Field‐based robotic phenotyping of sorghum plant architecture using stereo vision

Sorghum (Sorghum bicolor) is known as a major feedstock for biofuel production. To improve its biomass yield through genetic research, manually measuring yield component traits (e.g. plant height, stem diameter, leaf angle, leaf area, leaf number, and panicle size) in the field is the current best practice. However, such laborious and time‐consuming tasks have become a bottleneck limiting experiment scale and data acquisition frequency. This paper presents a high‐throughput field‐based robotic phenotyping system which performed side‐view stereo imaging for dense sorghum plants with a wide range of plant heights throughout the growing season. Our study demonstrated the suitability of stereo vision for field‐based three‐dimensional plant phenotyping when recent advances in stereo matching algorithms were incorporated. A robust data processing pipeline was developed to quantify the variations or morphological traits in plant architecture, which included plot‐based plant height, plot‐based plant width, convex hull volume, plant surface area, and stem diameter (semiautomated). These image‐derived measurements were highly repeatable and showed high correlations with the in‐field manual measurements. Meanwhile, manually collecting the same traits required a large amount of manpower and time compared to the robotic system. The results demonstrated that the proposed system could be a promising tool for large‐scale field‐based high‐throughput plant phenotyping of bioenergy crops.     

高分辨率卫星遥感影像立体像对量测的实验——精度统计、分析总结和可行性分析

对0.31 m分辨率Worldview3立体像对带RPC参数的立体量测实验,采用不同的作业平台对立体像对进行量测实验,进行精度统计、分析总结和可行性分析。最终得出0.31 m分辨率Worldview3立体像对在1∶2 000比例尺3D产品生产的可行性,为生产服务打下基础和实践。     

改进自适应加权的局部立体匹配算法

针对Yoon经典自适应加权法在深度不连续处误匹配率较高、边缘细节不突出以及匹配窗口大小凭经验设计不通用等缺陷,提出了一种改进自适应加权的局部立体匹配算法.在经典自适应加权局部立体匹配算法的基础上用高斯分布权值替换了几何空间权值,增加了边缘权值突出深度不连续处的边缘细节,采用赢家通吃原则(Winner Take All,WTA)获取单像素点视差,在目标视图中逐点求取视差,最终获得稠密视差图.实验结果表明,该算法相比于经典自适应加权法,在非遮挡区域错误匹配百分比上下降6％,在深度不连续处的误匹配率降低了5％,边缘细节毛刺明显减少.     

双目立体视觉测量系统的标定

考虑传统的自标定方法虽然无需场景信息即可实现摄像机标定,但是标定精度较低,故本文提出了一种新的大视场双目视觉测量系统自标定方法。该方法无需高精度标定板或者标定物,仅需利用空间中常见的平行线和垂直线建立摄像机参数与特征线间的约束方程,即可实现摄像机的内参数与旋转矩阵标定;同时利用空间中距离已知的3个空间点即可线性标定两摄像机间的平移向量。通过标定实验对本文提出的方法进行了验证。结果表明:该方法标定精度能够达到0.51%,可以较高精度地标定双目测量系统。由于避免了大视场测量系统标定中大型标定物制造困难,以及摄像机自标定过程中算法冗杂,标定精度不高等问题,该方法操作简便,精度较好,适用于大视场双目测量系统的在线标定。     

红外立体辅助驾驶系统可行性研究

为解决当前夜间辅助驾驶仪平面显示的弊端,提出利用平行式红外双目立体系统用于夜间辅助驾驶的方案。分别从波段选择、体视半径和体视区域三个方面分析了系统的可行性,最后通过搭建的红外立体辅助驾驶系统对系统的可行性进行验证。结果表明,红外立体辅助驾驶系统可以有效解决当前夜间辅助驾驶仪平面显示的弊端,有利于驾驶员对路况作出正确的判断。     

巡视探测器立体图像匹配技术研究及应用

提出了一种联合使用自适应权值选择匹配窗和邻域差值特征模板的立体匹配算法,针对复杂的非结构化场景,使用该方法进行了立体匹配实验,获得了浓密的视差图,进而进行了三维重建和基于视差估计与补偿的立体图像压缩应用研究。结果表明,该算法结构简单,能够处理复杂的非结构化场景,适合巡视探测器的自主导航和立体图像压缩等任务使用。     

Isospecific polymerization of vinyl ethers with titanium catalysts containing modified tridentate anionic donor ligands

BACKGROUND: Stereo‐regulated polymerization of vinyl ethers (VEs) assumes significance because of its elegance and the resultant unique polymer properties. Although several Lewis acid catalysts polymerize VEs with good control of molecular weight, achieving stereo‐regularity is quite challenging. There are literature reports of a few catalyst systems capable of producing highly isotactic poly(vinyl ether) (PVE) only at lower temperatures with the polymer becoming atactic with an increase in reaction temperature. Hence innovating new catalyst systems which can produce highly stereo‐regular PVEs with high molecular weight at ambient temperature is quite challenging. RESULTS: We used two different titanium pre‐catalysts (1‐TiCl₂ and 2‐TiCl₂) for the polymerization of VEs. These pre‐catalysts in combination with methylaluminoxane (MAO)/borate polymerized VEs in higher conversions. Highly isotactic poly(n‐butylvinyl ether) (PBVE; 75% dyad isotactic ratio) was obtained with 1‐TiCl₂/MAO at ambient temperature. CONCLUSION: We synthesized unimodal and highly isotactic PBVE with molecular weights of the order of 10⁵ g mol^?1 using the non‐metallocene‐type single‐site catalyst system 1‐TiCl₂/MAO even at ambient temperature. The symmetry around the metal centre in the pre‐catalyst and the polymerization temperature played a major role in controlling the stereo‐regularization of the olefin inserted. Copyright © 2009 Society of Chemical Industry     

Graph-based representations and techniques for image processing and image analysis

In this paper we will discuss the use of some graph-based representations and techniques for image processing and analysis. Instead of making an extensive review of the graph techniques in this field, we will explain how we are using these techniques in an active vision system for an autonomous mobile robot developed in the Institut de Robòtica i Informàtica Industrial within the project “Active Vision System with Automatic Learning Capacity for Industrial Applications (CICYT TAP98-0473)”. Specifically we will discuss the use of graph-based representations and techniques for image segmentation, image perceptual grouping and object recognition. We first present a generalisation of a graph partitioning greedy algorithm for colour image segmentation. Next we describe a novel fusion of colour-based segmentation and depth from stereo that yields a graph representing every object in the scene. Finally we describe a new representation of a set of attributed graphs (AGs), denominated function-described graphs (FDGs), a distance measure for matching AGs with FDGs and some applications for robot vision.     

Trinocular Stereo: A Real-Time Algorithm and its Evaluation

In telepresence applications each user is immersed in a rendered 3D-world composed from representations transmitted from remote sites. The challenge is to compute dense range data at high frame rates, since participants cannot easily communicate if the processing cycle or network latencies are long. Moreover, errors in new stereoscopic views of the remote 3D-world should be hardly perceptible. To achieve the required speed and accuracy, we use trinocular stereo, a matching algorithm based on the sum of modified normalized cross-correlations, and subpixel disparity interpolation. To increase speed we use Intel IPL functions in the pre-processing steps of background subtraction and image rectification as well as a four-processor parallelization. To evaluate our system we have developed a test-bed which provides a set of registered dense ground-truth laser data and image data from multiple views.     

Panoramic Depth Imaging: Single Standard Camera Approach

In this paper we present a panoramic depth imaging system. The system is mosaic-based which means that we use a single rotating camera and assemble the captured images in a mosaic. Due to a setoff of the camera's optical center from the rotational center of the system we are able to capture the motion parallax effect which enables stereo reconstruction. The camera is rotating on a circular path with a step defined by the angle, equivalent to one pixel column of the captured image. The equation for depth estimation can be easily extracted from the system geometry. To find the corresponding points on a stereo pair of panoramic images the epipolar geometry needs to be determined. It can be shown that the epipolar geometry is very simple if we are doing the reconstruction based on a symmetric pair of stereo panoramic images. We get a symmetric pair of stereo panoramic images when we take symmetric pixel columns on the left and on the right side from the captured image center column. Epipolar lines of the symmetrical pair of panoramic images are image rows. The search space on the epipolar line can be additionaly constrained. The focus of the paper is mainly on the system analysis. Results of the stereo reconstruction procedure and quality evaluation of generated depth images are quite promissing. The system performs well for reconstruction of small indoor spaces. Our finall goal is to develop a system for automatic navigation of a mobile robot in a room.