CN111696162B - Binocular stereo vision fine terrain measurement system and method - Google Patents

Binocular stereo vision fine terrain measurement system and method Download PDF

Info

Publication number
CN111696162B
CN111696162B CN202010529424.2A CN202010529424A CN111696162B CN 111696162 B CN111696162 B CN 111696162B CN 202010529424 A CN202010529424 A CN 202010529424A CN 111696162 B CN111696162 B CN 111696162B
Authority
CN
China
Prior art keywords
image
vision
calibration
binocular
coordinate
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010529424.2A
Other languages
Chinese (zh)
Other versions
CN111696162A (en
Inventor
班云云
徐锡蒙
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Institute of Geographic Sciences and Natural Resources of CAS
Original Assignee
Institute of Geographic Sciences and Natural Resources of CAS
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Institute of Geographic Sciences and Natural Resources of CAS filed Critical Institute of Geographic Sciences and Natural Resources of CAS
Priority to CN202010529424.2A priority Critical patent/CN111696162B/en
Publication of CN111696162A publication Critical patent/CN111696162A/en
Application granted granted Critical
Publication of CN111696162B publication Critical patent/CN111696162B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/02—Picture taking arrangements specially adapted for photogrammetry or photographic surveying, e.g. controlling overlapping of pictures
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/04—Interpretation of pictures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/55—Depth or shape recovery from multiple images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10028—Range image; Depth image; 3D point clouds

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • Data Mining & Analysis (AREA)
  • Remote Sensing (AREA)
  • General Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Databases & Information Systems (AREA)
  • Evolutionary Computation (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Artificial Intelligence (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Quality & Reliability (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Image Processing (AREA)

Abstract

The invention provides a binocular stereo vision fine terrain measurement system and a method thereof. And the binocular Vision camera is used for establishing connection with NI-MAX configuration management software through a GigE Vision digital interface, providing communication support between software and hardware equipment for an NI-IMAQ image acquisition and processing system of a LabVIEW development test strip, and completing High-Speed High-resolution image acquisition and processing. The method comprises the steps of setting a gravity sensing device to determine the vertical direction, utilizing a GPS (global positioning system) positioner to achieve acquisition of depth images and determination of longitude and latitude of shooting points, and then establishing a coordinate conversion relation to achieve coordinate conversion. The invention realizes the dynamic process measurement, real-time monitoring, remote transmission and multi-user data sharing of the high-precision topographic map.

Description

Binocular stereo vision fine terrain measurement system and method
Technical Field
The invention relates to the technical field of topographic survey, in particular to a binocular stereoscopic vision fine topographic survey system and method.
Background
The rapid and fine dynamic monitoring of the landform is an important data basis and difficulty of various scientific researches on the surface layer of the land, and the accurate acquisition of the landform data has important significance for knowing the change process and reasons of the landform of the drainage basin. Under the background condition of global climate change, the water and soil loss problem taking the hydraulic action as the driving force is increasingly serious, causes land degradation, ecological imbalance, frequent drought and flood disasters and silting downstream riverways, has serious local effect and allopatric effect, and in addition, frequent natural disasters such as landslide, debris flow and the like directly threaten the life and property safety of people in a drainage basin. The fine terrain acquisition is not only beneficial to rapidly acquiring slope water and soil loss monitoring, but also can be applied to landslide body ground gap monitoring, collapse and falling object distribution characteristics, river channel deformation, debris flow dynamic monitoring and the like, the fine terrain monitoring can provide technical support and help for recognizing the landscapes evolution process and building a reasonable natural disaster (landslide, debris flow and the like) early warning and prevention system, and has important significance for social sustainable development (Montanarella and Vargas, 2012).
Ground large-scale terrain measurement often depends on technologies such as remote sensing and unmanned aerial vehicles, but is different from large-scale terrain monitoring, and centimeter-level fine terrain measurement needs a more precise instrument. In the field topography monitoring, the monitoring of the form change of a surface gully is the main content, and the monitoring is mainly used for obtaining a Digital Elevation Model (DEM) of the topography based on field measurement or remote sensing products. The traditional measuring rule method or the terrain probe method can roughly acquire rough terrain features of a measured area, but wastes time and labor and cannot acquire high-precision terrain data, the current research requirement on the terrain and landform evolution of a drainage basin cannot be met, and a new method and a new technology need to be developed by combining modern science and technology. In making field measurements, precision measurement equipment is often required, such as total stations, high precision satellite system (GNSS) receivers, laser profilometers, etc. (Castillo et al, 2012), which are often not readily available or expensive, and furthermore, terrain variations and changes in the deposition process require intensive XYZ coordinate data, typically acquired by ground laser scanning (TLS) (peroy et al, 2012) or Airborne Laser Scanning (ALS) (heredity and Hetherington, 2007). TLS is highly accurate but requires small-scale use on the ground and is therefore somewhat limited, ALS typically does not accurately capture small-area terrain (Perroy et al, 2010), but can quickly acquire large-scale terrain data, limiting its use in most surveillance projects in terms of cost and feasibility (table 1). The high-precision GPS (RTK) technology is a modern measurement method for processing differential signals of carrier phases of two measuring stations in real time and realizing centimeter-level three-dimensional positioning precision through wireless signal transmission of a base station and a rover receiver. The technology is high in precision and is not affected by severe weather, so that the technology is valued and popular by field topographic survey workers, but the method requires a surveyor to touch each measuring position during the operation process, which is difficult to achieve in a topographic complex area, so that the application range is limited (Table 1). For remote sensing products to acquire terrain data, such as aerial photographs and satellite images, a high-resolution DEM (Gim renz et al, 2009) needs to be acquired with high accuracy, and although the acquisition mode of high-resolution images (resolution is <1m) is more and more, the acquisition of stereoscopic view images needs a large amount of capital, and the accuracy of the terrain data acquired based on the method is not enough to finely simulate terrain changes, so that a more appropriate method needs to be found to quickly and finely acquire the terrain change data.
TABLE 1 comparison of common topographical measurement instruments
Figure BDA0002534696080000021
With the development of modern photography techniques, researchers have conducted meaningful research in obtaining fine topographic data from stereo photogrammetry. The photogrammetry technology is used for interactively compiling the mutually overlapped parts of a plurality of photographic images to finally obtain the DEM. Ground or aerial image modeling based on the same surface is an important direction of photogrammetry, multi-view stereoscopic workflows (SFM-MVS) of semi-automated structures (Seitz et al, 2006; verhoven et al, 2012; Javernick et al, 2014) are gradually developed and integrated in photogrammetry software, such as Photoscan software developed by Agisoft, and the modeling of objects or topographic features by this research method can be increasingly applied for research in earth science by combining with remote control airships (Marzolff and Poesen,2009) or on-board (Frankl et al, 2015) in view of their low cost and flexible nature (corban et al, 2008; Hendrickx et al, 2011; Lucieer et al, 2014; Peter et al, 2014). For example, image-based terrain modeling has been used to generate accurate models of historical spheres (Stal et al, 2012), buildings (Stal et al, 2011), gullies (Castillo et al, 2012; G Lo mez-Guti é rrez et al, 2014; Kaiser et al, 2014), terrain (James and Robson, 2012; Qin et al, 2019), even special landscapes (Verhoeven et al, 2012), and so on.
However, most of the current fine terrain research related to photogrammetry is mostly based on monocular distance measurement principle to obtain two-dimensional plane images, and then the two-dimensional plane images are carried out in a 2.5D environment, so that the terrain information needs to be calibrated by using targets and the overlapping rate is ensured, the measurement range is limited, and the post-processing time is long. This results in a low automation standard for the measurement, too strong human intervention and a low working efficiency of the measurement. The binocular stereo vision measurement is based on a parallax principle, a left image and a right image which are collected by a system are matched and calculated through a block matching algorithm to generate left and right parallax images, then a depth image is calculated according to the parallax images, and the three-dimensional coordinates of a measured point are obtained through a triangular geometric relation. Therefore, any point in the space can be known to be in the corresponding coordinate, and the reconstruction of the space point can be carried out. The binocular stereo vision measurement has a wide spectral response range, and can be used for finely measuring the change of landform by combining spectral characteristics (such as landslide, erosion and humidity) of the ground features and ranging information. The measuring method belongs to non-contact measurement, can be used for complex terrains or dangerous (landslide) areas, can also carry out long-time monitoring, analyzing and identifying tasks, is relatively simple in system and low in cost, and is worthy of discussion on application in fine terrain measurement.
When the binocular stereoscopic vision photogrammetry is applied to the measurement of a fine topographic map, the binocular stereoscopic vision photogrammetry technology can acquire the three-dimensional morphological characteristics of an object, but cannot acquire topographic characteristic information quickly, so the following problems still need to be solved: 1. how to determine three-dimensional morphological features of a ground object to be measured in a topographic survey? 2. How does one achieve a transformation from the image pixel coordinate system to the world coordinate system? 3. How to process the acquired images to quickly generate topographic point cloud data and a visual topographic map?
Disclosure of Invention
The invention aims to solve the problem that when binocular stereoscopic vision photogrammetry in the prior art is applied to measurement of a fine topographic map, the binocular stereoscopic vision photogrammetry technology can acquire three-dimensional morphological characteristics of an object but cannot acquire topographic characteristic information quickly. The invention provides a binocular stereoscopic vision photogrammetry system and a method thereof, strives to realize market promotion of the measurement system, and provides scientific basis for measuring three-dimensional target coordinates and related research.
In order to solve the above technical problem, a first aspect of the present invention provides a binocular stereo vision fine terrain measurement system, including:
the electric appliance cabinet is used for protecting each component in the electric appliance cabinet;
a power supply, a hardware device, a communication part, a software data processing module and a coordinate system conversion processing program are arranged in the electric appliance cabinet;
the hardware device and the communication part are used for image, longitude and latitude acquisition and data transmission; the hardware device and the communication part comprise a GigE industrial camera, an embedded computer vision system (EVS), a 5G transmission terminal, a power supply system, a stepping motor, a driver, an encoder and eight infrared sensors; the stepping motor is used for providing power output for the movement of the measuring system, and the control driver and the encoder are combined with an NI-VISA program interface provided by a LabVIEW development platform through a serial port communication technology to realize the remote digital closed-loop control of the measuring system; the encoder is coaxially connected with the stepping motor and used for digital closed-loop control of the mobile measuring system; the eight infrared sensors are arranged on one side of the electric appliance cabinet in a diagonal manner, and the electric appliance cabinet is stopped at different slope positions due to the triggering of different infrared sensors;
the software data processing module is used for converting the shot image into three-dimensional point cloud data based on the machine vision technology of a LabVIEW platform, but does not have topographic features; the software data processing module comprises a binocular Vision camera and is used for establishing connection with NI-MAX configuration management software through a GigE Vision digital interface, providing communication support between software and hardware equipment for an NI-IMAQ image acquisition and processing system of a LabVIEW development certificate, and completing High-Speed High-resolution image acquisition and processing;
the coordinate system conversion processing program is used for converting the depth image pixel coordinate system into a world coordinate system, establishing a coordinate conversion relation and realizing coordinate conversion; the coordinate system conversion processing program comprises an embedded computer vision system, wherein the embedded computer vision system is connected with the binocular vision camera through an interface and is connected with the stepping motor controller and the digital input module through serial port communication;
all module functions are integrated, the size of the ground object is measured, and high-precision topographic survey data with longitude and latitude information are obtained in real time.
Optionally, the binocular vision camera is composed of two giga cameras and is used for acquiring images of the slope surface morphology.
The invention provides a binocular stereoscopic vision fine terrain measurement method, which uses the binocular stereoscopic vision fine terrain measurement system to estimate the terrain, and comprises the following steps:
step 1, calibrating a system,
the calibration procedure for the binocular vision camera requires a white calibration plate printed with 70 (10 × 7) black solid circles, all 4cm apart and 2cm in diameter. The binocular vision cameras are determined to be horizontally fixed before calibration and not to be moved or to change the relative positions between the cameras after calibration. The calibration result shows that the maximum relative error is 0.72 percent, and the minimum relative error is 0.10 percent;
the calibration procedure required a calibration device with 70 (10 × 7) black solid dots printed on a white background, each black solid dot having a diameter of 2cm and the distance between the centers of each two solid dots being 4 cm; the field of view of the cameras is divided into 9 units on average to determine the distance between the two cameras and the distortion coefficient; the calibration plate needs to be completely present in the first calibration image acquired by the two cameras, and then the calibration plate needs to cover all units in the camera field of view at different positions and different angles; finally, when all the calibration images cover the whole visual field of the two cameras, the tangential and radial distortion is corrected by the formula (1) and the formula (2), wherein the formula is as follows:
Figure BDA0002534696080000051
Figure BDA0002534696080000052
Figure BDA0002534696080000053
in the formula X1,X2,Y1,Y2Is the coordinate coefficient of the corrected image; (x, y) are the coordinate coefficients of the original image; r isx,ryAre focal lengths in different directions; m is a correction coefficient for radial distortion; t is1,T2Is a correction factor for tangential distortion.
Step 2, image acquisition, including developing a machine vision application program on a LabVIEW platform in combination with a VDM vision development module, and deploying the developed application program to a Windows or Linux real-time operating system to build an image acquisition system; images acquired by the system are automatically classified according to the acquisition time and stored in corresponding folders and MySQL databases, and the databases are combined with a LabVIEW platform through a database connection tool kit, so that the operation of the databases on the platform can be executed;
step 3, image analysis, wherein a machine vision module in a LabVIEW operation platform processes and analyzes the acquired image; in order to obtain better channel profile and more accurate channel image data; matching and calculating a left image and a right image acquired by a left digital industrial camera and a right digital industrial camera in an image acquisition system through a block matching algorithm to generate left and right parallax images; calculating a depth image according to the parallax image; the method comprises the steps of extracting a channel profile from a depth image by adopting an image subtraction method, binary image corrosion, particle removal and filling functions in a VDM visual development module, then carrying out particle analysis on the extracted channel profile, calculating a value of the sum of particles of the channel image of the profile, displaying the value on a reconstructed image after processing and analysis, extracting and classifying feature point data in the image, and establishing an estimation model of an image feature point data set and a measurement target size. From this it is possible to calculate the dimensions of the object to be measured and to determine the three-dimensional coordinates of any point in the image.
And 4, coordinate conversion, namely developing a coordinate conversion software system based on a machine vision technology of a LabVIEW platform, determining the three-dimensional coordinates of the monitoring target, and determining the coordinates of each point of the measured object on the ground. The coordinate conversion can be determined according to longitude and latitude information acquired during shooting, the height of a shooting system, the size of a ground object to be detected in an image and three-dimensional coordinates.
Through the system or the method, the hardware device and the software system of the invention realize the quick acquisition of the sub-centimeter-level fine topographic map, and verify and develop the precision and various indexes of the measuring system in indoor and outdoor development work, thereby realizing the dynamic process measurement, real-time monitoring, remote transmission and multi-user data sharing of the high-precision topographic map. The method provides scientific basis and technical support for comprehensive management of the drainage basin, landform and terrain observation, water and soil conservation and ecological environment restoration, natural disaster early warning and the like.
Drawings
In order to make the technical problems solved by the present invention, the technical means adopted and the technical effects obtained more clear, the following will describe in detail the embodiments of the present invention with reference to the accompanying drawings. It should be noted, however, that the drawings described below are only illustrations of exemplary embodiments of the invention, from which other embodiments can be derived by those skilled in the art without inventive step.
Fig. 1 is a schematic diagram illustrating an internal structure of a binocular stereo vision fine terrain measurement system according to an embodiment of the present invention.
Fig. 2 is a schematic diagram showing the structure of a binocular stereo vision movement measurement system according to an embodiment of the present invention.
Fig. 3 is a schematic structural diagram showing an electrical cabinet of a binocular stereo vision fine terrain measurement system according to an embodiment of the present invention.
Fig. 4 is a diagram showing a calibration process and a calibration software interface of a binocular stereo vision fine terrain measurement system according to an embodiment of the present invention.
Fig. 5 is a diagram illustrating a soil erosion tunnel acquired by a binocular stereo vision fine terrain measurement system according to an embodiment of the present invention.
Fig. 6 is a depth image acquired by a binocular stereo vision fine terrain measurement system according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments of the invention may be embodied in many specific forms, and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art.
The structures, properties, effects or other characteristics described in a certain embodiment may be combined in any suitable manner in one or more other embodiments, while still complying with the technical idea of the invention.
In describing particular embodiments, specific details of structures, properties, effects, or other features are set forth in order to provide a thorough understanding of the embodiments by one skilled in the art. However, it is not excluded that a person skilled in the art may implement the invention in a specific case without the above-described structures, performances, effects or other features.
The flow chart in the drawings is only an exemplary flow demonstration, and does not represent that all the contents, operations and steps in the flow chart are necessarily included in the scheme of the invention, nor does it represent that the execution is necessarily performed in the order shown in the drawings. For example, some operations/steps in the flowcharts may be divided, some operations/steps may be combined or partially combined, and the like, and the execution order shown in the flowcharts may be changed according to actual situations without departing from the gist of the present invention.
The block diagrams in the figures generally represent functional entities and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The same reference numerals denote the same or similar elements, components, or parts throughout the drawings, and thus, a repetitive description thereof may be omitted hereinafter. It will be further understood that, although the terms first, second, third, etc. may be used herein to describe various elements, components, or sections, these elements, components, or sections should not be limited by these terms. That is, these phrases are used only to distinguish one from another. For example, a first device may also be referred to as a second device without departing from the spirit of the present invention. Furthermore, the term "and/or", "and/or" is intended to include all combinations of any one or more of the listed items.
Fig. 1 is a schematic diagram illustrating an internal structure of a binocular stereo vision fine terrain measurement system according to an embodiment of the present invention. Fig. 2 is a schematic diagram showing the structure of a binocular stereo vision movement measurement system according to an embodiment of the present invention.
In order to solve the technical problem, the binocular stereoscopic vision fine terrain measurement system comprises the following technical scheme:
(1) a hardware system combining a terrain measurement visual system and a positioning system accurately determines three-dimensional information and longitude and latitude information of the terrain in the image. (2) The LabVIEW platform based on the virtual instrument technology develops an image acquisition and processing system, rapidly calculates parallax according to a shot image to generate a depth image, rapidly converts a visible light image into three-dimensional point cloud data and image pixel coordinates to a world left system by applying theoretical knowledge of subjects such as optics, electrodynamics, metrology, computer science and the like, researches a three-dimensional ground object coordinate monitoring method in the aspects of theory and technology, and determines a fine topographic map of a monitored area.
The measuring instrument can realize the functions of high-precision, time-saving, labor-saving and non-contact automatic measurement, meets the requirements of automatic monitoring of slope, basin and regional scale landform evolution, realizes three-dimensional reconstruction of landform, and realizes remote transmission and multi-user data sharing of dynamic measurement results. The developed instrument provides scientific basis and technical support for comprehensive management of a drainage basin, fine monitoring of landforms and terrains, water and soil conservation and ecological environment restoration, natural disaster early warning and prevention and the like.
Specifically, the invention uses theoretical knowledge of subjects such as optics, electrodynamic science, surveying, computer science and the like, aims at the main problems of the existing three-dimensional precise surveying instrument in the application of fine terrain change monitoring, and aims at developing a fine terrain change photogrammetry system based on binocular stereo vision. The hardware part adopts the hardware such as a GigE industrial camera, an embedded computer vision system (EVS), a 5G transmission terminal, a GPS positioner, a power supply system, a sensor, an encoder and the like, a gravity sensing device is assembled to accurately determine the vertical direction of a spherical coordinate system of the camera, and the high-precision GPS positioner is nested to realize the acquisition of depth images and the determination of the longitude and latitude of a shooting point. The method comprises the steps of developing a software system for instrument control, data acquisition and image processing based on a LabVIEW platform machine Vision technology, acquiring, storing, analyzing and processing images by using a Vision resolution module (VDM) Vision application module, extracting and classifying feature point cloud data in the images, establishing an image feature point cloud data set and an estimation model of a measurement target size, determining the three-dimensional coordinates and the size of a monitoring target, and determining the coordinates of each point of a measured object. The monitoring system aims to establish and perfect a stereo photogrammetry technology and equipment, quickly generate a visual topographic map and a fine DEM according to a shot image, establish a stereo automatic measurement system and an image processing method, obtain a high-precision, high-efficiency and non-contact measurement system, strive for realizing market popularization of the measurement system, and provide scientific basis for measuring three-dimensional target coordinates and related research.
As shown in fig. 1-2, the internal structure of a binocular stereo vision fine terrain measurement system is schematically shown. The binocular stereo vision mobile measurement system comprises: 1. the system comprises an embedded computer vision system, 2 an infrared sensor, 3 a GPS (global positioning system) positioner, 4a binocular vision GigE industrial camera, 5 a measuring system connecting piece, 6 an electric appliance cabinet equipment shell, 7.5G transmission terminals and 8 a power supply system. The binocular stereo vision measurement system mainly comprises two parts: the hardware device and the communication part are responsible for image, longitude and latitude acquisition and data transmission; the software processing module mainly has the functions of converting a shot image into three-dimensional point cloud data based on a machine vision technology of a LabVIEW platform and converting a coordinate system into a processing program, and mainly aims to convert a depth image pixel coordinate system into a world coordinate system, determine the vertical direction through a gravity sensing device, determine the accurate longitude and latitude coordinates of a camera by using a GPS (global positioning system) positioner, establish a coordinate conversion relation and finally realize coordinate conversion; after all module functions are integrated, the size of the ground object is measured, and finally high-precision topographic survey data with longitude and latitude information can be obtained in real time.
As shown in fig. 3, a schematic structural diagram of an electrical cabinet of a binocular stereo vision fine terrain measurement system. The electric appliance cabinet is made of stainless steel and is used for protecting hardware equipment inside the electric appliance cabinet: the system comprises a direct current power supply, two industrial digital cameras, an embedded computer vision system, a control driver of a stepping motor and a digital quantity input module.
The system comprises a hardware device and a communication part, wherein the hardware device is used for hardware control, and each part of a software processing module and a coordinate system conversion processing program is realized by combining a corresponding software system and a corresponding hardware device. The stepping motor provides power output for the movement of the whole set of measurement system, and the control driver and the encoder are combined with an NI-VISA program interface provided by a LabVIEW development platform through a serial port communication technology, so that the remote digital closed-loop control of the measurement system is realized. An industrial camera based on a gigabit Ethernet image transmission standard is selected, and is connected with NI-MAX configuration management software through a GigE Vision digital interface, so that communication support between software and hardware equipment is provided for an NI-IMAQ image acquisition and processing system of a LabVIEW development platform, and High-Speed High-resolution image acquisition and processing are realized.
The encoder is coaxially connected with the stepping motor to realize the digital closed-loop control of the mobile measuring system; the eight infrared sensors are diagonally arranged on one side of the electric appliance cabinet, and the electric appliance cabinet is stopped at different slope positions due to the triggering of different infrared sensors; the binocular vision camera consists of two kilomega (GigE) cameras, and each camera can reach high resolution and is used for acquiring a slope surface form image; the embedded computer vision system is the core of the mobile measurement system, is connected with the binocular vision camera through an interface, and is also connected with the stepping motor controller and the digital input module through serial port communication.
The setting of the binocular stereoscopic vision fine terrain measuring system further comprises the steps of completing the construction, debugging and installation of hardware equipment of the binocular stereoscopic vision fine terrain measuring instrument. Designing and processing an electric appliance cabinet, a square sliding rail and the like, and installing purchased hardware facilities into the electric appliance cabinet. A binocular vision camera, a gravity sensing device, a high-precision GPS (global positioning system) positioner, an embedded computer vision system, a driving controller, a power supply system, a 5G transmission terminal, a serial server, a digital quantity input module, a MySQL (structured query language) database, a sensor and a wireless network are built on a mobile platform, so that the three-dimensional information data of the ground object to be detected is acquired in a non-contact manner, and the data is issued to a remote database for checking and analyzing by utilizing a database network interconnection technology.
A software system for instrument control, data acquisition and image processing is developed based on a machine vision technology of a LabVIEW platform. And compiling a software program to control the built hardware part, realizing automatic data acquisition, image acquisition, storage, analysis and processing, acquiring a depth image by using a parallax principle, establishing an image characteristic point cloud data set and an estimation model of a measurement target size, and finally outputting a sub-centimeter-level fine topographic map under a geodetic coordinate system by combining coordinate conversion information.
The binocular stereoscopic vision fine topographic survey system is applied to field topographic monitoring, and the binocular stereoscopic vision topographic survey instrument is suitable for field investigation.
The key technical points of the invention are as follows:
(1) the depth image pixel three-dimensional coordinate system is converted to a world coordinate system.
The vertical direction of a depth image pixel coordinate system is accurately determined by assembling a gravity sensor, a high-precision GPS positioner in the system and a software program jointly realize the conversion of the depth image pixel coordinate system to a world coordinate system with longitude and latitude coordinate information, and a high-precision binocular GigE industrial camera is adopted to acquire a high-resolution parallax image, so that the functions of accurate measurement and three-dimensional reconstruction of ground objects are realized.
(2) And outputting the high-precision topographic map in real time.
The invention discloses a LabVIEW platform-based machine vision technology development instrument control, data acquisition and image processing software system, which adopts a VDM vision application module to realize the acquisition, storage, analysis and processing of images, extracts and classifies feature point data in the images, establishes an image feature point data set and an estimation model of the dimension of a measured target, determines the three-dimensional coordinates and the dimension of the monitored target, realizes the determination of the coordinates of each point of a measured object in the ground, establishes an image feature point cloud data and an estimation model of the three-dimensional dimension of the measured target, determines the three-dimensional coordinates and the dimension of the monitored target, and combines coordinate conversion data to obtain a high-precision topographic map. All the software systems are directly embedded in the measuring instrument in a chip form and connected with the embedded computer vision system, the MySQL database and the 5G transmission terminal to realize the real-time output of high-precision topographic maps, and the data is issued to a remote database for viewing and analysis by utilizing a database network interconnection technology to realize the automatic data acquisition, and the developed machine vision technology can realize the real-time and continuous monitoring of ground objects.
The binocular stereoscopic vision fine terrain measurement system provided by the invention has the following main performance indexes:
(1) geometric dimension of stainless steel box body filled with hardware equipment: 300mm × 300mm × 100mm (length × width × depth), a stainless steel plate 2mm thick is used, and the manufacturing error is less than 2 mm;
(2) the binocular stereoscopic vision measuring instrument has the horizontal measuring precision of +/-1 mm under the optimal working condition without environmental interference;
(3) the binocular stereoscopic vision measuring instrument has no environmental interference and has a vertical precision of +/-2 mm under the optimal working condition;
(4) the weight of the equipment (without optional accessories) is less than 3 kg;
(5) the LabVIEW platform-based instrument control, data acquisition and image processing system can realize accurate positioning of equipment, and the positioning accuracy is not lower than 1 cm;
(6) a minimum of 30 images per second can be acquired;
(7) the image resolution is not lower than 1294 x 964 pixel values;
(8) the real-time data release and transmission delay is not higher than 0.1 s;
(9) the time consumed for acquiring point cloud data by a single image processing system is less than 1 s;
(10) the binocular stereo vision measuring instrument 100m can measure ground objects with the maximum size of 350m at high altitude.
The invention also provides a method for estimating terrain by using the binocular stereo vision fine terrain measurement system, which comprises the following steps:
1. system calibration
The calibration procedure for the binocular vision camera requires a white calibration plate printed with 70 (10 x 7) black solid circles, all 4cm apart and 2cm in diameter. The binocular vision cameras are determined to be horizontally fixed before calibration and not to be moved or to change the relative positions between the cameras after calibration. The calibration results showed a maximum relative error of 0.72% and a minimum relative error of 0.10%.
Fig. 4 is a diagram showing a calibration process and a calibration software interface of a binocular stereo vision fine terrain measurement system according to an embodiment of the present invention.
The calibration procedure required a calibration device with 70 (10 × 7) black solid dots printed on a white background (fig. 4a, 4 b). Each solid black dot has a diameter of 2cm and the distance between the centers of each two solid dots is 4 cm. Calibration procedure as shown in fig. 4, the field of view of the camera is divided equally into 9 units to determine the distance between the two cameras and the distortion factor (fig. 4 d). The calibration plate needs to be completely present in the first calibration image acquired by both cameras and then the calibration plate needs to cover all cells in the camera field of view in different positions and at different angles, as shown (fig. 4 c). Finally, when all the calibration images cover the full field of view of both cameras (fig. 4d), the tangential and radial distortions will be corrected by the following equations (1) and (2):
Figure BDA0002534696080000131
Figure BDA0002534696080000132
Figure BDA0002534696080000133
in the formula X1,X2,Y1,Y2Is the coordinate coefficient of the corrected image; (x, y) are the coordinate coefficients of the original image; r isx,ryAre focal lengths in different directions; m is a correction coefficient for radial distortion; t is1,T2Is a correction factor for tangential distortion.
And step two, acquiring an image.
The development of the machine vision application program is carried out on a LabVIEW platform in combination with a VDM vision development module, and the developed application program is deployed to a Windows or Linux real-time operating system to build an image acquisition system. The images acquired by the system are automatically classified according to the acquisition time and stored in corresponding folders and MySQL databases, and the databases are combined with a LabVIEW platform through a database connection tool kit, so that the conventional operation of the databases on the platform can be executed. The soil erosion channel map acquired by the binocular stereo vision fine terrain measurement system shown in fig. 3 is the soil erosion channel image acquired by the image acquisition system indoors and outdoors.
And step three, image analysis.
And a machine vision module in the LabVIEW operating platform processes and analyzes the acquired image. In order to obtain better channel profile and more accurate channel image data, the image in fig. 5 is segmented using a depth threshold segmentation technique. And matching and calculating a left image and a right image acquired by a left digital industrial camera and a right digital industrial camera in the image acquisition system through a block matching algorithm to generate left and right parallax images. The depth image obtained by the binocular stereo vision fine terrain measurement system shown in fig. 6 is calculated according to the parallax image. The method comprises the steps of extracting a channel profile from a depth image by adopting functions of image subtraction, binary image corrosion, particle removal, filling and the like in a VDM visual development module, then carrying out particle analysis on the extracted channel profile, calculating a value of a channel image particle sum of the profile, displaying the value on a reconstructed image after processing and analysis, extracting and classifying feature point data in the image, and establishing an image feature point data set and a measurement target size estimation model. From this it is possible to calculate the dimensions of the object to be measured and to determine the three-dimensional coordinates of any point in the image.
And step four, coordinate conversion, namely developing a coordinate conversion software system based on a machine vision technology of a LabVIEW platform, determining the three-dimensional coordinates of the monitoring target, and realizing the determination of the coordinates of each point of the measured object on the ground. The coordinate conversion can be determined according to longitude and latitude information acquired during shooting, the height of a shooting system, the size of a ground object to be detected in an image and three-dimensional coordinates.
The main innovation points of the invention are as follows:
(1) acquiring a depth image by using a binocular GigE industrial camera;
(2) nesting a high-precision GPS positioner to obtain flight track information; the geodetic coordinate system;
(3) based on a machine vision technology of a LabVIEW platform, the functions of calibration, instrument control, data acquisition, image processing and coordinate conversion are realized, the size of a ground object is calculated according to a shot image, and a visual topographic map with world coordinate information is quickly generated;
(4) data real-time release, database remote connection access and mobile measurement system remote control.
Compared with the prior art, the key technology, the solution and the beneficial effects of the invention are as follows:
(1) conversion of depth image pixel coordinate system to world coordinate system
A binocular GigE industrial camera with high measurement precision is adopted to acquire a high-resolution parallax image, and a high-precision GPS positioner in the system and a software program jointly realize the conversion from an image pixel coordinate system to a world coordinate system, so that the functions of precise measurement and three-dimensional reconstruction of ground objects are realized.
(2) High-precision topographic map real-time output
The project develops an instrument control, data acquisition and image processing software system based on a LabVIEW platform machine vision technology, adopts a VDM vision application module to realize image acquisition, storage, analysis and processing, extracts and classifies feature point data in an image, establishes an estimation model of an image feature point data set and a measurement target size, determines the three-dimensional coordinates and the size of a monitoring target, realizes the determination of the coordinates of each point of a measured object on the ground, and combines coordinate conversion data to obtain a high-precision topographic map. The MySQL database and the 5G transmission terminal realize real-time output of high-precision topographic maps, and release data to a remote database for viewing and analysis by utilizing a database network interconnection technology, so that automatic data acquisition is realized, and the developed machine vision technology can realize real-time and continuous monitoring of ground features.
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.

Claims (2)

1. A binocular stereo vision fine terrain measurement system, comprising:
the electric appliance cabinet is used for protecting each component in the electric appliance cabinet;
a power supply, a hardware device, a communication part, a software data processing module and a coordinate system conversion processing program are arranged in the electric appliance cabinet;
the hardware device and the communication part are used for image, longitude and latitude acquisition and data transmission; the hardware device and the communication part comprise a GigE industrial camera, an embedded computer vision system EVS, a 5G transmission terminal, a power supply system, a stepping motor, a driver, an encoder and eight infrared sensors; the stepping motor is used for providing power output for the movement of the measuring system, and the control driver and the encoder are combined with an NI-VISA program interface provided by a LabVIEW development platform through a serial port communication technology to realize the remote digital closed-loop control of the measuring system; the encoder is coaxially connected with the stepping motor and used for digital closed-loop control of the mobile measuring system; the eight infrared sensors are arranged on one side of the electric appliance cabinet in a diagonal manner, and the electric appliance cabinet is stopped at different slope positions due to the triggering of different infrared sensors;
the software data processing module is used for converting the shot image into three-dimensional point cloud data based on the machine vision technology of a LabVIEW platform, but does not have topographic features; the software data processing module comprises a binocular Vision camera and is used for establishing connection with NI-MAX configuration management software through a GigE Vision digital interface, providing communication support between software and hardware equipment for an NI-IMAQ image acquisition and processing system of a LabVIEW development certificate, and completing High-Speed High-resolution image acquisition and processing;
the coordinate system conversion processing program is used for converting a depth image pixel coordinate system into a world coordinate system, setting a gravity sensing device to determine the vertical direction, acquiring a depth image and determining the longitude and latitude of a shooting point by using a GPS (global positioning system) positioner, and the GPS positioner and a software program jointly realize the conversion from the image pixel coordinate system to the world coordinate system, establish a coordinate conversion relation and realize the coordinate conversion; the coordinate system conversion processing program comprises an embedded computer vision system, wherein the embedded computer vision system is connected with the binocular vision camera through an interface and is connected with the stepping motor controller and the digital input module through serial port communication;
integrating all module functions, measuring the dimensions of ground objects, and acquiring high-precision topographic survey data with longitude and latitude information in real time; the method for estimating the terrain by using the binocular vision camera comprises the following steps
Step 1, calibrating a system,
the calibration procedure of the binocular vision camera needs a white calibration plate printed with 70 black solid circles, the distance between the circle centers is 4cm, and the diameter is 2 cm; before calibration, determining that the binocular vision cameras are horizontally fixed and cannot be moved or the relative positions of the cameras are changed after calibration; the calibration result shows that the maximum relative error is 0.72 percent, and the minimum relative error is 0.10 percent;
the calibration procedure required a calibration device with 70 black solid dots printed on a white background, each black solid dot having a diameter of 2cm and the distance between the centers of each two solid dots being 4 cm; the field of view of the cameras is divided into 9 units on average to determine the distance between the two cameras and the distortion coefficient; the calibration plate needs to be completely present in the first calibration image acquired by the two cameras, and then the calibration plate needs to cover all units in the camera field of view at different positions and different angles; finally, when all the calibration images cover the whole visual field of the two cameras, the tangential and radial distortion is corrected by the formula (1) and the formula (2), wherein the formula is as follows:
Figure 36251DEST_PATH_IMAGE001
(1)
Figure 850624DEST_PATH_IMAGE002
(2)
Figure 231008DEST_PATH_IMAGE003
(3)
in the formula
Figure 498042DEST_PATH_IMAGE004
Is the coordinate coefficient of the corrected image;
Figure 696942DEST_PATH_IMAGE005
is the coordinate coefficient of the original image;
Figure 365821DEST_PATH_IMAGE006
,
Figure 421501DEST_PATH_IMAGE007
are focal lengths in different directions;Mis a correction factor for radial distortion;T 1,T 2is a correction factor for tangential distortion;
step 2, image acquisition, including developing a machine vision application program on a LabVIEW platform in combination with a VDM vision development module, and deploying the developed application program to a Windows or Linux real-time operating system to build an image acquisition system; images acquired by the system are automatically classified according to the acquisition time and stored in corresponding folders and MySQL databases, and the databases are combined with a LabVIEW platform through a database connection tool kit, so that the operation of the databases on the platform can be executed;
step 3, image analysis, wherein a machine vision module in a LabVIEW operation platform processes and analyzes the acquired image; in order to obtain better channel outline and more accurate channel image data, a left image and a right image which are acquired by a left digital industrial camera and a right digital industrial camera in an image acquisition system are matched and calculated through a block matching algorithm to generate left and right parallax images; calculating a depth image according to the parallax image; extracting a channel profile from a depth image by adopting an image subtraction, binary image corrosion, particle removal and filling function in a VDM visual development module, then performing particle analysis on the extracted channel profile, calculating a value of the sum of the particles of the channel image of the profile, displaying the value on a reconstructed image after processing and analysis, extracting and classifying feature point data in the image, establishing an estimation model of an image feature point data set and a measurement target size, and thus calculating the size of a measured object and determining the three-dimensional coordinate of any point in the image;
step 4, coordinate conversion, namely developing a coordinate conversion software system based on a machine vision technology of a LabVIEW platform, determining the three-dimensional coordinates of the monitoring target, and realizing the determination of the coordinates of each point of the measured object on the ground; the coordinate conversion can be determined according to longitude and latitude information acquired during shooting, the height of a shooting system, the size of a ground object to be detected in an image and three-dimensional coordinates.
2. The binocular stereo vision fine terrain measurement system of claim 1,
the binocular vision camera consists of two kilomega cameras and is used for acquiring the images of the slope surface morphology.
CN202010529424.2A 2020-06-11 2020-06-11 Binocular stereo vision fine terrain measurement system and method Active CN111696162B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010529424.2A CN111696162B (en) 2020-06-11 2020-06-11 Binocular stereo vision fine terrain measurement system and method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010529424.2A CN111696162B (en) 2020-06-11 2020-06-11 Binocular stereo vision fine terrain measurement system and method

Publications (2)

Publication Number Publication Date
CN111696162A CN111696162A (en) 2020-09-22
CN111696162B true CN111696162B (en) 2022-02-22

Family

ID=72480361

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010529424.2A Active CN111696162B (en) 2020-06-11 2020-06-11 Binocular stereo vision fine terrain measurement system and method

Country Status (1)

Country Link
CN (1) CN111696162B (en)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20220054582A (en) * 2020-10-23 2022-05-03 저지앙 센스타임 테크놀로지 디벨롭먼트 컴퍼니 리미티드 Visual positioning method and related apparatus, device and computer readable storage medium
CN112526106A (en) * 2020-11-26 2021-03-19 长江水利委员会长江科学院 Terrain measuring probe device and method for rapidly measuring slope soil erosion amount
CN112781521A (en) * 2020-12-11 2021-05-11 北京信息科技大学 Software operator shape recognition method based on visual markers
CN113163085B (en) * 2021-04-01 2023-04-18 长春博立电子科技有限公司 Intelligent industrial camera based on binocular IDE development software
CN113873223B (en) * 2021-09-03 2023-07-21 大连中科创达软件有限公司 Method, device, equipment and storage medium for determining definition of camera
CN114234012B (en) * 2021-11-30 2023-04-18 深圳市勘察研究院有限公司 Slope monitoring device, monitoring method and cleaning method based on visual tracking

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106204595A (en) * 2016-07-13 2016-12-07 四川大学 A kind of airdrome scene three-dimensional panorama based on binocular camera monitors method
CN109597095A (en) * 2018-11-12 2019-04-09 北京大学 Backpack type 3 D laser scanning and three-dimensional imaging combined system and data capture method
WO2019228523A1 (en) * 2018-05-31 2019-12-05 上海微电子装备（集团）股份有限公司 Method and device for determining spatial position shape of object, storage medium and robot
CN110646808A (en) * 2019-10-26 2020-01-03 东北林业大学 Forestry knapsack formula laser radar multisensor integrated system
CN111238374A (en) * 2020-03-16 2020-06-05 天目爱视（北京）科技有限公司 Three-dimensional model construction and measurement method based on coordinate measurement

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109300190B (en) * 2018-09-06 2021-08-10 百度在线网络技术（北京）有限公司 Three-dimensional data processing method, device, equipment and storage medium
CN111174799B (en) * 2019-12-24 2023-02-17 Oppo广东移动通信有限公司 Map construction method and device, computer readable medium and terminal equipment

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106204595A (en) * 2016-07-13 2016-12-07 四川大学 A kind of airdrome scene three-dimensional panorama based on binocular camera monitors method
WO2019228523A1 (en) * 2018-05-31 2019-12-05 上海微电子装备（集团）股份有限公司 Method and device for determining spatial position shape of object, storage medium and robot
CN109597095A (en) * 2018-11-12 2019-04-09 北京大学 Backpack type 3 D laser scanning and three-dimensional imaging combined system and data capture method
CN110646808A (en) * 2019-10-26 2020-01-03 东北林业大学 Forestry knapsack formula laser radar multisensor integrated system
CN111238374A (en) * 2020-03-16 2020-06-05 天目爱视（北京）科技有限公司 Three-dimensional model construction and measurement method based on coordinate measurement

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
A vision-based perception framework for outdoor navigation tasks applicable to legged robots;Junwen Sun 等;《2017 Chinese Automation Congress (CAC)》;20180101;全文 *
LabVIEW与ARM嵌入式的结合系统在岩体裂缝检测中的应用;龙柄全;《中国优秀博硕士学位论文全文数据库(硕士) 基础科学辑》;20190115;第2018年卷(第12期);全文 *
海岸带地形基础数据测量装置设计;杨靖伦 等;《机械研究与应用》;20180831;第31卷(第156期);全文 *

Also Published As

Publication number Publication date
CN111696162A (en) 2020-09-22

Similar Documents

Publication Publication Date Title
CN111696162B (en) Binocular stereo vision fine terrain measurement system and method
Eltner et al. Image-based surface reconstruction in geomorphometry–merits, limits and developments
Goncalves et al. UAV photogrammetry for topographic monitoring of coastal areas
CN113607135B (en) Unmanned aerial vehicle inclination photogrammetry method for road and bridge construction field
Gruen et al. Joint processing of UAV imagery and terrestrial mobile mapping system data for very high resolution city modeling
Abuhadrous et al. Digitizing and 3D modeling of urban environments and roads using vehicle-borne laser scanner system
CN113740844A (en) Dam body three-dimensional deformation monitoring-oriented two-foundation radar combined observation method
CN112862966B (en) Method, device, equipment and storage medium for constructing surface three-dimensional model
CN110889899A (en) Method and device for generating digital earth surface model
Jiang et al. UAV-based oblique photogrammetry for 3D reconstruction of transmission line: Practices and applications
Abbate et al. Prospective upon multi-source urban scale data for 3d documentation and monitoring of urban legacies
Gonçalves et al. Monitoring Local Shoreline Changes by Integrating UASs, Airborne LiDAR, Historical Images and Orthophotos.
Cilek et al. Generation of high-resolution 3-D maps for landscape planning and design using UAV technologies
Boonpook et al. UAV-based 3D urban environment monitoring
CN110132131A (en) A kind of measurement method of scene data
Griesbaum et al. Direct local building inundation depth determination in 3-D point clouds generated from user-generated flood images
Yeh et al. The Evaluation of GPS techniques for UAV-based Photogrammetry in Urban Area
Stylianidis et al. A digital close-range photogrammetric technique for monitoring slope displacements
Huang et al. Integration of mobile laser scanning data with UAV imagery for very high resolution 3D city modeling
CN109859315B (en) Surface vegetation separation method of three-dimensional image
Yaemjaem et al. Development of high-definition 3D mapping system for water resources management
CN100395779C (en) Measurable seamless space stereomodel gereration method based on digital stereo normal incidence image mosaic
Chen et al. 3D model construction and accuracy analysis based on UAV tilt photogrammetry
Scaioni et al. Monitoring of geological sites by laser scanning techniques
Polat LIDAR Derived 3d City Modelling

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
CB03 Change of inventor or designer information
CB03 Change of inventor or designer information

Inventor after: Ban Yunyun

Inventor after: Xu Ximeng

Inventor before: Tang Qiuhong

Inventor before: Ban Yunyun

Inventor before: Xu Ximeng

GR01 Patent grant
GR01 Patent grant