具体实施方式

下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。

以下，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征。在本公开实施例的描述中，除非另有说明，“多个”的含义是两个或两个以上。

另外，“基于”或“根据”的使用意味着开放和包容性，因为“基于”或“根据”一个或多个条件或值的过程、步骤、计算或其他动作在实践中可以基于额外条件或超出的值。

点云是一种常见的空间几何结构表达方式，通过激光雷达在获取物体表面每个采样点的空间坐标后，得到的是一个点的集合，即为“点云”。包括三维坐标、激光反射强度和颜色信息。点云在计算机视觉、自动驾驶领域等都有着广泛的应用。近年来，随着3D传感器的不断出现和发展，降低了点云数据的获取成本，获取数据也变得越来越便利。目前，自动驾驶等领域产生了对点云的数据高效存储和渲染的需求。高精地图的制作主要是依赖激光点云，通常都是海量的数据，例如，高精地图中一个路口的点云数据量就可能上亿。这就对点云数据的渲染处理提出了更高的要求。

目前，基于web端的点云渲染方法相较于基于桌面端点云渲染方法的具有兼容性好，便携性好，数据管理方便等优势。但目前基于web端的点云渲染方法只能读取预定义的数据格式的点云数据，对于其他格式的点云数据转换为预定义的数据格式，这样严重影响了点云数据的处理效率，且无法快捷实时的对点云数据进行编辑。

为了解决上述问题，本申请实施例提供的基于Web端的点云渲染方法，通过获取当前待渲染的目标场景的目标坐标范围和目标视角高度，并获取目标场景的上一渲染场景的参考坐标范围，根据目标坐标范围和参考坐标范围，确定新增坐标范围和重复坐标范围，并根据新增坐标范围和目标视角高度生成数据调用请求，向服务器发送数据调用请求，数据调用请求用于请求新增坐标范围和目标视角高度对应的新增点云数据，接收服务器发送的新增点云数据，并基于新增点云数据和预设的重复坐标范围对应的重复点云数据，生成目标场景。本申请实施例提供的基于Web端的点云渲染方法，通过根据新增坐标范围和目标视角高度从服务器中直接调用所需的点云数据，服务器中已经对点云数据进行预先解析和分类存储，这样可以提高点云数据的获取效率，进而可以提高点云的渲染效率。

如图1所示，本申请实施例提供了一种基于Web端的点云渲染方法，应用于终端设备，该方法包括以下步骤：

步骤101、获取当前待渲染的目标场景的目标坐标范围和目标视角高度，并获取目标场景的上一渲染场景的参考坐标范围。

其中，目标视角高度是指在不同高度的视角下观测目标场景，目标视角高度的数值可以用来表示距离目标场景的距离大小，当目标视角高度的数值较大，也就是距离目标场景较远时，观测到的目标场景较小；当目标视角高度的数值较小，也就是距离目标场景较近时，观测到的目标场景较大。

可以理解的是，在进行点云渲染时通常是一个连续渲染的过程，因此上一渲染场景可以理解为当前渲染操作的上一渲染操作所要渲染的场景。

可选的，可以在Web页面中通过构建三维空间体系的视椎体和控制器来监听待渲染场景的坐标范围变化，并在监听到坐标范围变化时，获取当前待渲染的目标场景的目标坐标范围和目标视角高度。

步骤102、根据目标坐标范围和参考坐标范围，确定新增坐标范围和重复坐标范围，并根据新增坐标范围和目标视角高度生成数据调用请求。

需要说明的是，在进行连续渲染操作时，通常会有重复的渲染场景，这时也就包括了重复渲染的坐标范围，因此这时可以根据当前渲染场景的目标坐标范围和上一渲染场景的参考坐标范围来确定出新增坐标范围和重复坐标范围。然后只需要获取新增坐标范围对应的点云是数据即可，不需要再调动重复坐标范围对应的点云数据，这样可以提高点云数据的获取效率。

同时，在根据当前渲染场景的目标坐标范围和上一渲染场景的参考坐标范围来确定出新增坐标范围和重复坐标范围的同时，还可能确定出了多余的坐标范围，针对多余的坐标范围可以删除该多余的坐标范围对应的点云数据。也就是说，当视锥体的视角范围再次变化时，比对下一次需要的数据和已加载数据的情况，不需要的数据进行清除，从而避免不必要的渲染开销，未加载的数据通过线程进行获取。

步骤103、向服务器发送数据调用请求，数据调用请求用于请求新增坐标范围和目标视角高度对应的新增点云数据。

其中，点云数据存储在服务器的目标数据库中，目标数据库中包括多个级别的数据标识，每个第i级数据标识指示的坐标范围由多个第（i+1）级坐标标识指示的坐标范围组成，i为正整数。

具体的，该目标数据库可以为对象-关系型数据库（PostgreSQL）。

也就是说，服务器的目标数据库包括多级索引标识，每一级索引标识用来指示对应的坐标范围。示例的，目标数据库中包括三级索引标识，其中，第一级别的索引标识，第一级别的索引标识下又包括多个第二级别的索引标识，第二级别的索引标识下又包括多个第三级别的索引标识，点云数据按照第三级别索引标识的范围，存储在对应的第三级别的索引标识下。

同时，服务器中预设了视角高度与最后一级数据标识的数量之间的映射关系，根据映射关系可以从最后一级的点云数据中向终端设备推送对应层数的点云数据。这样根据新增坐标范围和目标视角高度调用对应的新增点云数据的过程可以为：根据目标坐标范围确定对应的目标数据标识，根据目标视角高度确定最后一级数据标识的目标数量，然后确定并向终端设备推送目标数据标识的最后一级数据标识中目标数量的点云数据，这样可以提高数据的查找效率。

步骤104、接收服务器发送的新增点云数据，并基于新增点云数据和预设的重复坐标范围对应的重复点云数据进行渲染操作，生成目标场景。

终端设备在接收到服务器发送的新增点云数据后，利用新增点云数据以及终端设备中存储的重复点云数据进行渲染操作，从而得到目标场景。

可选的，上一渲染场景的参考点云数据包括对应的多个级别的数据标识，每个数据标识用于标识对应的坐标范围；

获取待渲染的目标场景的目标坐标范围和目标视角高度之前，方法还包括：获取参考点云数据的数据标识。因此，根据目标坐标范围和参考坐标范围，确定新增坐标范围和重复坐标范围的过程可以为：根据目标坐标范围和参考点云数据的数据标识，确定新增坐标范围和重复坐标范围。这样只需要将数据标识进行比对就可以确定出新增坐标范围和重复坐标范围，可以提高确定效率。

在一个实施例中，终端设备在接收服务器发送的新增点云数据之后，还包括：对新增点云数据进行解压处理，并对解压后的新增点云数据进行反序列化处理，得到中间点云数据，然后将中间点云数据以二进制的格式进行存储，得到目标新增点云数据。对应的，基于新增点云数据和预设的重复坐标范围对应的重复点云数据，生成目标场景的过程就可以为：基于目标新增点云数据和重复点云数据，生成目标场景。这样可以满足渲染程序所需的数据格式要求，并基于该格式的点云数据可以直接进行渲染操作，从而生成目标场景。

具体的，在渲染过程中，可以根据目标新增点云数据和重复点云数据得到目标点云数据，然后通过获取目标点云数据的强度信息，根据目标点云数据的强度信息得到目标点云数据的对应的像素值，最后根据目标点云数据的坐标数据和像素值，生成目标场景。这样根据点云数据的强度信息就可以生成对应的像素值，用于区别渲染得到的物体即可，不需要再获取实际物体的像素值，可以简化数据采集过程。

如图2所示，本申请实施还提供了一种基于Web端的点云渲染方法，应用于服务器，该方法包括：

步骤201、接收终端设备发送的数据调用请求。

其中，数据调用请求中包括新增坐标范围和目标视角高度。

步骤202、根据新增坐标范围和目标视角高度中调用对应的新增点云数据。

步骤203、向终端设备发送新增点云数据。

可选的，接收终端设备发送的数据调用请求之前还包括：获取多个初始点云文件，其中，初始点云文件包括不同的文件格式，对初始点云文件进行解析，得到各初始点云文件中的点云数据，并将各点云数据存储至目标数据库中。

可以理解的是，通过采集装置采集得到点云数据文件可能为各种不同的文件格式，因此需要对采集到的初始点云文件进行解析，得到各初始点云文件中的点云数据，并将点云数据存储至目标数据库中，用于终端设备的调用渲染。

具体的，目标数据库中包括多个级别的数据标识，每个第i级数据标识指示的坐标范围由多个第（i+1）级坐标标识指示的坐标范围组成，i为正整数；因此，将各点云数据存储至目标数据库中的过程可以为：根据各数据标识对应的坐标范围，将获取到的点云数据存储至目标数据库中。

也就是说，服务器的目标数据库包括多级索引标识，每一级索引标识用来指示对应的坐标范围。示例的，目标数据库中包括三级索引标识，其中，第一级别的索引标识，第一级别的索引标识下又包括多个第二级别的索引标识，第二级别的索引标识下又包括多个第三级别的索引标识，点云数据按照第三级别索引标识的范围，存储在对应的第三级别的索引标识下。

可选的，服务器中还存储有每个视角高度对应的最后一级数据标识的数量；

对应的，根据新增坐标范围和目标视角高度从目标数据库中调用对应的新增点云数据，包括：根据目标坐标范围确定对应的目标数据标识，根据目标视角高度确定最后一级数据标识的目标数量，调用目标数据标识的最后一级数据标识中目标数量的点云数据。

在一个实施例中，服务器还会对目标数据库中包括的点云数据压缩后存储至缓存空间中。对应的，服务器向终端设备发送新增点云数据的过程可以为：从缓存空间中，通过多线程向终端设备发送新增点云数据。通过将点云数据压缩后存储至缓存空间，且利用多线程的方式向终端设备发送点云数据，可以提高点云数据的发送效率。

具体的，该缓存空间可以为redis数据库，Redis（Remote Dictionary Server )，即远程字典服务，是一个开源的使用ANSI C语言编写、支持网络、可基于内存亦可持久化的日志型、Key-Value数据库，并提供多种语言的API。

为了便于本领域技术人员的理解，本申请实施例还提供了一种压差传感器的故障检测方法，具体的，该方法包括：

（1）服务器获取多个初始点云文件，初始点云文件包括不同的文件格式；

（2）服务器对初始点云文件进行解析，得到各初始点云文件中的点云数据，并将各点云数据存储至目标数据库中。

（3）服务器根据各数据标识对应的坐标范围，将获取到的点云数据存储至目标数据库中。

（4）服务器对目标数据库中包括的点云数据压缩后存储至缓存空间中；

（5）终端设备获取参考点云数据的数据标识；

（6）终端设备获取当前待渲染的目标场景的目标坐标范围和目标视角高度，并获取目标场景的上一渲染场景的参考坐标范围；

（7）终端设备根据目标坐标范围和参考点云数据的数据标识，确定新增坐标范围和重复坐标范围。

（8）终端设备根据新增坐标范围和目标视角高度生成数据调用请求；

（9）终端设备向服务器发送数据调用请求，数据调用请求用于请求新增坐标范围和目标视角高度对应的新增点云数据；

（10）服务器接收终端设备发送的数据调用请求，数据调用请求中包括新增坐标范围和目标视角高度；

（11）服务器根据新增坐标范围和目标视角高度中调用对应的新增点云数据；

（12）服务器从缓存空间中，通过多线程向终端设备发送新增点云数据。

（13）接收服务器发送的新增点云数据，

（14）对新增点云数据进行解压处理，并对解压后的新增点云数据进行反序列化处理，得到中间点云数据；

（15）基于目标新增点云数据和重复点云数据进行渲染操作，生成目标场景。

本申请实施例提供的基于Web端的点云渲染方法，通过获取当前待渲染的目标场景的目标坐标范围和目标视角高度，并获取目标场景的上一渲染场景的参考坐标范围，根据目标坐标范围和参考坐标范围，确定新增坐标范围和重复坐标范围，并根据新增坐标范围和目标视角高度生成数据调用请求，向服务器发送数据调用请求，数据调用请求用于请求新增坐标范围和目标视角高度对应的新增点云数据，接收服务器发送的新增点云数据，并基于新增点云数据和预设的重复坐标范围对应的重复点云数据，生成目标场景。本申请实施例提供的基于Web端的点云渲染方法，通过根据新增坐标范围和目标视角高度从服务器中直接调用所需的点云数据，服务器中已经对点云数据进行预先解析和分类存储，这样可以提高点云数据的获取效率，进而可以提高点云的渲染效率。

通过对不同大小数据的图幅测试，针对10GB，20GB，30GB等大小的一幅点云数据分别执行上述流程，在8核处理器，4g独显的机器配置下，可以达到流畅渲染的效果。在千兆宽带下，点云通过websocket通信协议的传输处理渲染可以达到100m/s。可同时支持上亿个点的点云数据加载，同时通过渲染调度策略可以对大数据的点云图幅数据进行加载。根据对一幅20G大小的点云图幅数据加载，在web浏览器端可以达到60fps的帧率，对于比较密集的路口，也能达到30fps以上的稳定帧率加载，同时支持在渲染的图幅数据中进行绘制，编辑等操作。如图3所示，采用本申请实施例提供的基于Web端的点云渲染方法的实际渲染效果示意图。

同时，本申请实施例提供的Web端的点云渲染方法，在进行渲染过程中，直接将所有点云数据存入数据库，存储后可基于web端实现海量点云实时渲染，同时满足基于渲染的其他编辑扩展能力。且，由于点云数据是存储在数据库中的，因此可以实时快捷的对点云数据进行编辑，同时可以随时随地对点云数据进行访问，且数据具有共享性，任意一个符合要求的终端设备的浏览器即可通过访问服务器来获取到所需的点云数据。

如图4所示，本申请实施例还提供了一种基于Web端的点云渲染系统，该系统包括：终端设备10和服务器20。具体的，对于该终端设备10和服务器20可以执行上述方法实施例，其实现原理和技术效果与上述方法实施例类似，在此不再多加赘述。其实现原理和技术效果类似，在此不再多加赘述。

本申请另一实施例中，还提供一种计算机可读存储介质，其上存储有计算机程序，计算机程序被处理器执行时实现如本申请实施例的基于Web端的点云渲染方法的步骤。

本申请另一实施例中，还提供一种计算机程序产品，该计算机程序产品包括计算机指令，当计算机指令在终端设备或者服务器中运行时，使得终端设备或者服务器执行上述方法实施例所示的方法流程中基于Web端的点云渲染方法执行的各个步骤。

在上述实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件程序实现时，可以全部或部分地以计算机程序产品的形式来实现。该计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行计算机执行指令时，全部或部分地产生按照本申请实施例的流程或功能。计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，计算机指令可以从一个网站站点、计算机、服务器或者数据中心通过有线（例如同轴电缆、光纤、数字用户线（digitalsubscriber line，DSL））或无线（例如红外、无线、微波等）方式向另一个网站站点、计算机、服务器或数据中心进行传输。计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可以用介质集成的服务器、数据中心等数据存储设备。可用介质可以是磁性介质（例如，软盘、硬盘、磁带），光介质（例如，DVD）、或者半导体介质（例如固态硬盘（solid state disk，SSD））等。

以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。

以上实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Specific embodiments

The following will be combined with the drawings in the embodiment of the present application, the technical solution in the embodiment of the present application is clearly and completely described, it is clear that the embodiment described is only a part of the embodiment of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without the premise of creative labor are within the scope of the present application.

Hereinafter, the terms "first", "second" are for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features limited to "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present disclosure embodiment, unless otherwise indicated, "multiple" means two or more.

In addition, the use of "based on" or "based on" implies openness and inclusiveness, because a process, step, calculation, or other action that is "based on" or "based on" one or more conditions or values may in practice be based on additional conditions or values that exceed them.

Point cloud is a common expression of spatial geometry, through the lidar to obtain the spatial coordinates of each sample point on the surface of the object, the result is a collection of points, that is, "point cloud". Includes 3D coordinates, laser reflection intensity, and color information. Point cloud has a wide range of applications in the field of computer vision and automatic driving. In recent years, with the continuous emergence and development of 3D sensors, the cost of obtaining point cloud data has been reduced, and the acquisition of data has become more and more convenient. At present, areas such as autonomous driving have created a demand for efficient storage and rendering of data from point clouds. The production of HIGH-precision maps mainly relies on laser point clouds, which are usually massive amounts of data, for example, the amount of point cloud data at an intersection in a high-precision map may be hundreds of millions. This puts forward higher requirements for the rendering processing of point cloud data.

At present, the web-based point cloud rendering method has the advantages of good compatibility, portability and convenient data management compared with the desktop endpoint cloud rendering method. However, at present, the web-based point cloud rendering method can only read the point cloud data in a predefined data format, and the point cloud data in other formats is converted into a predefined data format, which seriously affects the processing efficiency of the point cloud data, and the point cloud data cannot be edited quickly and real-time.

In order to solve the above problems, the present application embodiment provides a web-based point cloud rendering method, by obtaining the target coordinate range and target viewing angle height of the current target scene to be rendered, and obtaining the reference coordinate range of the previous rendered scene of the target scene, according to the target coordinate range and reference coordinate range, determine the new coordinate range and the repeating coordinate range, and generate a data call request according to the new coordinate range and the target viewing angle height, send a data call request to the server, The data call request is used to request the new point cloud data corresponding to the new coordinate range and the height of the target viewing angle, receive the new point cloud data sent by the server, and generate the target scene based on the new point cloud data and the duplicate point cloud data corresponding to the preset repeating coordinate range. Embodiment of the present application provides a web-based point cloud rendering method, by directly calling the desired point cloud data from the server according to the new coordinate range and target viewing angle height, the server has been pre-parsed and classified storage of point cloud data, which can improve the acquisition efficiency of point cloud data, and thus can improve the rendering efficiency of point cloud.

As shown in FIG. 1, the present application embodiment provides a web-based point cloud rendering method, applied to the terminal device, the method comprising the following steps:

Step 101, obtain the target coordinate range and target viewing angle height of the target scene to be rendered, and obtain the reference coordinate range of the previous rendered scene of the target scene.

Among them, the target perspective height refers to the observation of the target scene under different heights of the perspective, the value of the target perspective height can be used to indicate the distance from the target scene, when the value of the target perspective height is larger, that is, when the target scene is farther away, the observed target scene is smaller; When the value of the height of the target perspective is small, that is, closer to the target scene, the observed target scene is larger.

Understandably, point cloud rendering is usually a continuous rendering process, so the previous rendered scene can be understood as the scene to be rendered by the previous render operation of the current render operation.

Optionally, you can monitor the coordinate range of the scene to be rendered by building the visual vertebra and controller of the three-dimensional spatial system in the Web page, and obtain the target coordinate range and target viewing angle height of the current target scene to be rendered when the coordinate range change is heard.

Step 102, according to the target coordinate range and reference coordinate range, determine the new coordinate range and duplicate coordinate range, and generate a data call request according to the new coordinate range and the target viewing angle height.

It should be noted that when performing continuous rendering operations, there will usually be duplicate rendering scenes, which also includes the coordinate range of repeated rendering, so the new coordinate range and duplicate coordinate range can be determined according to the target coordinate range of the current rendered scene and the reference coordinate range of the previous rendered scene. Then you only need to obtain the point cloud corresponding to the new coordinate range is the data, and there is no need to mobilize the point cloud data corresponding to the repeated coordinate range, which can improve the acquisition efficiency of the point cloud data.

At the same time, while determining the new coordinate range and the duplicate coordinate range according to the target coordinate range of the current rendered scene and the reference coordinate range of the previous rendered scene, the excess coordinate range may also be determined, and the point cloud data corresponding to the excess coordinate range can be deleted for the excess coordinate range. That is to say, when the viewing angle range of the cone changes again, comparing the next time the data needed and the loaded data, the unwanted data is cleared, thus avoiding unnecessary rendering overhead, and the unloaded data is obtained through the thread.

Step 103, send a data call request to the server, the data call request is used to request the new coordinate range and the target viewing angle height corresponding to the new point cloud data.

Wherein, the point cloud data is stored in the target database of the server, the target database includes multiple levels of data identification, each level i data identification indicates the coordinate range by a plurality of (i + 1) level coordinate identification indicated by the coordinate range, i is a positive integer.

Specifically, the target database may be an object-relational database (PostgreSQL).

That is, the target database of the server includes a multi-level index ID, each of which is used to indicate the corresponding coordinate range. For example, the target database includes a three-level index identification, wherein the first level of index identification, the first level of index identification includes a plurality of second-level index identification, the second level of index identification includes a plurality of third-level index identification, point cloud data in accordance with the scope of the third level index identification, stored under the corresponding third-level index identity.

At the same time, the server presets the mapping relationship between the viewing angle height and the number of data identifications of the last level, and the point cloud data of the corresponding number of layers can be pushed from the point cloud data of the last level to the terminal device according to the mapping relationship. In this way, the process of invoking the corresponding new point cloud data according to the new coordinate range and the target perspective height can be: the corresponding target data identification is determined according to the target coordinate range, the target number of the last level of data identification is determined according to the target perspective height, and then the point cloud data in the target number of the target data identification in the last level of the target data identification is determined and pushed to the terminal device, which can improve the data search efficiency.

Step 104, receive the new point cloud data sent by the server, and render the new point cloud data and the duplicate point cloud data corresponding to the preset repeat coordinate range to generate the target scene.

After the terminal device receives the new point cloud data sent by the server, it uses the new point cloud data and the duplicate point cloud data stored in the terminal device to render the target scene.

Optionally, the reference point cloud data of the previous rendered scene includes a corresponding plurality of levels of data identifiers, each data identifier is used to identify the corresponding coordinate range;

Before getting the target coordinate range and target viewing angle height of the target scene to be rendered, you can also obtain the data identification of the reference point cloud data. Therefore, based on the target coordinate extent and the reference coordinate extent, the process of determining the new coordinate range and the duplicate coordinate range can be: based on the target coordinate extent and the data identification of the reference point cloud data, the new coordinate range and the duplicate coordinate range are determined. In this way, only the data identification needs to be compared to determine the new coordinate range and the duplicate coordinate range, which can improve the determination efficiency.

In one embodiment, after receiving the new point cloud data transmitted by the server, the terminal apparatus further comprises: decompressing the new point cloud data, deserializing the new point cloud data after decompression, obtaining the intermediate point cloud data, and then storing the intermediate point cloud data in binary format to obtain the target new point cloud data. Correspondingly, based on the new point cloud data and the duplicate point cloud data corresponding to the preset repeating coordinate range, the process of generating the target scene can be: based on the new point cloud data and duplicate point cloud data of the target, the target scene is generated. This satisfies the data format requirements required by the renderer, and the point cloud data based on this format can be rendered directly, resulting in the target scene.

Specifically, in the rendering process, the target point cloud data can be obtained according to the target new point cloud data and repeated point cloud data, and then by obtaining the intensity information of the target point cloud data, the corresponding pixel values of the target point cloud data are obtained according to the intensity information of the target point cloud data, and finally the target scene is generated according to the coordinate data and pixel values of the target point cloud data. In this way, the corresponding pixel values can be generated according to the intensity information of the point cloud data, which can be used to distinguish the objects obtained by rendering, and there is no need to obtain the pixel values of the actual objects, which can simplify the data acquisition process.

As shown in FIG. 2, the present application embodiment also provides a web-based point cloud rendering method, applied to the server, the method comprising:

Step 201, receiving a data call request sent by the terminal device.

The data call request includes the new coordinate range and target viewing angle height.

Step 202, according to the new coordinate range and target viewing angle height in the corresponding new point cloud data.

Step 203, send the new point cloud data to the terminal device.

Optionally, before receiving the data call request sent by the terminal device further comprises: obtaining a plurality of initial point cloud files, wherein the initial point cloud file includes different file formats, parsing the initial point cloud file, obtaining the point cloud data in each initial point cloud file, and storing each point cloud data in the target database.

It is understandable that the point cloud data file collected by the acquisition device may be a variety of different file formats, so it is necessary to parse the initial point cloud file collected, obtain the point cloud data in each initial point cloud file, and store the point cloud data in the target database for the invocation rendering of the terminal device.

Specifically, the target database includes multiple levels of data identification, each level i data identification indicates the coordinate range by a plurality of (i + 1) level coordinate identification indicated by the coordinate range, i is a positive integer; Therefore, the process of storing each point cloud data in the target database can be: according to the corresponding coordinate range of each data, the obtained point cloud data is stored in the target database.

That is, the target database of the server includes a multi-level index ID, each of which is used to indicate the corresponding coordinate range. For example, the target database includes a three-level index identification, wherein the first level of index identification, the first level of index identification includes a plurality of second-level index identification, the second level of index identification includes a plurality of third-level index identification, point cloud data in accordance with the scope of the third level index identification, stored under the corresponding third-level index identity.

Optionally, the server also stores the number of last level data identifiers corresponding to the height of each viewing angle;

Correspondingly, the corresponding new point cloud data is called from the target database according to the new coordinate range and the target viewing angle height, including: determining the corresponding target data identification according to the target coordinate range, determining the target number of the last level of data identification according to the target perspective height, and calling the target cloud data in the target data identification of the last level of data identification.

In one embodiment, the server will also compress the point cloud data included in the target database and store it in the cache space. Correspondingly, the process of the server sending new point cloud data to the terminal device can be: from the cache space, the new point cloud data is sent to the terminal device through multi-threading. By compressing the point cloud data and storing it in the cache space, and using multithreading to send point cloud data to the terminal device, the transmission efficiency of point cloud data can be improved.

Specifically, the cache space can be a redis database, Redis (Remote Dictionary Server), or remote dictionary service, which is an open source log database written in anSI C language, supported by the network, memory-based and persisted, key-Value database, and provides API in multiple languages.

In order to facilitate the understanding of those skilled in the art, the present application embodiment also provides a fault detection method for differential pressure sensor, specifically, the method comprising:

(1) The server obtains multiple initial point cloud files, and the initial point cloud files include different file formats;

(2) The server parses the initial point cloud file, obtains the point cloud data in each initial point cloud file, and stores each point cloud data in the target database.

(3) The server stores the obtained point cloud data in the target database according to the corresponding coordinate range of each data identification.

(4) The server compresses the point cloud data included in the target database and stores it in the cache space;

(5) The terminal device obtains the data identification of the reference point cloud data;

(6) The terminal device obtains the target coordinate range and target viewing angle height of the current target scene to be rendered, and obtains the reference coordinate range of the previous rendered scene of the target scene;

(7) The terminal device determines the new coordinate range and the duplicate coordinate range according to the target coordinate range and the data identification of the reference point cloud data.

(8) The terminal device generates a data call request according to the new coordinate range and the height of the target viewing angle;

(9) The terminal device sends a data call request to the server, and the data call request is used to request the new point cloud data corresponding to the coordinate range and the height of the target perspective;

(10) The server receives the data call request sent by the terminal device, and the data call request includes the new coordinate range and the target viewing angle height;

(11) The server calls the corresponding new point cloud data according to the new coordinate range and target viewing angle height;

(12) The server sends new point cloud data to the terminal device through multi-threading from the cache space.

(13) Receive the new point cloud data sent by the server,

(14) Decompress the newly added point cloud data, and deserialize the newly added point cloud data after the extraction to obtain the intermediate point cloud data;

(15) Render the new point cloud data and duplicate point cloud data based on the target to generate the target scene.

The point cloud rendering method based on the Web end provided in the embodiment of the present application, by obtaining the target coordinate range and target viewing angle height of the current target scene to be rendered, and obtaining the reference coordinate range of the previous rendered scene of the target scene, according to the target coordinate range and reference coordinate range, determining the new coordinate range and the repeating coordinate range, and generating a data call request according to the new coordinate range and the target perspective height, sending a data call request to the server, The data call request is used to request the new point cloud data corresponding to the new coordinate range and the height of the target viewing angle, receive the new point cloud data sent by the server, and generate the target scene based on the new point cloud data and the duplicate point cloud data corresponding to the preset repeating coordinate range. Embodiment of the present application provides a web-based point cloud rendering method, by directly calling the desired point cloud data from the server according to the new coordinate range and target viewing angle height, the server has been pre-parsed and classified storage of point cloud data, which can improve the acquisition efficiency of point cloud data, and thus can improve the rendering efficiency of point cloud.

Through the image frame test of different sizes of data, the above process is performed for a point cloud data of 10GB, 20GB, 30GB and other sizes, and the smooth rendering effect can be achieved under the 8-core processor and 4G unique machine configuration. Under gigabit broadband, the transmission processing rendering of the point cloud through the websocket communication protocol can reach 100m/s. It can support the loading of point cloud data of hundreds of millions of points at the same time, and the point cloud map data of big data can be loaded through the rendering scheduling strategy. According to the loading of a 20G-sized point cloud image frame data, the frame rate of 60fps can be reached on the web browser side, and for more dense intersections, it can also reach a stable frame rate loading of more than 30fps, and at the same time support drawing, editing and other operations in the rendered image frame data. As shown in FIG. 3, the embodiment of the present application provides a schematic diagram of the actual rendering effect of the web-based point cloud rendering method.

At the same time, the point cloud rendering method provided by the present application embodiment, during the rendering process, all point cloud data is directly stored in the database, and the massive point cloud real-time rendering can be realized based on the web side after storage, while meeting the requirements of other editing extension capabilities based on rendering. Moreover, because the point cloud data is stored in the database, the point cloud data can be edited quickly and in real time, and the point cloud data can be accessed anytime and anywhere, and the data is shared, and the browser of any terminal device that meets the requirements can access the required point cloud data by accessing the server.

As shown in FIG. 4, the present application embodiment further provides a web-based point cloud rendering system, the system comprising: a terminal device 10 and a server 20. Specifically, for the terminal apparatus 10 and server 20 may perform the above method embodiment, its implementation principle and technical effect is similar to the above method embodiment, and will not be repeated here. Its implementation principle and technical effect are similar, and it will not be repeated here.

In another embodiment of the present application, there is also a computer-readable storage medium on which a computer program is stored, the computer program is executed by the processor to implement the steps of a web-based point cloud rendering method such as the embodiment of the present application.

In another embodiment of the present application, there is also a computer program product, the computer program product comprising a computer instruction, when the computer instruction is run in a terminal device or server, such that the terminal device or server performs the method flow shown in the above method embodiment in the web-based point cloud rendering method performs each step.

In the above embodiments, it may be achieved in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using a software program, it may be implemented in whole or in part in the form of a computer program product. This computer program product includes one or more computer instructions. When loading and executing computer execution instructions on a computer, all or partly generate a process or function in accordance with the embodiments of the present application. The computer may be a general purpose computer, a dedicated computer, a computer network, or other programmable device. Computer instructions may be stored in a computer-readable storage medium, or from a computer-readable storage medium to another computer-readable storage medium transmission, e.g., computer instructions may be transmitted from a website site, computer, server or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) to another website site, computer, The server or data center makes the transfer. A computer-readable storage medium may be any available media that the computer can access or a data storage device that contains one or more servers, data centers, and other data storage devices that can be integrated with the media. Available media can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid state disks (SSDs)) and the like.

The technical features of the above embodiments may be arbitrarily combined, in order to make the description concise, not all possible combinations of each of the technical features in the above embodiments are described, however, as long as the combination of these technical features does not contradictory, it should be considered to be the scope of the present specification.

The above embodiments only express several embodiments of the present application, the description of which is more specific and detailed, but can not therefore be understood as a limitation on the scope of the invention patent. It should be noted that, for those of ordinary skill in the art, without departing from the concept of the present application, a number of deformations and improvements may also be made, which fall within the scope of protection of the present application. Therefore, the scope of protection of the patent in this application shall be subject to the appended claims.