CN103325255B - The method of region transportation situation detection is carried out based on photogrammetric technology - Google Patents
The method of region transportation situation detection is carried out based on photogrammetric technology Download PDFInfo
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Abstract
The invention discloses a kind of method of carrying out region transportation situation detection based on photogrammetric technology, comprise implantation of device, obtain traffic key element, obtain the step such as the motion feature of traffic key element, the judgement of traffic behavior, the inventive method utilizes photogrammetric technology to detect region transportation situation, and not by natural environment influence, rate of false alarm is low, sensing range is large, attainable feature richness.
Description
Technical field
The invention belongs to region transportation situation monitoring field, particularly a kind of method of carrying out region transportation situation detection based on photogrammetric technology.
Background technology
Many scientific & technical corporation of current home and abroad are all proposed the video intelligent traffic products of oneself.Such as: the VD video vehicle detection system ' of Belgian TrafCon company research and development, " epoch No. one " of Astronavigation Age Science and Technology Ltd. of Beijing, the VTD3000 system of Shenzhen Hagongda Traffic Electronic Technology Co., Ltd., said system can realize traffic data collection, traffic incidents detection and intersection signal control optimization etc.
Its core technology of these systems is the change using video, and Utilization prospects and background segmentation techniques check traffic events, but there is the shortcomings such as large by natural environment influence, rate of false alarm is high, examination scope is limited, and effect is unsatisfactory in actual applications.
The photogrammetric information science referred to by the acquisition of image research target subject spatial information, process, extraction and result provision.Photogrammetry is the subdiscipline of mapping science, and its main task being topomap for surveying and drawing various engineer's scale, setting up digital terrain model (DTM), for various Geographic Information System and land information system provide basic data.
The subject matter that photogrammetry solves is geometry location, namely determines the size of subject, shape and locus.The ultimate principle of geometry location comes from the forward intersection method of surveying, and it is according to two known photography websites and two known photography direction lines, and intersection goes out to form the three-dimensional coordinate of the point to be located of these two photography light.
The difference of the position residing for video camera during photography, photogrammetry can be divided into terrestrial photogrammetry, photogrammetric measurement and space photogrammetry.According to the difference of application, photogrammetry can be divided into again field observation to measure the large class with non-topographic photogrammetry two.According to the difference (being also the difference of historical stage) of technical finesse means, photogrammetry can be divided into analog photogrammetry, analytical photogrammetry and digital photogrammetry again.
Summary of the invention
One is the object of the present invention is to provide to utilize photogrammetric technology to detect region transportation situation, not by natural environment influence, rate of false alarm is low, sensing range the is large method of carrying out region transportation situation detection based on photogrammetric technology.
The technical solution realizing the object of the invention is:
Carry out a method for region transportation situation detection based on photogrammetric technology, comprise the following steps:
Step one: implantation of device: the photography at least two intervals, picture pick-up device are set;
Step 2: utilize photography, picture pick-up device to obtain the volume coordinate collection of all things in detected region according to photogrammetric survey method, obtain a cloud, according to the dense degree of a cloud, distribution situation and coordinate information, a cloud is divided into different traffic key elements, wherein, traffic key element comprises barrier, the vehicles, means of transportation and people, and identifying the physical features of each traffic key element, its physical features comprises the position of traffic key element, size, quantity;
Step 3: carry out continuous detecting to region, determines traffic key element motion feature in three dimensions according to the change of the coordinate position of a cloud, and its motion feature comprises the direction of motion, track and trend;
Step 4: the judgement to traffic behavior:
(1) judge whether according to the physical features of the barrier detected the quantity and the degree that there is hidden trouble of traffic and hidden trouble of traffic;
(2) judge whether according to the shape of means of transportation or the change of position the quantity and the degree that there is hidden trouble of traffic and hidden trouble of traffic;
(3) vehicles and the motion feature of people and the traffic rules in this region are contrasted, detect break in traffic rules and regulations;
(4) service condition of traffic resource is calculated as the detection of road occupying rate, parking stall use, queue length, congestion in road situation according to the position of the vehicles and people, quantity, relativeness.
The present invention compared with prior art, its remarkable advantage:
(1) the present invention utilizes photogrammetric technology by the digitizing of traffic key element, utilizes digitizing means to improve Vehicle Detection and management level.
(2) testing result of the present invention is not by the impact of the physical environments such as shadow, and can accurately distinguish shade, hot spot and vehicle, barrier, pedestrian etc., accuracy of judgement degree is higher.
(3) the present invention utilizes measurement moment image to carry out traffic condition detection, and the accuracy in detection of moving object is high.
(4) the present invention can carry out timesharing detection to multiple region, and does not affect accuracy of detection, and plant factor is higher.
Below in conjunction with accompanying drawing, the present invention is described in further detail.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the inventive method.
Embodiment
A kind of method of carrying out region transportation situation detection based on photogrammetric technology of the present invention, comprises the following steps:
Step one: implantation of device: photography or camera head that at least two intervals are set;
Step 2: utilize photography, picture pick-up device to obtain the volume coordinate collection of all things in detected region according to photogrammetric survey method, obtain a cloud, according to the dense degree of a cloud, distribution situation and coordinate information, a cloud is divided into different traffic key elements, wherein, traffic key element comprises barrier, the vehicles, means of transportation and people, and identifying the physical features of each traffic key element, its physical features comprises the position of traffic key element, size, quantity;
Measuring method described here is prior art, and photogrammetric survey method is exactly the 3 D stereo coordinate pixel transitions on image being become space, coordinate points be integrated into photogrammetric in be called a cloud; The photogrammetric technology related generally to is camera calibration technology, gather the image in tested region, process image, stereogram Auto-matching, determine pixel space coordinate; Specific as follows:
Step 1: the demarcation of camera, namely according to arranging and the monumented point measured in advance, and by the inside and outside parameter of this monumented point correcting camera;
Step 2: the image gathering tested region;
Step 3: image is processed; Utilize image processing algorithm to process image, the image processing algorithm related to mainly contains: gray-level correction, filtering and noise reduction, image enhaucament, Iamge Segmentation, image binaryzation, image plus and minus calculation, feature point extraction scheduling algorithm;
Step 4: stereogram Auto-matching; The coupling fast and accurately that pixel is right, traffic zone pixel space coordinate extracts, and pixel space coordinate is the basis of reconstruction region traffic;
Step 5: determine pixel space coordinate, volume coordinate collection is a cloud;
Step 3: carry out continuous detecting to region, determines traffic key element motion feature in three dimensions according to the change of the coordinate position of a cloud, and its motion feature comprises the direction of motion, track and trend; I.e. comparison repeatedly check result, judges the difference situation of change of son point cloud, and then extrapolates motion and the situation of change of traffic key element;
Traffic key element motion feature calculates
Before and after contrast, twice testing result calculates the motion feature (comprise and whether being kept in motion, and direction of motion, movement velocity etc.) of people, car.Following several method can be used but be not limited to make in the following method, utilizing changes in coordinates to calculate motion feature.
1, obvious characteristic point method: registration of vehicle the most obviously, the position coordinates of unique point that the most easily identifies, through repeatedly checking the situation of change of the volume coordinate calculating this unique point.
2, minimum encirclement method: utilize minimum cube to wrap up all unique points, calculates cube centre coordinate situation of change.
3, average coordinates method: the volume coordinate of all unique points that can extract is averaged, calculates the situation of change of this mean value.
The direction of motion of the change calculations object to be detected of the coordinate utilizing above-mentioned each method to calculate and distance, utilize distance to calculate movement velocity divided by detection time, and when detected material is static, the change of this centre coordinate is less than measuring error all the time.
Step 4: the judgement to traffic behavior:
(1) judge whether according to the physical features of the barrier detected the quantity and the degree that there is hidden trouble of traffic and hidden trouble of traffic;
Road is shed quality testing and is surveyed: have the key element meeting and shed thing feature in region.As the barrier that about 20cm is square appears in highway, size is high at 1.5m, the long and wide pedestrian being less than 0.6m.
(2) judge whether according to the shape of means of transportation or the change of position the quantity and the degree that there is hidden trouble of traffic and hidden trouble of traffic;
The change of means of transportation detects: when detecting that the height change (can make to increase, also can make to drop to) of certain position of road reaches certain limit, thinking that the larger potential safety hazard of impact appears in this road, may be surface doming, surface collapse, bridge collapse etc.
(3) vehicles and the motion feature of people and the traffic rules in this region are contrasted, detect break in traffic rules and regulations;
(4) service condition of traffic resource is calculated as the detection of road occupying rate, parking stall use, queue length, congestion in road situation according to the position of the vehicles and people, quantity, relativeness.
Following distance detects: the obvious characteristic point method, average coordinates method etc. (see 3.3) that utilize minimum encirclement method, vehicle, calculates the spacing between vehicle.
Parking stall detect: the height change on parking stall, uprises and reaches certain numerical value, and the height as calculated this region increases more than 18cm, think this parking stall occupied or use.
The method obtaining traffic key element in step 2 is: utilize the automatic structure realm digital terrain model of photogrammetric technology, and the difference of the volume coordinate collection and digital terrain model that utilize photography, picture pick-up device to obtain all things being detected region according to photogrammetric survey method obtains traffic key element.
The method obtaining traffic key element in step 2 is: the volume coordinate collection relative difference utilizing photography, picture pick-up device to obtain all things in detected region according to photogrammetric survey method obtains traffic key element.
The method judged the change of the shape of means of transportation or position is judge whether hidden trouble of traffic exists and the quantity of hidden trouble of traffic and degree according to the shape of means of transportation in the zone digit ground model set up or the shape of means of transportation of position and detection or the change of position.
The method judged the change of the shape of means of transportation or position is judge whether hidden trouble of traffic exists and the quantity of hidden trouble of traffic and degree according to the change of means of transportation in repeated detection.
Utilize the inventive method comprehensively can detect region transportation situation:
1, traffic key element is utilized to judge to detect traffic
1) road sheds quality testing survey: have the key element meeting and shed thing feature in region.As the barrier that about 20cm is square appears in highway, size is high at 1.5m, the long and wide pedestrian being less than 0.6m
2) following distance detects: the obvious characteristic point method, average coordinates method etc. (see 3.3) that utilize minimum encirclement method, vehicle, calculates the spacing between vehicle.
3) parking stall detect: the height change on parking stall, uprises and reaches certain numerical value, and the height as calculated this region increases more than 8cm, think this parking stall occupied or use.
4) the traffic things of other influences safety detects, when detecting that the height change (can make to increase, also can make to drop to) of certain position of road reaches certain limit, thinking that the larger potential safety hazard of impact appears in this road, may be uncertainly shed thing, surface doming, surface collapse, bridge collapse etc.
5) vehicle differentiates
2, traffic hazard judges
The determination methods of traffic hazard mainly adopts following 4 kinds but be not limited to method in 4
1) vehicle clearance is too small, when even there is negative value.
2) there is the dense feature point of two groups or more.
3) meet Accident Characteristic: the length breadth ratio detected changes, length breadth ratio does not meet existing vehicle classification.
Detect that vehicle stops traffic hazard occurring.
3, flow detection
1) quantity in surveyed area: the quantity of adding up the traffic key element identified in certain spatial areas.
2) through the quantity in certain region: identify to there is motor behavior and the quantity of traffic key element by the identification in this region.
4, judgement violating the regulations
1) pedestrian: pedestrian appears in highway, there is pedestrian in car lane, during red light, pedestrian appears in road.
2) vehicle line ball: the edge feature point of vehicle is positioned at above graticule coordinate; Minimum cube of vehicle is surrounded by the part above graticule coordinate, and the wheel arch unique point of vehicle is positioned at above graticule coordinate.
3) drive in the wrong direction and detect: by judging that direction of motion to conform to this space communication rule degree, the situations such as retrograde, turning roadway craspedodrome, Through Lane turning can be checked.
4) stop: have vehicle in region, and remain static---within the scope of the sub-metrical error of change of the obvious characteristic of this vehicle of repeated detection, minimum encirclement, coordinate average.
5, means of transportation service condition judges
1) occupancy rate detection method: the number calculating occupancy utilizing the traffic element detected in this space; Utilize the change estimation occupancy of dispersed elevation; Utilize vehicle clearance to calculate occupancy, the plane projection in space deducts the summation in gap.
2) queue length detection method: the coordinate detecting queuing tail calculates the distance of this position such as coordinate and crossing; Calculate the coordinate difference that team starts and terminates;
3) traffic congestion: utilize form velocity estimated: travel speed obviously decline road gets congestion; Occupancy is utilized to judge: occupancy raises and occurs blocking up; Vehicle clearance is utilized to judge: the mean gap of vehicle diminishes, vehicle congestion.
4) parking stall is detected
Contour feature, minimum encirclement, unique point average is utilized to judge whether that vehicle is parked on parking stall, both service conditions of parking stall
Utilize the gap between vehicle, judged whether vacant parking stall, lateral direction of car spacing is greater than a parking stall distance and thinks there is parking stall.
Parking stall occurs that elevation changes, or has other barriers, thinks that parking stall is occupied.
6, means of transportation detect
1) size changes: can detect that the situations such as the barrier of road, road collapsion, bridge collapse occur.
2) position changes: sign label damages or artificially movement, likely causes traffic safety problem.
3) shape or position change: means of transportation or affiliated facility are damaged.
Utilize the automatic structure realm digital terrain model of photogrammetric technology, the feature that utilization photography, picture pick-up device obtain the method for traffic key element according to the volume coordinate collection of all things in the detected region of photogrammetric survey method acquisition and the difference of digital terrain model is as follows:
1, digital terrain model is set up
Utilize photogrammetric detection data to carry out digitizing to surveyed area, build the digital terrain model (DTM) comprising road, bridge, tunnel and parking lot and affiliated facility thereof.These data can as follow-up identification traffic key element and the basic data judging traffic behavior.
2, particular range detects
Only calculate the some cloud in the region of user's care, and only contrast the data in the spatial dimension in this region, improve computing velocity.
3, automatic Calibration
1) special sign is utilized to demarcate
Sign significantly easy to identify is installed in surveyed area, and measures the coordinate of each mark in advance.System identifies automatically according to the feature of mark, and according to the inside and outside parameter of coordinates correction camera of mark.
2) provincial characteristics is utilized to demarcate
Utilize the fixed objects such as the sign board on road, graticule, bridge, street lamp as the inside and outside parameter indicating point calibration camera.
3) demarcate in advance
The inside and outside parameter that the inside and outside parameter of calibration for cameras is current with the matching relationship determination camera controlling camera head angle and focal length parameter.
4, many scenes
Utilize photography, the The Cloud Terrace of picture pick-up device and the zoom function of camera, allow photography, the multiple scene of picture pick-up device poll, increase sensing range, raising plant factor.
5, known state is rejected
When surveyed area has working-yard, when the friendship such as the sign label piled up, Anti-collision barrel is installed and is executed.By arranging, system can ignore the testing result in feature region in the specific time period, avoids repetition of alarms.
Embodiment 1:
Follow above-mentioned technical step, certain road places barrier, barrier is separately positioned on distance video camera 200M, 500M and 900M place, the barrier of setting comprises, the tire of 195, the carton of 30x30x20cm and 10x20x20cm.
The photography of at least two interval 28.3m, picture pick-up device are set;
Build the DTM of road, in embodiment, measure a transversal section, the planimetric position of each cross-sectioning 8 grid points and elevation for every 15 meters.The three-dimensional coordinate of 8 grid points of one of them transversal section sees the following form:
| Grid points | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| Horizontal ordinate | 0.225 | 3.705 | 7.586 | 11.466 | 15.553 | 19.410 | 23.268 | 26.716 |
| Ordinate | 8.984 | 8.697 | 10.087 | 11.478 | 10.057 | 8.093 | 6.126 | 6.274 |
| Elevation | 42.388 | 42.407 | 42.505 | 42.483 | 42.556 | 42.481 | 42.387 | 42.421 |
Inside and outside parameter after camera calibration, comprising: the three-dimensional coordinate at photographic field lens center, the spatial attitude of photographic perpendicular, objective focal length and optical lens distortion coefficient.The internal and external orientation of two video-photographic equipment sees the following form:
| Internal and external orientation | Left photo | Right photo |
| Object lens x coordinate | 0.581 | 28.968 |
| Object lens y coordinate | 54.561 | 54.657 |
| Object lens z coordinate | 211.228 | 209.468 |
| The photo angle of pitch | 0.129909731373891 | -0.149957529672916 |
| The photo angle of roll | -0.0907850031756845 | -0.0869651113684297 |
| Photo rotation angle | -0.036281204021685 | 0.00336946979484145 |
| Objective focal length | 6494.98 | 6219.05 |
| Optical lens distortion coefficient | -8.2E-09 | -4.4E-09 |
Calculation level cloud, utilizes the poor acquired disturbance thing information of some cloud and DTM:
Tire is detected all accurately, rectangle barrier at three position systems.
The barrier of outstanding ground 90mm is detected as at the tire height of the 900m carton that is 200mm, 10cm;
Tire height at 500m place is the barrier that the carton of 190mm, 10cm is detected as outstanding ground 95mm;
Tire height at 200m place is the barrier that the carton of 195mm, 10cm is detected as outstanding ground 95mm.
Especially there is identification plate at 800m place at the shade on road surface, utilizes photogrammetric survey method, and system accurately can detect that shade height is 2mm, and for not affecting the environment shade of traffic, system is accurately rejected.
Utilize above-mentioned detection method, can accurately cognitive disorders thing, shade.Utilize the method for cognitive disorders thing also accurately can identify the other influences traffic safety factor such as road swag, means of transportation change in location, highway pedestrian, visible the present invention can carry out widespread use in practice.
Embodiment 2:
Follow above-mentioned technical step, by the road at photography, the photography of picture pick-up device primary optical axis alignment distance, picture pick-up device 200m place, detect vehicle to drive in the wrong direction situation, the probability driven in the wrong direction due to vehicle is little, in system, the traffic rules of road both sides are exchanged, all like this vehicles are retrograde vehicle, and because this set can cause a large amount of vehicle to drive in the wrong direction, system cancels the vehicle automatic tracking function that drives in the wrong direction.
10 minutes test durations, through the oversize vehicle 13 of photography, picture pick-up device, minibus 29.
The retrograde vehicle of native system report is 42.
By above-mentioned experiment known this method, vehicle is driven in the wrong direction, craspedodromes of vehicle line ball, turning roadway, Through Lane turnings, the situation such as parking violation all have good behaviour, contain that the hidden trouble of traffic caused due to break in traffic rules and regulations is significant effective.
Embodiment 3:
In surveyed area, there is traffic mark board at 814m place, repeatedly detects 600 ~ 900m region, and the site error of the x, y, z of sign board coordinate is all less than 100mm, and physical dimension does not change, and System inventory means of transportation are intact.Deducibility goes out when the change in location of more than 10cm or the change of shape of more than 5cm occur means of transportation thus, system can automatic-prompting means of transportation state change, hidden trouble of traffic may be there is, for traffic administration person provides important information, for traffic trip people provides traffic support significant.
Embodiment 4:
By the 500m place of photography, picture pick-up device primary optical axis aligning surveyed area, the mean value of the difference of some cloud coordinate and ground coordinate in surveyed area, 50mm is changed to from 20mm, the high capacity waggon showed increased of road, the vehicle average velocity in vehicle detection region has 103km/h to drop to 86km/h, headstock is apart from being less than 200m, the prompting of blocking up may be there is in system generation road, system prompt is consistent with road driving truth, useful said method, has good behaviour to aspects such as the parking stall management in traffic congestion, queue length, parking lot.
Claims (3)
1. carry out a method for region transportation situation detection based on photogrammetric technology, it is characterized in that, comprise the following steps:
Step one: implantation of device: photography or camera head that at least two intervals are set;
Step 2: utilize photography, picture pick-up device to obtain the volume coordinate collection of all things in detected region according to photogrammetric survey method, obtain a cloud, according to the dense degree of a cloud, distribution situation and coordinate information, a cloud is divided into different traffic key elements, wherein, traffic key element comprises barrier, the vehicles, means of transportation and people, and identifying the physical features of each traffic key element, its physical features comprises the position of traffic key element, size, quantity; Wherein, the method obtaining traffic key element is: the volume coordinate collection relative difference that the volume coordinate collection relative difference utilizing photography, picture pick-up device to obtain all things in detected region according to photogrammetric survey method obtains traffic key element or utilizes photography, picture pick-up device to obtain all things in detected region according to photogrammetric survey method obtains traffic key element;
Step 3: carry out continuous detecting to region, determines traffic key element motion feature in three dimensions according to the change of the coordinate position of a cloud, and its motion feature comprises the direction of motion, track and trend;
Step 4: the judgement to traffic behavior:
(1) judge whether according to the physical features of the barrier detected the quantity and the degree that there is hidden trouble of traffic and hidden trouble of traffic;
(2) judge whether according to the shape of means of transportation or the change of position the quantity and the degree that there is hidden trouble of traffic and hidden trouble of traffic;
(3) vehicles and the motion feature of people and the traffic rules in this region are contrasted, detect break in traffic rules and regulations;
(4) road occupying rate, parking stall use, queue length, congestion in road situation is calculated according to the position of the vehicles and people, quantity, relativeness.
2. a kind of method of carrying out region transportation situation detection based on photogrammetric technology according to claim 1, it is characterized in that, described utilization photography, picture pick-up device obtains the method for the volume coordinate collection relative difference acquisition traffic key element of all things in detected region according to photogrammetric survey method, it is judge whether hidden trouble of traffic exists and the quantity of hidden trouble of traffic and degree according to the shape of means of transportation in the zone digit ground model set up or the shape of means of transportation of position and detection or the change of position to the method that the change of the shape of means of transportation or position judges.
3. a kind of method of carrying out region transportation situation detection based on photogrammetric technology according to claim 1, it is characterized in that, described utilization photography, picture pick-up device obtain all things in detected region volume coordinate collection relative difference according to photogrammetric survey method obtains the method for traffic key element, and it is judge whether hidden trouble of traffic exists and the quantity of hidden trouble of traffic and degree according to the change of means of transportation in repeated detection to the method that the change of the shape of means of transportation or position judges.
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Families Citing this family (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102015121952A1 (en) * | 2015-12-16 | 2017-06-22 | Valeo Schalter Und Sensoren Gmbh | Method for identifying an object in a surrounding area of a motor vehicle, driver assistance system and motor vehicle |
| CN107784844B (en) * | 2016-08-31 | 2021-05-14 | 百度在线网络技术（北京）有限公司 | Intelligent traffic signal lamp system and road environment detection method thereof |
| WO2018068317A1 (en) * | 2016-10-14 | 2018-04-19 | 富士通株式会社 | Vehicle wrong-way detection apparatus and method, and electronic device |
| CN107423679A (en) * | 2017-05-31 | 2017-12-01 | 深圳市鸿逸达科技有限公司 | A kind of pedestrian is intended to detection method and system |
| CN107221175B (en) * | 2017-05-31 | 2020-10-27 | 深圳市鸿逸达科技有限公司 | Pedestrian intention detection method and system |
| WO2019031002A1 (en) * | 2017-08-08 | 2019-02-14 | ソニー株式会社 | Control system and control method |
| TWI674210B (en) * | 2017-12-04 | 2019-10-11 | 財團法人資訊工業策進會 | System and method for detecting dangerous vehicle |
| CN109993976A (en) * | 2017-12-29 | 2019-07-09 | 技嘉科技股份有限公司 | Traffic accident monitors system and method |
| TWI651696B (en) * | 2017-12-29 | 2019-02-21 | 技嘉科技股份有限公司 | Systems and methods for monitoring traffic accident |
| CN108198419A (en) * | 2018-01-04 | 2018-06-22 | 山东华夏高科信息股份有限公司 | A kind of Intelligent road traffic safety hidden troubles removing system |
| CN108182811A (en) * | 2018-01-04 | 2018-06-19 | 山东华夏高科信息股份有限公司 | A kind of road safety perils detecting system |
| EP3625786A4 (en) * | 2018-08-06 | 2020-04-15 | Beijing Didi Infinity Technology and Development Co., Ltd. | Systems and methods for determining traffic conditions |
| CN109243181A (en) * | 2018-09-21 | 2019-01-18 | 深圳市轱辘汽车维修技术有限公司 | Traffic accident method for early warning, device, terminal device and storage medium |
| CN109345829B (en) * | 2018-10-29 | 2021-11-23 | 百度在线网络技术（北京）有限公司 | Unmanned vehicle monitoring method, device, equipment and storage medium |
| CN113299102A (en) * | 2021-03-27 | 2021-08-24 | 宁波工程学院 | Underground parking lot navigation method, system and storage medium |
| CN116453065B (en) * | 2023-06-16 | 2023-09-19 | 云途信息科技(杭州)有限公司 | Road surface foreign matter throwing identification method and device, computer equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202057328U (en) * | 2011-04-12 | 2011-11-30 | 清华大学 | Vehicle-mounted scale-free traffic accident scene quick surveying system based on binocular vision |
| CN102445186A (en) * | 2011-09-28 | 2012-05-09 | 中交第二公路勘察设计研究院有限公司 | Method for generating road design surface information by laser radar scan |
| CN102592454A (en) * | 2012-02-29 | 2012-07-18 | 北京航空航天大学 | Intersection vehicle movement parameter measuring method based on detection of vehicle side face and road intersection line |
| CN102661736A (en) * | 2012-05-17 | 2012-09-12 | 天津市星际空间地理信息工程有限公司 | Highway reorganization and expansion surveying method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE602007012321D1 (en) * | 2007-11-07 | 2011-03-10 | Tele Atlas Bv | METHOD AND ARRANGEMENT FOR SHAPING DISTANCE SENSORS ON PICTORIAL DATA |
-
2013
- 2013-06-29 CN CN201310269045.4A patent/CN103325255B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202057328U (en) * | 2011-04-12 | 2011-11-30 | 清华大学 | Vehicle-mounted scale-free traffic accident scene quick surveying system based on binocular vision |
| CN102445186A (en) * | 2011-09-28 | 2012-05-09 | 中交第二公路勘察设计研究院有限公司 | Method for generating road design surface information by laser radar scan |
| CN102592454A (en) * | 2012-02-29 | 2012-07-18 | 北京航空航天大学 | Intersection vehicle movement parameter measuring method based on detection of vehicle side face and road intersection line |
| CN102661736A (en) * | 2012-05-17 | 2012-09-12 | 天津市星际空间地理信息工程有限公司 | Highway reorganization and expansion surveying method |
Non-Patent Citations (1)
| Title |
|---|
| 车载式三维信息快速采集及数据处理系统;苏岳龙;《中国优秀硕士学位论文全文数据库（电子期刊）工程科技Ⅱ辑》;20051215(第08期);第3-13页 * |
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