CN107193286B - Bridge live-action digital acquisition method - Google Patents
Bridge live-action digital acquisition method Download PDFInfo
- Publication number
- CN107193286B CN107193286B CN201710406248.1A CN201710406248A CN107193286B CN 107193286 B CN107193286 B CN 107193286B CN 201710406248 A CN201710406248 A CN 201710406248A CN 107193286 B CN107193286 B CN 107193286B
- Authority
- CN
- China
- Prior art keywords
- bridge
- equipment
- carrier
- virtual reality
- acquisition
- 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
Links
- 238000000034 method Methods 0.000 title claims abstract description 20
- 238000001514 detection method Methods 0.000 claims abstract description 18
- 238000004891 communication Methods 0.000 claims description 11
- 230000005540 biological transmission Effects 0.000 claims description 2
- 238000000605 extraction Methods 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 description 7
- 238000013079 data visualisation Methods 0.000 description 2
- 201000010099 disease Diseases 0.000 description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
- G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Accessories Of Cameras (AREA)
- Studio Devices (AREA)
Abstract
The invention provides a digital acquisition method for a bridge real scene, which comprises the following steps: a. determining the position of the virtual reality acquisition equipment installed on the carrier equipment; b. moving the virtual reality acquisition equipment to a target bridge area through carrier equipment; c. the carrier equipment is communicated with the bridge detection identification tag in the bridge area to determine the pose of the carrier equipment; d. and controlling the virtual reality acquisition equipment to shoot by the carrier equipment, and recording shooting parameters of all lenses and pose information of the carrier equipment during shooting. The invention solves the problems that the prior art is difficult to efficiently and accurately acquire the bridge damage information and the like, and further promotes the efficient and accurate extraction and storage of the bridge live-action information.
Description
Technical Field
The invention belongs to the technical field of traffic engineering, and relates to a bridge live-action digital acquisition method.
Background
At present, the traditional bridge image information acquisition means is a camera, but because the time or energy of shooting personnel is limited, the shooting of the bridge panorama cannot be completed generally, and only the damaged part is shot for evidence collection. Corresponding bridge and member information must be recorded when shooting for evidence obtaining, otherwise, the verification can not be carried out in the later period. In the aspect of data visualization, generally, only damaged pictures of a specific bridge can be called and checked, and the real scene of the bridge cannot be restored.
With the development of VR acquisition technology, the image fineness is continuously improved, the lens distortion rate is low, and the cost is continuously reduced, so that the method has wide application prospects in various industries. The bridge is a structural body with a plurality of complex components, the traditional bridge real-scene acquisition technology is time-consuming and labor-consuming, and due to human negligence, missed acquisition of damaged data can be caused. Introduce bridge disease detection area with VR collection technique, can greatly promote data acquisition's efficiency, improve data acquisition's quality to reduce data acquisition personnel to mastering bridge professional knowledge's requirement. Furthermore, introduction of the VR acquisition technology into the field of bridge disease acquisition has extremely strong research significance and application value.
In the prior art, although technologies of adopting VR acquisition devices are already related in the fields of movie shooting and archaeology, technologies of adopting VR acquisition devices are not related on bridges serving as detection objects completely different from the detection objects, and specific application technologies of VR acquisition devices on bridge panoramic real scene acquisition are not available in the prior art due to the fact that the bridges serving as special objects are greatly different from common management objects in terms of actual properties, structural distribution and the like.
Disclosure of Invention
In order to overcome the defects in the prior art, a digital acquisition method for the bridge live-action is provided so as to solve the problems that the bridge damage information is difficult to acquire efficiently and accurately and the like in the prior art, and further promote the efficient and accurate extraction and storage of the bridge live-action information.
In order to achieve the above purpose, the solution of the invention is:
a bridge live-action digital acquisition method comprises the following steps:
a. according to task requirements, determining the position of mounting the virtual reality acquisition equipment on carrier equipment, and moving the virtual reality acquisition equipment to a target bridge area through the carrier equipment;
b. communicating the carrier robot with the bridge detection identification tag to determine the pose of the carrier robot;
c. the carrier robot moves and controls shooting of the virtual reality acquisition equipment according to a preset program or through manual operation, and simultaneously records shooting parameters of the camera and pose information of the carrier robot.
Preferably, the step a specifically comprises the following steps:
placing the virtual reality acquisition equipment at the bottom of the carrier equipment to acquire image information of bridge deck pavement, bridge spanned entities, bridge deck affiliated facilities and piers of the target bridge;
or the virtual reality acquisition equipment is arranged at the top of the carrier equipment so as to acquire the image information of the beam bottom, the bridge deck attached facilities and the bridge piers of the target bridge.
Preferably, the method further comprises the following steps when the step c is carried out:
the virtual reality acquisition equipment is connected with the carrier equipment through a communication interface to artificially allow the carrier equipment to control the virtual reality acquisition equipment to be opened and closed, and real-time azimuth information of the carrier equipment is transmitted to the virtual reality acquisition equipment.
Preferably, the communication interface has both wired and wireless transmission connection functions, and the carrier device controls the shooting parameters of the virtual reality acquisition device through the communication interface.
Preferably, the method further comprises the following steps when the step b is carried out:
controlling the carrier equipment to automatically recognize the position and the posture of the carrier equipment in the space;
absolute coordinate information of the carrier device in a bridge coordinate system is stored in the bridge detection identification tag, and the carrier device interacts with the bridge detection identification tag to determine the position and posture of the carrier device in the bridge coordinate system.
Preferably, when the real scene of the target bridge is shot, the panoramic information of the target bridge is directly collected through the virtual reality collecting device.
Preferably, the carrier device is a manually controllable carrier robot.
The bridge live-action digital acquisition method has the beneficial effects that:
the bridge detection identification tag and the VR acquisition technology are applied to bridge detection engineering, so that the detection device can efficiently carry out digital acquisition on bridge live-action information, the data acquisition precision is greatly improved, the data acquisition cost is reduced, and the bridge live-action can be restored.
Drawings
FIG. 1 is a logic block diagram of the bridge live-action digital acquisition method of the present invention.
Detailed Description
The invention will be further described with reference to examples of embodiments shown in the drawings.
As shown in fig. 1, the invention provides a bridge live-action digital acquisition method, which comprises the following steps:
a. loading Virtual Reality (VR) acquisition equipment to the top or the bottom of a carrier robot according to task requirements;
b. moving the carrier robot to a target bridge area;
c. the carrier robot communicates with the bridge detection identification tag to determine the pose of the carrier robot;
d. the carrier robot moves and controls shooting of the virtual reality acquisition equipment according to a preset program or through manual operation, and simultaneously records shooting parameters of the camera and pose information of the carrier robot.
Wherein the VR acquisition equipment is provided with a communication interface relative to the carrier robot so as to allow the carrier robot to control the start of the VR acquisition equipment and transmit the pose information of the VR acquisition equipment to the VR acquisition equipment.
The VR acquisition device in the step a may be disposed at the bottom of the carrier robot to acquire image information of a bridge deck pavement, an entity spanned by the bridge, a bridge deck affiliated facility, a pier and other parts (the entity spanned by the bridge refers to objects such as a river, a road, and a general land spanned by the bridge); the VR acquisition equipment can also be arranged at the top of the carrier robot to acquire image information of the bridge bottom, bridge deck auxiliary facilities, piers and other parts (no matter which installation mode is adopted, the image information of the piers and the bridge deck auxiliary facilities can be acquired, wherein the bridge auxiliary facilities refer to objects such as railings, electric wires, street lamps and the like).
And c, the carrier robot in the step a is provided with a mounting interface connected with the VR acquisition equipment, and the mounting interfaces are respectively positioned at the top and the bottom of the carrier robot and can fix the VR acquisition equipment on the carrier robot.
The carrier robot in the step b can identify the position of the carrier robot in the space through the GPS. Specifically, the general position of the self is determined through a GPS (global positioning system) and the self flies into the vicinity of a bridge space, and then the self posture is further accurately positioned and confirmed through a bridge detection identification tag.
C, the carrier robot can identify the position and the posture of the carrier robot in the space through the GPS and the bridge detection identification tag; absolute coordinate information of the carrier robot in a bridge coordinate system is stored in the bridge detection identification tag, and the carrier robot interacts with the bridge detection identification tag to determine the position and posture of the carrier robot in the bridge coordinate system.
And d, the VR acquisition equipment in the step d is provided with a communication interface with the carrier robot, and the communication interface can be in a wired form or a wireless form. The communication interface is used for transmitting signals of the carrier robot for opening and closing the VR acquisition equipment and transmitting pose information of the carrier robot during shooting; the shooting parameters of the camera include focal length, magnification ratio, aperture, vertical displacement, white balance, shutter speed, film speed ISO, depth of field and other parameters; the pose of the carrier robot refers to the absolute position of the carrier robot in a predefined bridge coordinate system and the posture of the carrier robot relative to the bridge coordinate system.
The method of the steps a-d can be used for completing the live-action acquisition of the bridge panoramic information.
Specifically, the task requirement determines the mode of installing the VR acquisition equipment on the carrier robot, and then the carrier robot conveys the VR acquisition equipment to a bridge area for bridge real scene acquisition. The carrier robot moves in the bridge area in a pre-programmed or manual control mode, and controls the VR acquisition equipment to shoot so as to complete digital acquisition of the bridge real scene. In the shooting process, the carrier robot transmits the pose information of the carrier robot in the space to the VR acquisition equipment through the communication interface and controls shooting parameters of the VR acquisition equipment so as to reproduce the live-action at a later stage.
After the implementation process is completed, the following characteristics of the invention can be embodied:
the method is easy to realize, the resource consumption is less, the collected information is large and fine, and the data visualization degree is high.
The embodiments described above are intended to facilitate one of ordinary skill in the art in understanding and using the present invention. It will be readily apparent to those skilled in the art that various modifications to these embodiments may be made, and the generic principles described herein may be applied to other embodiments without the use of the inventive faculty. Therefore, the present invention is not limited to the above embodiments, and those skilled in the art should make improvements and modifications within the scope of the present invention based on the disclosure of the present invention.
Claims (3)
1. A bridge live-action digital acquisition method is characterized by comprising the following steps:
a. moving the virtual reality acquisition equipment to a target bridge area;
a1, according to task requirements, determining the position of a virtual reality acquisition device installed on a carrier device;
a 2, moving the virtual reality acquisition equipment to a target bridge area through carrier equipment;
b. communicating the carrier device with a bridge detection identification tag to determine the pose of the carrier device; the carrier equipment can automatically identify the position and the posture of the carrier equipment in a predefined bridge coordinate system;
absolute coordinate information of the carrier device in a bridge coordinate system is stored in the bridge detection identification tag, and the carrier device interacts with the bridge detection identification tag to determine the pose of the carrier device in the bridge coordinate system;
c. the carrier equipment removes and control according to programming in advance or through manual operation virtual reality collection equipment is right the target bridge shoots, simultaneously records the shooting parameter of camera and the position appearance information of carrier equipment, virtual reality collection equipment pass through communication interface connect in carrier equipment to artificial allowance carrier equipment control opening and close of virtual reality collection equipment, and will the real-time azimuth information of carrier equipment self is carried and is given virtual reality collection equipment, communication interface has wired and wireless transmission connection function simultaneously, carrier equipment passes through communication interface control virtual reality collection equipment's shooting parameter is shooing, when shooing the real scene of target bridge, directly passes through virtual reality collection equipment gathers the panoramic information of target bridge.
2. The digital acquisition method for the real scene of the bridge according to claim 1, wherein the step a1 is executed by the following steps:
placing the virtual reality acquisition equipment at the bottom of the carrier equipment to acquire image information of bridge deck pavement, bridge spanned entities, bridge deck affiliated facilities and piers of the target bridge;
or the virtual reality acquisition equipment is arranged at the top of the carrier equipment so as to acquire the image information of the beam bottom, the bridge deck attached facilities and the bridge piers of the target bridge.
3. The digital acquisition method for the real scene of the bridge according to any one of claims 1 to 2, characterized in that: the carrier device is a manually controllable carrier robot.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710406248.1A CN107193286B (en) | 2017-06-02 | 2017-06-02 | Bridge live-action digital acquisition method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710406248.1A CN107193286B (en) | 2017-06-02 | 2017-06-02 | Bridge live-action digital acquisition method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107193286A CN107193286A (en) | 2017-09-22 |
| CN107193286B true CN107193286B (en) | 2020-12-08 |
Family
ID=59876419
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710406248.1A Active CN107193286B (en) | 2017-06-02 | 2017-06-02 | Bridge live-action digital acquisition method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107193286B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109272573A (en) * | 2018-09-07 | 2019-01-25 | 东南大学 | The wisdom bridge visualization system of three-dimensional digital model and three-dimensional live models coupling |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5366038A (en) * | 1992-08-25 | 1994-11-22 | Nishiguchi Hidetsugu | Robot traveling on wall face |
| CN101914893A (en) * | 2010-07-09 | 2010-12-15 | 重庆交通大学 | Bridge detection robot based on four-axle aircraft |
| WO2011016857A2 (en) * | 2009-08-05 | 2011-02-10 | Elliott James C | Equipment and system for structure inspection and monitoring |
| JP2011530692A (en) * | 2008-05-21 | 2011-12-22 | ザ・ボーイング・カンパニー | System and method for inspection of structures and objects by remote unmanned transport means |
| CN102708512A (en) * | 2012-04-24 | 2012-10-03 | 重庆市鹏创道路材料有限公司 | Intelligent bridge maintenance management system based on Internet of Things and 3D (three-dimensional) GIS (geographic information system) |
| CN202976181U (en) * | 2012-12-03 | 2013-06-05 | 重庆市鹏创道路材料有限公司 | Bridge management system based on Internet of Things and 3D GIS |
| CN103253314A (en) * | 2013-03-29 | 2013-08-21 | 华中科技大学 | Negative pressure absorption climbing type robot used for detecting fissure of bridge |
| CN205188841U (en) * | 2015-11-20 | 2016-04-27 | 上海市政工程设计研究总院（集团）有限公司 | Overpass beam supports system of patrolling and examining based on many rotor crafts |
| CN105735150A (en) * | 2016-03-04 | 2016-07-06 | 浙江大学 | Movable multi-view visual bridge conventional detection method |
| CN205554590U (en) * | 2016-03-15 | 2016-09-07 | 哈尔滨伟方智能科技开发有限责任公司 | A many rotors unmanned vehicles for bridge detects |
| JP2016176766A (en) * | 2015-03-19 | 2016-10-06 | 株式会社日立ソリューションズ | Inspection object extraction device, and method for extracting inspection object |
| WO2016165491A1 (en) * | 2015-08-26 | 2016-10-20 | 中兴通讯股份有限公司 | Bridging service and bridging network element inspection method and apparatus |
| CN106062510A (en) * | 2014-04-25 | 2016-10-26 | 索尼公司 | Information processing device, information processing method, and computer program |
| CN106245524A (en) * | 2016-08-30 | 2016-12-21 | 上海法赫桥梁隧道养护工程技术有限公司 | A kind of UAS for bridge machinery |
| CN106320173A (en) * | 2016-08-24 | 2017-01-11 | 周劲宇 | System and method for detecting daily safety of bridge by vehicle-mounted unmanned aerial vehicle |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100703444B1 (en) * | 2003-06-03 | 2007-04-03 | 삼성전자주식회사 | Device and method for downloading and displaying a images of global position information in navigation system |
| CN1892660A (en) * | 2005-07-07 | 2007-01-10 | 同济大学 | Efficient bridge facility data collection method |
| CN102077230A (en) * | 2008-04-17 | 2011-05-25 | 旅行者保险公司 | A method of and system for determining and processing object structure condition information |
| CN101916507B (en) * | 2010-08-10 | 2012-04-25 | 广东省建筑科学研究院 | Bridge health monitoring system |
| US20140336928A1 (en) * | 2013-05-10 | 2014-11-13 | Michael L. Scott | System and Method of Automated Civil Infrastructure Metrology for Inspection, Analysis, and Information Modeling |
| CN106648046A (en) * | 2016-09-14 | 2017-05-10 | 同济大学 | Virtual reality technology-based real environment mapping system |
| CN106485786A (en) * | 2016-10-20 | 2017-03-08 | 安徽协创物联网技术有限公司 | A kind of virtual reality panoramic video acquisition device |
| CN106778949B (en) * | 2016-11-24 | 2020-03-31 | 同济大学 | Method for promoting automatic bridge detection and identification and bridge detection and identification label |
| CN106758805B (en) * | 2016-12-29 | 2018-07-03 | 天津大学 | A kind of Bridge Testing Equipment and its application method based on VR virtual reality technologies |
-
2017
- 2017-06-02 CN CN201710406248.1A patent/CN107193286B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5366038A (en) * | 1992-08-25 | 1994-11-22 | Nishiguchi Hidetsugu | Robot traveling on wall face |
| JP2011530692A (en) * | 2008-05-21 | 2011-12-22 | ザ・ボーイング・カンパニー | System and method for inspection of structures and objects by remote unmanned transport means |
| WO2011016857A2 (en) * | 2009-08-05 | 2011-02-10 | Elliott James C | Equipment and system for structure inspection and monitoring |
| CN101914893A (en) * | 2010-07-09 | 2010-12-15 | 重庆交通大学 | Bridge detection robot based on four-axle aircraft |
| CN102708512A (en) * | 2012-04-24 | 2012-10-03 | 重庆市鹏创道路材料有限公司 | Intelligent bridge maintenance management system based on Internet of Things and 3D (three-dimensional) GIS (geographic information system) |
| CN202976181U (en) * | 2012-12-03 | 2013-06-05 | 重庆市鹏创道路材料有限公司 | Bridge management system based on Internet of Things and 3D GIS |
| CN103253314A (en) * | 2013-03-29 | 2013-08-21 | 华中科技大学 | Negative pressure absorption climbing type robot used for detecting fissure of bridge |
| CN106062510A (en) * | 2014-04-25 | 2016-10-26 | 索尼公司 | Information processing device, information processing method, and computer program |
| JP2016176766A (en) * | 2015-03-19 | 2016-10-06 | 株式会社日立ソリューションズ | Inspection object extraction device, and method for extracting inspection object |
| WO2016165491A1 (en) * | 2015-08-26 | 2016-10-20 | 中兴通讯股份有限公司 | Bridging service and bridging network element inspection method and apparatus |
| CN205188841U (en) * | 2015-11-20 | 2016-04-27 | 上海市政工程设计研究总院（集团）有限公司 | Overpass beam supports system of patrolling and examining based on many rotor crafts |
| CN105735150A (en) * | 2016-03-04 | 2016-07-06 | 浙江大学 | Movable multi-view visual bridge conventional detection method |
| CN205554590U (en) * | 2016-03-15 | 2016-09-07 | 哈尔滨伟方智能科技开发有限责任公司 | A many rotors unmanned vehicles for bridge detects |
| CN106320173A (en) * | 2016-08-24 | 2017-01-11 | 周劲宇 | System and method for detecting daily safety of bridge by vehicle-mounted unmanned aerial vehicle |
| CN106245524A (en) * | 2016-08-30 | 2016-12-21 | 上海法赫桥梁隧道养护工程技术有限公司 | A kind of UAS for bridge machinery |
Non-Patent Citations (5)
| Title |
|---|
| Application of Virtual Reality Technology in Bridge Structure Safety Monitoring;Dongwei Qiu etal.;《International Conference on Computer and Information Application（ICCIA 2010）》;20101231;第465-467页 * |
| Research and Application of Bridge Three-Dimensional Interactive Virtual Scene System;Xiongjun HE etal.;《2010 2nd Conference on Environmental Science and Information Application Technology 》;20101231;第631-634页 * |
| 上海城市梁桥型钢伸缩装置损坏保持性分析;梁远路等;《中国科技信息》;20151231;第65-68页 * |
| 基于Android的折叠臂式桥梁检测车智能监控系统的研究;张麒;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》;20150315;第C34-1064页 * |
| 桥梁PDA数据采集系统研究;曾胜男等;《桥梁工程》;20041231;第36-38页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107193286A (en) | 2017-09-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106468918B (en) | Standardized data acquisition method and system for line inspection | |
| CN103716595B (en) | Panoramic mosaic video camera and ball machine inter-linked controlling method and device | |
| CN112164015B (en) | Monocular vision autonomous inspection image acquisition method and device and power inspection unmanned aerial vehicle | |
| CN103716594B (en) | Panorama splicing linkage method and device based on moving target detecting | |
| WO2018103408A1 (en) | Aerial image capturing method and system for unmanned aerial vehicle to survey traffic accident scene | |
| CN102622767B (en) | Method for positioning binocular non-calibrated space | |
| CN106571039A (en) | Automatic snapshot system for highway traffic offence | |
| CN110297498A (en) | A kind of rail polling method and system based on wireless charging unmanned plane | |
| CN111508260A (en) | Vehicle parking space detection method, device and system | |
| CN105015419A (en) | Automatic parking system and method based on stereoscopic vision localization and mapping | |
| CN104754302A (en) | Target detecting tracking method based on gun and bullet linkage system | |
| CN104134352A (en) | Video vehicle characteristic detection system and detection method based on combination of long exposure and short exposure | |
| CN104217439A (en) | Indoor visual positioning system and method | |
| CN108320575A (en) | A kind of guiding of parking stall and reverse vehicle searching system and its parking space-detecting device, method | |
| CN104050679A (en) | Illegal parking automatic evidence obtaining method | |
| CN106060479A (en) | Smart pasture monitoring system based on beyond visual range video technology | |
| CN106781680A (en) | A kind of curb parking intelligent control method based on the detection of image empty parking space | |
| CN104253950A (en) | Intelligent dimming method and system of surveillance camera | |
| CN109094556A (en) | A kind of automatic parking method and system based on parking stall characteristic point | |
| CN106097724A (en) | Outdoor portable transport information Video Detection and acquisition system and detection method thereof | |
| CN110009675A (en) | Generate method, apparatus, medium and the equipment of disparity map | |
| CN112785709A (en) | TBM (tunnel boring machine) carrying type surrounding rock fracture reconstruction identification method and device, storage medium and equipment | |
| CN107193286B (en) | Bridge live-action digital acquisition method | |
| CN111147764A (en) | Leaky coaxial cable image acquisition method and system based on real-time image recognition | |
| CN116309370A (en) | Real-time detection method and system for apparent diseases of concrete dam |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |