超仔细！绝不可错失的点云数据处理与建模过程
<h1 style="color: black; text-align: left; margin-bottom: 10px;">什么是点云？</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">点云是<span style="color: black;">目的</span>表面特性的海量点集合，点云越密集，反映的图像细节和信息就越多。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">当<span style="color: black;">咱们</span>利用三维激光扫描仪扫描某一建筑表面时，<span style="color: black;">咱们</span><span style="color: black;">能够</span>得到<span style="color: black;">海量</span>密集的点，这些点带有三维坐标<span style="color: black;">（XYZ）、激光反射强度和和颜色信息（RGB）等信息，它们<span style="color: black;">一起</span>创建了可识别的三维结构。</span></span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/254db8df3816463194cae07bfa400570~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=KcqdM%2FWp5wFrthLv8NPvn0CTVTk%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">创建和利用点云是从另一种<span style="color: black;">方向</span>认识数据世界的方式，当<span style="color: black;">咱们</span>想要利用点云去实现<span style="color: black;">目的</span>，<span style="color: black;">咱们</span>必须<span style="color: black;">晓得</span><span style="color: black;">怎样</span><span style="color: black;">得到</span>点云数据，并从中取得最大的价值。下面，<span style="color: black;">咱们</span><span style="color: black;">一块</span>来<span style="color: black;">认识</span>下点云的获取和处理方式。</span></p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;"><span style="color: black;">怎样</span>创建点云？</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">日前</span>，点云的获取方式<span style="color: black;">通常</span>是<span style="color: black;">经过</span>三维激光扫描仪，三维激光扫描仪<span style="color: black;">经过</span>扫描选定的<span style="color: black;">目的</span>物体或环境后，能大面积高分辨率地快速获取被测对象表面的三维坐标数据。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">下面，我们以Trimble三维激光扫描仪为例，<span style="color: black;">一块</span>来看下点云数据的<span style="color: black;">详细</span>创建过程。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">Trimble三维激光扫描仪<span style="color: black;">重点</span>扫描过程和技术流程如下：</span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p26-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/fd4474d1f8cb47ee92e2b733c217c320~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=xZi%2Bs6Zyy1GHFCGUGk3BgDIUXX8%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">Trimble三维激光扫描仪<span style="color: black;">最后</span>采集的数据以点云和图像的形式储存在扫描仪设备里，运用Trimble RealWorks进行<span style="color: black;">必定</span>处理后，能获取建筑物的相对位置信息、尺寸、纹理和形状，<span style="color: black;">从而</span><span style="color: black;">创立</span>真实的物体数据模型。</span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/6bac0ee97ba04224a368abb43511b284~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=f%2FY74TAr0Cj02B2s%2B3Ax75riP2Y%3D" style="width: 50%; margin-bottom: 20px;"></div>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">点云数据预处理</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">在三维激光扫描的过程中，点云数据的获取常常会受到物体遮挡、光照不均匀等<span style="color: black;">原因</span>的影响，容易<span style="color: black;">导致</span><span style="color: black;">繁杂</span>形状物体的区域扫描盲点，形成孔洞。<span style="color: black;">同期</span><span style="color: black;">因为</span>扫描<span style="color: black;">测绘</span>范围有限，<span style="color: black;">针对</span>大尺寸物体<span style="color: black;">或</span>大范围场景，<span style="color: black;">不可</span>一次性进行完整<span style="color: black;">测绘</span>，必须多次扫描<span style="color: black;">测绘</span>，<span style="color: black;">因此呢</span>扫描结果<span style="color: black;">常常</span>是多块具有<span style="color: black;">区别</span>坐标系统且存在噪声的点云数据，<span style="color: black;">不可</span>够完全满足人们对数字化模型真实度和实时性的<span style="color: black;">需求</span>，<span style="color: black;">因此</span>需要对三维点云数据进行去噪、简化、配准以及补洞等预处理。</span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/d7d415635cb148c789d1ecccb7abcd95~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=SatILb3Naxt%2F4acgQnoMaOJzTBc%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">经过</span>数据预处理，<span style="color: black;">能够</span>有效剔除点云中的噪声和外点，在保持几何特征的<span style="color: black;">基本</span>上实现点云数据简化，并将<span style="color: black;">区别</span><span style="color: black;">方向</span>扫描的点云统一到同一坐标系下，为后续的曲面构建及三维实体模型生成<span style="color: black;">供给</span>稳健的数据<span style="color: black;">基本</span>。</span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/b7a6004179c24d5ea72ec212e3d1e9bd~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=NrLK%2Bt%2BBdk2AMyYkNOF5v3IfMTI%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">1.数据配准</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">点云数据配准，<span style="color: black;">亦</span>成点云数据拼接或坐标纠正<span style="color: black;">。点云拼接</span>是点云数据处理时最<span style="color: black;">重点</span>的数据处理之一，<span style="color: black;">因为</span><span style="color: black;">目的</span>物的<span style="color: black;">繁杂</span>性，<span style="color: black;">一般</span>需要从<span style="color: black;">区别</span>方位扫描多个测站，<span style="color: black;">才可</span>把<span style="color: black;">目的</span>物扫描完整，每一测站扫描数据都有自己的坐标系统，三维模型的重构<span style="color: black;">需求</span>把<span style="color: black;">区别</span>测站的扫描数据纠正到统一的坐标系下。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">点云拼接<span style="color: black;">办法</span><span style="color: black;">归类</span>如下：</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">1）标靶拼接。标靶拼接是点云拼接最常用的<span style="color: black;">办法</span>，<span style="color: black;">首要</span>在扫描两站的公共区域<span style="color: black;">安置</span>3个或3个以上的标靶，依次对各个测站的数据和标靶进行扫描，最后利用<span style="color: black;">区别</span>站点相同的标靶数据进行点云配准。每一个标靶对应一个ID号，同一标靶在<span style="color: black;">区别</span>测站的ID号必须一致，<span style="color: black;">才可</span>完成拼接。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">2）点云拼接。基于点云的拼接方式<span style="color: black;">需求</span>在扫描<span style="color: black;">目的</span>对象时要有<span style="color: black;">必定</span>的区域重叠度，<span style="color: black;">况且</span><span style="color: black;">目的</span>对象特征点要<span style="color: black;">显著</span>，否则<span style="color: black;">没法</span>完成数据的拼接。此<span style="color: black;">办法</span>需要依靠寻找重叠区域的同名点进行拼接，<span style="color: black;">因此呢</span>重叠区域特征点的确定直接关系到配准结果的好坏。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">3）<span style="color: black;">掌控</span>点拼接。为了<span style="color: black;">加强</span>拼接精度，三维激光扫描系统<span style="color: black;">能够</span>与全站仪或GPS技术联合<span style="color: black;">运用</span>。<span style="color: black;">经过</span>全站仪<span style="color: black;">或</span>GPS确定公共<span style="color: black;">掌控</span>点的大地坐标，<span style="color: black;">而后</span>用三维激光扫描仪对所有公共<span style="color: black;">掌控</span>点进行精确扫描。再以<span style="color: black;">掌控</span>点为基站直接将扫描的多测站的点云数据与其拼接，<span style="color: black;">就可</span>将扫描的所有点云数据转换成工程<span style="color: black;">实质</span>需要的坐标系。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">2.数据去噪</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">在利用三维激光扫描仪扫描<span style="color: black;">目的</span>时，会受到扫描设备、<span style="color: black;">周边</span>环境、人为扰动、<span style="color: black;">目的</span>特性等影响，使得点云数据<span style="color: black;">没法</span>避免的存在<span style="color: black;">有些</span>噪点，<span style="color: black;">引起</span>数据<span style="color: black;">没法</span>正确表达扫描对象的空间位置。</span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/589f9b459f3c4a43a2836e38b4a91bc6~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=4NZV8WansalC4SoCYYKt7OdhL3k%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">噪声点<span style="color: black;">重点</span>分为三类：</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">1）<span style="color: black;">因为</span>物体表面材质或光照环境<span style="color: black;">引起</span>反射信号较弱等<span style="color: black;">状况</span>下产生的噪点；</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">2）<span style="color: black;">因为</span>扫描过程中，人、车辆或其他物体从扫描仪器与物体之间经过而产生的噪点；</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">3）<span style="color: black;">因为</span><span style="color: black;">测绘</span>设备<span style="color: black;">自己</span><span style="color: black;">原由</span>，如扫描仪精度、相机分辨率等<span style="color: black;">导致</span>的系统误差和随机误差。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">数据去噪的<span style="color: black;">办法</span><span style="color: black;">能够</span><span style="color: black;">按照</span><span style="color: black;">区别</span>的<span style="color: black;">状况</span>分为<span style="color: black;">区别</span>的处理<span style="color: black;">办法</span>：</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">1）基于有序点云数据用平滑滤波去噪法，<span style="color: black;">日前</span>数据平滑滤波<span style="color: black;">重点</span>采取的是高斯滤波、均值滤波以及中值滤波。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">①高斯滤波属于线性平滑滤波，是对指定区域内的数据加权平均，<span style="color: black;">能够</span>去除高频信息，其优点为能够在<span style="color: black;">保准</span>去噪质量的前提下<span style="color: black;">保存</span>住点云数据特征信息。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">②均值滤波<span style="color: black;">亦</span>叫平均滤波，<span style="color: black;">亦</span>是一种较为典型的线性滤波，其原理为<span style="color: black;">选取</span><span style="color: black;">必定</span>范围内的点求取其平均值来代替其<span style="color: black;">本来</span>的数据点，优点为算法简单易行，缺点为去噪的效果较为平均.且<span style="color: black;">不可</span>很好的<span style="color: black;">保存</span>住点云的特征细节。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">③中值滤波属于非线性平滑滤波，其原理是对某点数据相邻的三个或以上的数据求中值，求取后的结果取代其原始值，其优点在于对毛刺噪声的去除有很好效果，<span style="color: black;">况且</span><span style="color: black;">亦</span>能很好的<span style="color: black;">守护</span>数据边缘特征信息。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">2）基于散乱点云数据去噪常用的<span style="color: black;">办法</span>为拉普拉斯去噪、平均曲率流<span style="color: black;">办法</span>、双边滤波算法。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">①拉普拉斯算法虽然能够很好的<span style="color: black;">保准</span>模型的细节特征，<span style="color: black;">然则</span>还会残存有噪声点。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">②双边滤波算法虽然能够很好的去除噪声点，<span style="color: black;">然则</span><span style="color: black;">不可</span>够很好的<span style="color: black;">保存</span>住模型的细节特征。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">③平均曲率是依赖于曲率估计，<span style="color: black;">针对</span>模型简单噪声点较少的数据去噪效果较好，而<span style="color: black;">针对</span><span style="color: black;">繁杂</span>且噪声点多的数据，其计算速度慢且去噪效果较差。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">3.数据精简</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">数据精简<span style="color: black;">便是</span>在精度<span style="color: black;">准许</span>下减少点云数据的数据呈，提取有效信息。<span style="color: black;">通常</span>分为两种：去除冗余与抽稀简化。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">冗余数据<span style="color: black;">指的是</span>在数据配准之后，其重复区域的数据，这部分数据的数据呈大，多为无用数据，对建模的速度以及质量有很大影响，<span style="color: black;">针对</span>这部分数据要予以去除。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">抽稀简化<span style="color: black;">指的是</span>扫描的数据密度过大，数量<span style="color: black;">太多</span>，其中一部分数据<span style="color: black;">针对</span>后期建模用处不大，<span style="color: black;">因此</span>在满足<span style="color: black;">必定</span>精度以及保持被测物体几何特征的前提下，对数据进行精简。以<span style="color: black;">加强</span>数据的操作运算速度、建模效率以及模型精度。</span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/22b45bb9ec76487fb9b8684243b396f4~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=2g4uuQjVn%2B%2BLet5bTlWI5tmLm7g%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">4.数据分割</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">针对</span>较为<span style="color: black;">繁杂</span>的扫描对象，<span style="color: black;">倘若</span>直接进行点云数据建模，会使得建模过程<span style="color: black;">非常</span>困难，三维模型的数学表达变得<span style="color: black;">繁杂</span>。<span style="color: black;">因此</span><span style="color: black;">针对</span><span style="color: black;">繁杂</span>的建模对象，<span style="color: black;">咱们</span><span style="color: black;">通常</span>会进行点云数据分割，<span style="color: black;">而后</span>再分别建模，最后再进行组合。</span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p26-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/7d3a6288f14a489681c337724aa2dd9c~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=%2FkJZ3SFgeYRSC7%2F5inzqegzh2aM%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">点云数据分割应该遵守以下准则：</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">1）分块区域的特征单一且同一区域内<span style="color: black;">无</span>法矢量及曲率的突变；</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">2）分割的公共边<span style="color: black;">尽可能</span>便于后续的拼接；</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">3）分块的个数<span style="color: black;">尽可能</span>少，可减少后续的拼接<span style="color: black;">繁杂</span>度；</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">4）分割后的每<span style="color: black;">一起</span>要易于重建几何模型。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">点云数据分割的<span style="color: black;">重点</span><span style="color: black;">办法</span>有三种，基于边的分割<span style="color: black;">办法</span>、基于面的分割<span style="color: black;">办法</span>和基于聚类的分割<span style="color: black;">办法</span>。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">1）基于边的分割<span style="color: black;">办法</span>需先寻找出特征线。<span style="color: black;">所说</span>特征线，<span style="color: black;">亦</span><span style="color: black;">便是</span>特征点所连成的线，<span style="color: black;">日前</span>最常用的提取特征点的<span style="color: black;">办法</span>为基于曲率和法矢量的提取<span style="color: black;">办法</span>，<span style="color: black;">一般</span>认为曲率<span style="color: black;">或</span>法矢量突变的点为特征点，例如拐点<span style="color: black;">或</span>角点。提取出特征线之后，再对特征线围成的区域进行分割。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">2）基于面的<span style="color: black;">办法</span>是一个<span style="color: black;">持续</span>迭代过程，找到<span style="color: black;">拥有</span>相同曲面性质的点，将属于同一基本几何特征的点集分割到同一区域，再确定这些点所属的曲面，最后由相邻的曲面决定曲面间的边界。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">3）基于聚类的<span style="color: black;">办法</span><span style="color: black;">便是</span>将<span style="color: black;">类似</span>的几何特征参数数据点<span style="color: black;">归类</span>，可用<span style="color: black;">按照</span>高斯曲率和平均曲率来求出其几何特征再聚类，最后<span style="color: black;">按照</span>所属类来分割。</span></p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">点云数据建模</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">日前</span>，业内<span style="color: black;">运用</span>较多的点云数据建模软件为ContextCapture。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">ContextCapture 是一款可由简单的照片和/或点云自动生成<span style="color: black;">仔细</span>三维实景模型的软件。ContextCapture 的高兼容性，能对<span style="color: black;">各样</span>对象<span style="color: black;">各样</span>数据源进行精确无缝重建，从厘米级到<span style="color: black;">千米</span>级，从地面或从空中拍摄。只要输入照片的分辨率和精度足够，生成的三维模型是<span style="color: black;">能够</span>实现无限精细的细节。</span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/2265757f5420401fa47dea5f94aa2f16~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=n%2FCwu9eFJcpSfKGNVnVWMeruPqI%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">ContextCapture<span style="color: black;">拥有</span>以下功能：</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">1.集成地理参考数据</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">ContextCapture 可为<span style="color: black;">包含</span> GPS 标记和<span style="color: black;">掌控</span>点在内的多种类型的定位数据<span style="color: black;">供给</span>本地支持。它还<span style="color: black;">能够</span><span style="color: black;">经过</span>定位/旋转导入或完整块导入来导入任何其他定位数据，能够精确<span style="color: black;">测绘</span>坐标、距离、面积和体积。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">2.自动空中三角<span style="color: black;">测绘</span>和三维重建</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">一旦自动识别每张相片的相对位置和方向，就<span style="color: black;">能够</span><span style="color: black;">经过</span>添加<span style="color: black;">掌控</span>点和编辑连接点来对空中三角<span style="color: black;">测绘</span>结果进行微调，以最大限度<span style="color: black;">提高</span>几何和地理空间精度。优化的三维重建算法以无可匹敌的精度生成<span style="color: black;">精细</span>的三维模型以及<span style="color: black;">每一个</span>格网面片的影像纹理。ContextCapture 可<span style="color: black;">保证</span>各个三维格网模型顶点<span style="color: black;">安置</span>在最佳位置，<span style="color: black;">因此呢</span><span style="color: black;">能够</span>更少的瑕疵表现重现更精细的细节和更锐利的边缘，从而大幅<span style="color: black;">加强</span>几何精度。</span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/88c8413fc50345809d9322b486a2e0ae~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=OX1sSfy%2FSZbLOEZ3QIEN5q0H3JM%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">3.生成二维和三维 GIS 模型</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">借助 ContextCapture，<span style="color: black;">能够</span>生成<span style="color: black;">各样</span> GIS 格式的精确地理参考三维模型，<span style="color: black;">包含</span>真正射影像和新的 Cesium 3D Tiles，并将瓦片范围和空三成果导出为KML和XML。ContextCapture <span style="color: black;">供给</span>的坐标系数据库接口可<span style="color: black;">保证</span>与GIS <span style="color: black;">处理</span><span style="color: black;">方法</span>的数据互用性。<span style="color: black;">能够</span>从 4,000 多个空间参考系统中进行<span style="color: black;">选取</span>，并可添加用户自定义的坐标系。<span style="color: black;">况且</span>，ContextCapture 会<span style="color: black;">按照</span>输入照片的分辨率和空间分布<span style="color: black;">状况</span>，自动<span style="color: black;">调节</span>模型的分辨率和精度。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">这<span style="color: black;">寓意</span>着，ContextCapture<span style="color: black;">能够</span>处理分辨率不均匀的场景，而不必为<span style="color: black;">保存</span><span style="color: black;">有些</span>更高分辨率的场景区域而牺牲整体效率。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">4.处理实景模型</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">ContextCapture<span style="color: black;">能够</span>快速<span style="color: black;">容易</span>地处理任何比例的格网模型，以及横断面的生成、地形和断裂线的提取，及正射影像、三维 PDF 和 iModel 的生成。它<span style="color: black;">能够</span>将格网模型与 GIS 和工程数据集成，以在格网模型的视觉环境中实现该信息的直观搜索、导航、可视化和动画。</span></p>
<div style="color: black; text-align: left; margin-bottom: 10px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-qvj2lq49k0/96a696363b5a409fbde6889bc868b1b2~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1728805630&x-signature=8BaGlgG%2Bg66tWqwdjRNmjoP25R4%3D" style="width: 50%; margin-bottom: 20px;"></div>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">5.处理点云</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">能够</span>对点云进行<span style="color: black;">加强</span>、分割、<span style="color: black;">归类</span>，并与工程模型相结合。<span style="color: black;">而后</span>，利用 ContextCapture的高级三维建模、横截面切割、断裂线和地形提取功能，快速<span style="color: black;">有效</span>地对竣工<span style="color: black;">要求</span>进行建模并支持设计流程。<span style="color: black;">因此呢</span>，ContextCapture<span style="color: black;">能够</span>更好地<span style="color: black;">评定</span>点云并生成更精确的工程模型，还<span style="color: black;">能够</span>生成用于展示的动画和渲染。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">6.生成和处理大型可缩放地形模型</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">ContextCapture<span style="color: black;">能够</span>从多种<span style="color: black;">源自</span>中生成非常庞大的可缩放地形模型，<span style="color: black;">包含</span>点云、断裂线、光栅数字高程模型和现有三角形化不规则网络。<span style="color: black;">经过</span>与原始数据源同步，可缩放地形模型可实时更新到最新。<span style="color: black;">这般</span>做的价值在于，<span style="color: black;">持有</span>您所有数据的全局、最新和综合<span style="color: black;">暗示</span>，并用于<span style="color: black;">运用</span><span style="color: black;">各样</span><span style="color: black;">表示</span>模式执行分析，以及生成动画和可视化效果。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">ContextCapture软件详情：<a style="color: black;">实景建模比你想象的更强大！ContextCapture在全生命周</a>期中的应用</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;"><span style="color: black;">倘若</span>，您对点云数据处理与建模感兴趣，有<span style="color: black;">关联</span>的项目<span style="color: black;">需要</span>，或想采购实景建模软件ContextCapture，欢迎关注“艾三维技术”<span style="color: black;">微X</span>公众号，联系<span style="color: black;">咱们</span>。</span></span></p>
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