and with in situ NOAA National Data Center buoy measurement products.     

离散ADMM方法下像素与对象基元协同优化的遥感影像无监督语义分割

语义分割是遥感影像分析中的重要技术之一。现有的方法（如基于深度卷积神经网络的方法等）虽然在语义分割中取得了显著进展,但往往需要大量训练数据。基于图模型的马尔可夫随机场模型（Markov random field model,MRF）提出了一种不依赖训练数据的无监督语义分割思路,可以有效地刻画地物空间关系,并对地物空间分布的统计规律进行建模。但现有的MRF模型方法通常建立在基于像素或对象的单一粒度基元上,难以充分利用影像信息,语义分割效果不佳。针对上述问题,引入交替方向乘子法 （alternative direction method of multiplier,ADMM）并将其离散化,提出了一种像素与对象基元协同的MRF模型无监督语义分割方法（MRF-ADMM）。首先构建像素基元和对象基元两个概率图,其中像素基元概率图用于刻画影像的细节信息,保持语义分割的边界;对象基元概率图用于描述较大范围的空间关系,以应对遥感影像地物内部的高异质性,使分割结果中地物内部具有良好的区域完整性。在模型求解过程中,针对像素和对象基元的特点,提出了一种离散化的ADMM方法,并将其用于两种基元类别标记的传递与更新,实现像素基元细节信息和对象基元区域信息的协同优化。高分二号和航拍影像等不同数据库不同类型遥感影像的语义分割实验结果表明,相较于现有的MRF模型,提出的MRF-ADMM方法能有效地协同不同粒度基元的优点,优化语义分割结果。     

直角坐标系中雷达测量方差的计算方法分析

The distributed network system of multi radar target monitoring usually includes polar coordinate system with radar as co- ordinate origin and rectangular coordinate system with command center as coordinate origin. However, due to the complex situation of different radar surrounding airspace environment and radar equipment, large sample standard deviation is prone to occur in the measurement of target distance, azimuth and elevation angle by single radar. In this case, according to the unified rectangular coordi- nate system, target position error transfer method, comprehensive index statistics method and other calculation methods, the mea- surement weight, variance and standard deviation of different coordinate components of the target object are analyzed statistically. After that, the weighted fusion model of multi radar tracks is used to verify the vertical weighted estimation value of limited radar measurement points in rectangular coordinate system, and then the result value of each element state of the target is determined.     

一种运动模糊图像的模糊参数估计方法

在摄取图像的过程中,物体间的高速运动及景物与成像设备的相对运动是引发图像退化的主要原因之一,称之为运动模糊。模糊长度和模糊方向是运动模糊中影响图像模糊程度的主要参数。提出了一种改进的误差参数分析方法,对模糊长度进行估计并比较了不同的复原方法对参数误差曲线法估计的效果,同时提出运用傅里叶分解和Hough变换从模糊图像的频谱特性上对运动模糊方向进行了估计。实验结果表明,所提出的方法对运动模糊图像的复原有良好的效果。     

A Rendering Algorithm for Discrete Volume Density Objects

We present a new algorithm for simulating the effect of light travelling through volume objects. Such objects (haze, fog, clouds…) are usually modelized by voxel grids which define their density distribution in a discrete tridimensional space. The method we propose is a two-pass Monte-Carlo ray-tracing algorithm that does not make any restrictive assumptions neither about the characteristics of the objects (both arbitrary density distributions and phase functions are allowed) nor about the physical phenomena included in the rendering process (multiple scattering is accounted for). The driving idea of the algorithm is to use the phase function for Monte-Carlo sampling, in order to modify the direction of the ray during scattering.     

Exploiting detected visual objects for frame-level video filtering

Videos are generated at an unprecedented speed on the web. To improve the efficiency of access, developing new ways to filter the videos becomes a popular research topic. One on-going direction is using visual objects to perform frame-level video filtering. Under this direction, existing works create the unique object table and the occurrence table to maintain the connections between videos and objects. However, the creation process is not scalable and dynamic because it heavily depends on human labeling. To improve this, we propose to use detected visual objects to create these two tables for frame-level video filtering. Our study begins with investigating the existing object detection techniques. After that, we find object detection lacks the identification and connection abilities to accomplish the creation process alone. To supply these abilities, we further investigate three candidates, namely, recognizing-based, matching-based and tracking-based methods, to work with the object detection. Through analyzing the mechanism and evaluating the accuracy, we find that they are imperfect for identifying or connecting the visual objects. Accordingly, we propose a novel hybrid method that combines the matching-based and tracking-based methods to overcome the limitations. Our experiments show that the proposed method achieves higher accuracy and efficiency than the candidate methods. The subsequent analysis shows that the proposed method can efficiently support the frame-level video filtering using visual objects.