CN205829834U - A kind of Intelligent aerial photography system - Google Patents
A kind of Intelligent aerial photography system Download PDFInfo
- Publication number
- CN205829834U CN205829834U CN201620526241.4U CN201620526241U CN205829834U CN 205829834 U CN205829834 U CN 205829834U CN 201620526241 U CN201620526241 U CN 201620526241U CN 205829834 U CN205829834 U CN 205829834U
- Authority
- CN
- China
- Prior art keywords
- image
- intelligent
- unmanned plane
- aerial photography
- aerial
- 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.)
- Expired - Fee Related
Links
Landscapes
- Image Processing (AREA)
Abstract
The utility model discloses a kind of Intelligent aerial photography system, it is characterised in that: include that Aerial Images harvester and Aerial Images processing means, described Aerial Images harvester include aerial photography aircraft and camera head；Described Aerial Images processing means includes the advanced processes device on carry-on primary treatment device and ground；Described aerial photography aircraft uses unmanned plane, and described unmanned plane includes that airflight subsystem and ground control subsystem；Described camera head includes the high-definition camera being installed on below unmanned aerial vehicle body；Also include the method that primary treatment device carries out the method for image primary treatment and advanced processes device carries out high vision process.The system of taking photo by plane that this utility model provides includes the unmanned plane independently continuing a journey and automatically control, and the collection and the image that automatically carry out high-definition image repeatedly process simultaneously, it is possible to obtain completely, image clearly.
Description
Technical field
This utility model relates to one and takes photo by plane field, particularly a kind of Intelligent aerial photography system.
Background technology
It is that a collection singlechip technology, sensor technology of taking photo by plane, GPS navigation are taken photo by plane technology, the communication service of taking photo by plane that unmanned plane is taken photo by plane
Many technology such as technology, flight control technology, task control technology, programming technique also rely on the high-tech product of hardware, its
Filmed image has high-resolution, large scale, little area, the advantage of high Up-to-date state, is particularly suitable for obtaining banding area and takes photo by plane
Image (highway, railway, river, reservoir, coastline etc.).And UAV provides easy to operate for photography of taking photo by plane,
It is prone to the remote sensing platform of transition；Taking off landing is limited less by place, on playground, highway or other openr ground
Landing, its stability, safety are good, and transition etc. is very easy to；Small portable, low-noise energy-saving, the most motor-driven, image is clear
Clear, lightness, miniaturization, the intelligent outstanding feature that unmanned plane is taken photo by plane especially；But the problem that there is also following aspect.
At present, unmanned plane on the market mainly uses lithium polymer battery as major impetus, and flying power is typically at 20 minutes
Between 30 minutes, because of technical elements difference difference, but most of cruising time is all within 45 minutes.By
Needing to alleviate as far as possible take-off weight in unmanned plane, so heavier high capacity cell cannot be carried, most of unmanned planes maintain
After ten a few minutes to 20 minutes flight, it is necessary for they replacing batteries artificial or has plugged charging wire, having caused generally going out
Door will carry three or four pieces of batteries.This is one fatal short slab of Development of UAV, greatly limit the entirety of unmanned plane industry
Development, to the benign development that promotion unmanned plane market is lasting, solves unmanned plane battery durable capability problems extremely urgent.
Unmanned plane awing needs the operation carrying out flying, and automatic charging, photographed data transmit and ground communication control
Deng, if using manual operation or directly from ground control, it will be unfavorable for the work of unmanned plane, it is possible to carry out unmanned plane
Intelligent flight will become extremely important.
Existing taking photo by plane all uses unmanned plane to shoot, and then beams back the mode that ground carries out processing, but the content one taken photo by plane
As compare many, transmission data many, captured data through process just beams back ground, add data transmission total amount,
Reduce data transmission bauds, reduce the efficiency of image procossing simultaneously；The efficiency comparison of ground image procossing is low simultaneously.
Utility model content
Goal of the invention of the present utility model is: for the problem of above-mentioned existence, it is provided that one includes independently continuing a journey and automatically controls
The unmanned plane of system, the collection and the image that automatically carry out high-definition image repeatedly process simultaneously, obtain complete, the intelligence of picture rich in detail
Take photo by plane system.
The technical solution adopted in the utility model is as follows:
This utility model one Intelligent aerial photography system, including Aerial Images harvester and Aerial Images processing means, described boat
Clap image collecting device and include aerial photography aircraft and camera head；Described Aerial Images processing means includes carry-on primary
The advanced processes device on processing means and ground.
This utility model one Intelligent aerial photography system, described aerial photography aircraft uses unmanned plane, and described unmanned plane includes sky
Middle flight subsystem and ground control subsystem；Described airflight subsystem includes fuselage, wing, power supply and Based Intelligent Control
Module, Based Intelligent Control mould connects all devices on unmanned plane；Described ground controls subsystem and includes wireless data transfer module
And control module.
This utility model one Intelligent aerial photography system, described power supply includes that charging device and accumulator, described charging device are energy
Amount collection device；Described energy collecting device includes device of solar generating, wind power generation plant and pressure generating set；Energy
Amount collection device is connected with accumulator, is used for charging a battery.
Above structure, the setting of energy collecting device, the continuation of the journey problem of present unmanned plane can be solved, provide for unmanned plane and hold
Continuous power.Device of solar generating can be passed through in the case of illumination, generate electricity, for storage and the flight of electricity
Use；There is the biggest air to flow the most simultaneously, produce wind-force, be used for generating electricity；The use of pressure generating set, equally
The kinetic energy of unmanned plane can be converted into electric energy, the flight for unmanned plane provides more energy.
This utility model one Intelligent aerial photography system, described intelligent control module includes aspect control module and wireless data
Transport module；Described intelligent control module, for controlling the normal flight of unmanned plane, receive simultaneously ground control information and
Send the flight information of unmanned plane.
Above structure, intelligent control module can gather the data that unmanned plane during flying needs, by algorithm and the control of program,
Carry out Intelligent flight, do not have ground control in the case of, also can fly.
This utility model one Intelligent aerial photography system, described camera head includes the high-definition camera being installed on below unmanned aerial vehicle body
Head, is used for carrying out image acquisition.
This utility model one Intelligent aerial photography system, the method that described primary treatment device carries out primary treatment includes: (1), enter
The pretreatment of row image, carries out gray processing, image enhaucament, filtering and binaryzation to the image inputted and overcomes image disruption；(2)、
Carry out the judgement of nearly multiimage, such as, the image p collected and image q is extracted characteristic point, by image p and the spy of image q
Levying and a little carry out similarity comparison, similarity formula is:Wherein, a is two images
The feature of coupling is counted, and b is that after mating, remaining feature is counted, and N (p) is that the feature of image p is counted, and Nmax is two images
The feature of the more image of middle eigenvalue is counted, and when similarity S, (q, time p) more than 0.8, deletes the image that eigenvalue is few；(3), by institute
The image gathered is pressed shooting time and is sorted out, and the image that similarity in previous step is less than more than 0.3 0.8 simultaneously is sorted out；(4)、
Image after operation above is compressed, is sent to ground control centre.
The image of collection can be carried out preliminary process by above method, is deleted by the image of picture noise and repetition,
Simplify transmission data, improve the speed of transmission, the most beneficially reprocessing on ground.
This utility model one Intelligent aerial photography system, the method that described advanced processes device carries out image procossing includes: step one:
By the image decompression of pretreatment, carry out the correction of wide-angle distortion simultaneously；Step 2: the image after correction is carried out at motion blur
Reason；Step 3: the image after process splices, obtains completely, image clearly；The input of image in described image procossing
Output uses flowing water I/O mode, first processes two width images, at the new image of input, and input picture and previous
The edge of stitching image mates.
In above method, image, after distortion correction, Fuzzy Processing and splicing, will obtain complete and image clearly, simultaneously
Flowing water I/O mode instead of original I/O mode, and I/O mode originally is: all images to be spliced
Splicing after fully entering, the image spliced during output stores as an entirety and shows, flowing water input and output again
Mode can save the time of feature extraction and matching, the data volume simultaneously reducing routine processes and the memory headroom taken, and keeps away
Exempting from overflow error occur during program performs, it is ensured that being normally carried out of program, and the image spliced is the most, the time used is the shortest,
Advantage is the most obvious.
This utility model one Intelligent aerial photography system, the bearing calibration of described wide-angle distortion is: include that (1) selects net template,
Its grid distance is 15mm, and grid distance is the biggest, it is thus achieved that intersection point the fewest, undistorted distance gets over inaccuracy, and grid distance is more
Little, amount of calculation is the biggest, and 15mm is appropriately distance；(2) extract characteristic point and determine center of distortion；Extract characteristic point i.e. to carry
Taking distortion and the ideal coordinates in net template cross point, the distortion coordinate wherein detecting each height uses SUSAN Corner Detection
Method, when extracting ideal coordinates, using the ultimate range of adjacent mesh intersection point in fault image as ideal grid spacing, then root
The ideal coordinates of each intersection point are determined according to ideal grid spacing and its end points；Center of distortion is only precisely located, and preferable
Mesh spacing, just can calculate each some ideal distance to center of distortion；The method finding optimum center of distortion: with each net
Lattice point is reference to the relation between distortion distance and the ideal distance of center of distortion, it is determined that in the most optimum distortion of candidate point
The heart.If ideal point is ranked up in a certain order, then after corresponding distortion point sequence the most on a corresponding position so that corresponding
Distortion point sequence after most point of counting the most on a corresponding position it is determined that center of distortion；(3) distortion factor is solved
Recover image, use piecewise fitting restoring method: the scope that whole ideal distance comprises be divided into and have the several of overlapping region each other
Part, then simulates distortion curve respectively to the point in these several parts, solves distortion factor, utilizes distortion factor segmentation extensive
Complex pattern, obtains the recovery figure of fault image.Wherein, in the function of first section of matched curve, constant term equal to 0 or is approximately equal to 0,
The maximum of the quadratic equation simulated of latter end more than distance center of distortion point furthest in fault image to center of distortion away from
From and the symmetrical centre value of equation be greater than the half of the catercorner length recovering image；The matching of mid portion is according to camera lens
The size of the angle of visual field or the order of severity of distortion carry out piecewise fitting, but must be sure that adjacent two intersegmental with the presence of intersection point.
In above method, net template compares other template can obtain more reflection distortion pass in the place that pattern distortion is serious
The point of system, grid is the least simultaneously, it is thus achieved that intersection point the most and undistorted distance is the most accurate.In piecewise fitting restoring method,
After segmentation, each segmentation needs the some Relatively centralized of matching, and matching distortion curve out more can be anti-than wall scroll polynomial curve
Reflecting distortion relation, and the span of piecewise fitting is little, can reduce polynomial number of times, the curve of matching is more accurate.
This utility model one Intelligent aerial photography system, the method that described motion blur processes is: (1) is come by the method for frequency domain
Realize solving of motion blur direction；The method for solving in motion blur direction is: carry out Hough transform: u-v plane become
Changing accumulator into, set up an accumulator A (ρ, θ), the span of ρ is the absolute value of the distance in image between angle point, and θ takes
Value space is between negative 90 degree to 90 degree, and by initial value to 0；Each non-zero points in u-v plane is taken according to different θ
Value, obtains ρ according to ρ=μ cos θ+ν sin θ, adds 1 by the value of corresponding accumulator element；Judge the maximum of accumulator,
The angle, θ that maximum is corresponding is exactly motion blur angle；Maximum one vector of composition of each angle after taking Hough transform,
Then this vector equivalent vector of one m dimension is done convolution, ask the maximum of convolution, corresponding angle to obscure angle exactly
Degree；(2) calculating of motion blur length is carried out: rotate broad image, obtain horizontal blur image；Calculated level broad image
Differentiation function；Computing differential image auto-correlation function；The data of each row are added and obtain data line；Draw Sad curve,
Determine minimum point, so that it is determined that blurred length；(3) by liftering method, broad image is strengthened.
In above method, the method for frequency domain realizes simple, it is thus achieved that spectrogram be easy to subsequent calculations blurred length, save and calculate
Time.Broad image carries out derivative operation along blur direction, and the derivative value after computing there will be contrary symbol at two ends, will
Derived function carries out auto-correlation computation, and the result obtained takes minima at positive and negative blurred length 2, according to the point of minima
Position can calculate blurred length.It is little with the error of picture rich in detail that what Wiener Filter Method obtained strengthens image, the shadow of noise simultaneously
Ring little.The method for solving in described motion blur direction includes: from the frequency spectrum formula of broad image:
| understanding in G (μ, ν)=| F (μ, ν) | | H (μ, ν) |, blur direction is vertical with frequency spectrum direction, may determine that mould by the direction of frequency spectrum
Sticking with paste direction, frequency spectrum direction can be judged by the linear character of detection frequency spectrum, and detecting linear method is Hough transform,
There is certain error between result of calculation and the exact value of Hough transform, error can be reduced by further decision algorithm, additional
Evaluation algorithm be: maximum one vector of composition of each angle after taking Hough transform, then to this vector with a m
The equivalent vector of dimension does convolution, asks the maximum of convolution, corresponding angle to obscure angle exactly.
This utility model one Intelligent aerial photography system, the joining method of described image includes: (1) carries out feature by SIFT algorithm and carries
Take；(2) characteristic matching, by ratio criterion, carries out the coupling of characteristic vector, the even ratio of two Similarity value little
In particular value, then it is assumed that specific vector and one of them characteristic vector are couplings；(3) camera parameter is estimated, including rough estimate
Meter and fine control, i.e. calculate the parameters of camera, then carry out error transfer factor according to the transformation matrix between image；(4) profit
It is exposed compensating by parameterless method；(5) lookup of splicing seams, calculates the similarity of pixel on splicing line, when similar
Line corresponding when spending the highest is splicing line；(6) blending algorithm is utilized to carry out image co-registration；Described blending algorithm is multiresolution
Batten blending algorithm, it realizes process and is: set up laplacian pyramid LA, LB of two image A, B to be spliced respectively；
Set up the pyramid of the image of mark composograph H value；Fusion image pyramid LG is become with H-shaped according to LA, LB；According to
LG obtains fusion image.
Above method, SIFT algorithm has translation, rotates and illumination invariant, also has the invariance of scaling image
Invariance with radiation conversion, it is adaptable to carry out feature extraction.The method of the rough estimate in camera parameter estimation is: according to figure
Transformation matrix between Xiang determines the value of camera focus, and the matrix of every two adjacent images determines the value of a focal length, by these values
Sequence, takes the intermediate value value according to a preliminary estimate as camera focus；The method of fine control is: positive negative direction changes camera ginseng successively
Number size and the value of camera matrix, calculate matching double points error and, be allowed to constantly reduce, until adjacent twice error and
Difference less than threshold value 2*e-16.The process that realizes of the blending algorithm of image co-registration is: set up respectively two image A to be spliced,
Laplacian pyramid LA, LB of B；Set up the pyramid of the image of mark composograph H value；According to LA, LB and H
Form fusion image pyramid LG；Fusion image is obtained according to LG.This method can enable the image of varying strength smooth
Ground transition, has good robustness.
In sum, owing to have employed technique scheme, the beneficial effects of the utility model are:
1, this utility model is capable of the autonomous continuation of the journey of unmanned plane, set energy collecting device can pass through solar electrical energy generation,
The mode of wind-power electricity generation and pressure electricity-generating generates electricity, and provides more energy for unmanned plane, improves flying power, thus is
Take photo by plane and bring convenience.
2, it is provided with control system on unmanned plane of the present utility model, by the program arranged, it is possible to realize the autonomous navigation of unmanned plane,
Control for unmanned plane brings convenience.
Accompanying drawing explanation
Fig. 1 is the structural representation of this utility model a kind of Intelligent aerial photography system.
Fig. 2 is the structural representation of aerial photography aircraft.
Detailed description of the invention
Below in conjunction with the accompanying drawings, this utility model is described in detail.
In order to make the purpose of this utility model, technical scheme and advantage clearer, below in conjunction with drawings and Examples,
This utility model is further elaborated.Should be appreciated that specific embodiment described herein is only in order to explain this reality
With novel, it is not used to limit this utility model.
As it is shown in figure 1, this utility model one Intelligent aerial photography system, process dress including Aerial Images harvester and Aerial Images
Putting, described Aerial Images harvester includes aerial photography aircraft and camera head；Described Aerial Images processing means includes flight
Primary treatment device on device and the advanced processes device on ground.
As in figure 2 it is shown, this utility model one Intelligent aerial photography system, described aerial photography aircraft uses unmanned plane, described nothing
Man-machine include that airflight subsystem and ground control subsystem；Described airflight subsystem includes fuselage, wing, power supply
And intelligent control module, Based Intelligent Control mould connects all devices on unmanned plane；Described ground controls subsystem and includes wireless number
According to transport module and control module；Described power supply includes that charging device and accumulator, described charging device are energy collecting device；
Described energy collecting device includes device of solar generating, wind power generation plant and pressure generating set；Energy collecting device with
Accumulator connects, and is used for charging a battery；Described intelligent control module includes that aspect control module and wireless data pass
Defeated module；Described intelligent control module, for controlling the normal flight of unmanned plane, receives the control information on ground simultaneously and sends out
Send the flight information of unmanned plane.
This utility model one Intelligent aerial photography system, described camera head includes the high-definition camera being installed on below unmanned aerial vehicle body
Head, is used for carrying out image acquisition.
This utility model one Intelligent aerial photography system, the method that described primary treatment device carries out primary treatment includes: at the beginning of described
Level processing means carries out the method for pretreatment and includes: (1), carry out the pretreatment of image, the image of input is carried out gray processing,
Image enhaucament, filtering and binaryzation overcome image disruption；(2), the judgement of nearly multiimage, the figure that such as will collect are carried out
As p and image q extracts characteristic point, the characteristic point of image p and image q being carried out similarity comparison, similarity formula is:Wherein, a is that the feature of two images match is counted, and b is remaining spy after coupling
Levying and count, N (p) is that the feature of image p is counted, and Nmax is that in two images, the feature of the more image of eigenvalue is counted, and works as similarity
(q, time p) more than 0.8, deletes the image that eigenvalue is few to S；(3), by acquired image press shooting time to sort out, will simultaneously
In previous step similarity more than 0.3 less than 0.8 image sort out；(4), the image after operation above is compressed,
It is sent to ground control centre.
This utility model one Intelligent aerial photography system, the method that described advanced processes device carries out image procossing includes: step one:
By the image decompression of pretreatment, carry out the correction of wide-angle distortion simultaneously；Step 2: the image after correction is carried out at motion blur
Reason；Step 3: the image after process splices, obtains completely, image clearly；The input of image in described image procossing
Output uses flowing water I/O mode, first processes two width images, at the new image of input, and input picture and previous
The edge of stitching image mates.
This utility model one Intelligent aerial photography system, the bearing calibration of described wide-angle distortion is: include that (1) selects net template,
Its grid distance is 15mm；(2) extract characteristic point and determine center of distortion；Extract characteristic point and i.e. extract net template cross point
Distortion and ideal coordinates, wherein detect each height distortion coordinate use SUSAN corner detection approach；Find optimum distortion
The method at center: with each mesh point to the relation between distortion distance and the ideal distance of center of distortion as reference, it is determined that candidate
The most optimum center of distortion of point；If ideal point is ranked up in a certain order, then also accordingly after corresponding distortion point sequence
Position on so that after corresponding distortion point sequence, most point of counting the most on a corresponding position is it is determined that center of distortion；
(3) solve distortion factor and recover image, use piecewise fitting restoring method: the scope that whole ideal distance comprises be divided into mutually
Between have several parts of overlapping region, then the point in these several parts is simulated distortion curve respectively, solves distortion factor, profit
Recover image with distortion factor segmentation, obtain the recovery figure of fault image；Wherein, constant term in the function of first section of matched curve
Equal to 0 or be approximately equal to 0, the maximum of the quadratic equation simulated of latter end is farthest more than distance center of distortion in fault image
Point be greater than the half of catercorner length recovering image to the distance of center of distortion and the symmetrical centre value of equation；Middle
The matching of part carrys out piecewise fitting according to the size of the angle of view or the order of severity of distortion, but must be sure that adjacent two
Intersegmental with the presence of intersection point.
This utility model one Intelligent aerial photography system, the method that described motion blur processes is: (1) is come by the method for frequency domain
Realize solving of motion blur direction；The method for solving in motion blur direction is: carry out Hough transform: u-v plane become
Changing accumulator into, set up an accumulator A (ρ, θ), the span of ρ is the absolute value of the distance in image between angle point, and θ takes
Value space is between negative 90 degree to 90 degree, and by initial value to 0；Each non-zero points in u-v plane is taken according to different θ
Value, obtains ρ according to ρ=μ cos θ+ν sin θ, adds 1 by the value of corresponding accumulator element；Judge the maximum of accumulator,
The angle, θ that maximum is corresponding is exactly motion blur angle；Maximum one vector of composition of each angle after taking Hough transform,
Then this vector equivalent vector of one m dimension is done convolution, ask the maximum of convolution, corresponding angle to obscure angle exactly
Degree；(2) calculating of motion blur length is carried out: rotate broad image, obtain horizontal blur image；Calculated level broad image
Differentiation function；Computing differential image auto-correlation function；The data of each row are added and obtain data line；Draw Sad curve,
Determine minimum point, so that it is determined that blurred length；(3) by liftering method, broad image is strengthened.
This utility model one Intelligent aerial photography system, the joining method of described image includes: (1) carries out spy by SIFT algorithm
Levy extraction；(2) characteristic matching, by ratio criterion, carries out the ratio of the coupling of characteristic vector, even two Similarity value
Value is less than particular value, then it is assumed that specific vector and one of them characteristic vector are couplings；(3) camera parameter is estimated, including
Rough estimate and fine control, i.e. calculate the parameters of camera, then carry out error transfer factor according to the transformation matrix between image；(4)
The method utilizing band parameter is exposed compensating；(5) lookup of splicing seams, calculates the similarity of pixel on splicing line, works as phase
The line corresponding time the highest like degree is splicing line；(6) blending algorithm is utilized to carry out image co-registration；Described blending algorithm is differentiates more
Rate batten blending algorithm, it realizes process and is: set up laplacian pyramid LA, LB of two image A, B to be spliced respectively；
Set up the pyramid of the image of mark composograph H value；Fusion image pyramid LG is become with H-shaped according to LA, LB；According to
LG obtains fusion image.
The foregoing is only preferred embodiment of the present utility model, not in order to limit this utility model, all in this practicality
Any amendment, equivalent and the improvement etc. made within novel spirit and principle, should be included in guarantor of the present utility model
Within the scope of protecting.
Claims (5)
1. an Intelligent aerial photography system, it is characterised in that: include that Aerial Images harvester and Aerial Images processing means, described Aerial Images harvester include aerial photography aircraft and camera head；Described Aerial Images processing means includes the advanced processes device on carry-on primary treatment device and ground.
A kind of Intelligent aerial photography system the most according to claim 1, it is characterised in that: described aerial photography aircraft uses unmanned plane, and described unmanned plane includes that airflight subsystem and ground control subsystem；Described airflight subsystem includes fuselage, wing, power supply and intelligent control module, and Based Intelligent Control mould connects all devices on unmanned plane；Described ground controls subsystem and includes wireless data transfer module and control module.
A kind of Intelligent aerial photography system the most according to claim 2, it is characterised in that: described power supply includes that charging device and accumulator, described charging device are energy collecting device；Described energy collecting device includes device of solar generating, wind power generation plant and pressure generating set；Energy collecting device is connected with accumulator, is used for charging a battery.
A kind of Intelligent aerial photography system the most according to claim 2, it is characterised in that: described intelligent control module includes aspect control module and wireless data transfer module；Described intelligent control module, for controlling the normal flight of unmanned plane, receives the control information on ground simultaneously and sends the flight information of unmanned plane.
A kind of Intelligent aerial photography system the most according to claim 1, it is characterised in that: described camera head includes the high-definition camera being installed on below unmanned aerial vehicle body, is used for carrying out image acquisition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201620526241.4U CN205829834U (en) | 2016-05-31 | 2016-05-31 | A kind of Intelligent aerial photography system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201620526241.4U CN205829834U (en) | 2016-05-31 | 2016-05-31 | A kind of Intelligent aerial photography system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN205829834U true CN205829834U (en) | 2016-12-21 |
Family
ID=57568003
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201620526241.4U Expired - Fee Related CN205829834U (en) | 2016-05-31 | 2016-05-31 | A kind of Intelligent aerial photography system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN205829834U (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105872413A (en) * | 2016-05-31 | 2016-08-17 | 成都德善能科技有限公司 | Intelligent aerial photographing system |
-
2016
- 2016-05-31 CN CN201620526241.4U patent/CN205829834U/en not_active Expired - Fee Related
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105872413A (en) * | 2016-05-31 | 2016-08-17 | 成都德善能科技有限公司 | Intelligent aerial photographing system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105872413A (en) | Intelligent aerial photographing system | |
| US11288884B2 (en) | UAV real-time path planning method for urban scene reconstruction | |
| CN110163177B (en) | Unmanned aerial vehicle automatic sensing and identifying method for wind turbine generator blades | |
| CN110297498A (en) | A kind of rail polling method and system based on wireless charging unmanned plane | |
| CN109739254B (en) | Unmanned aerial vehicle adopting visual image positioning in power inspection and positioning method thereof | |
| WO2022213612A1 (en) | Non-contact three-dimensional human body size measurement method | |
| CN107729808A (en) | A kind of image intelligent acquisition system and method for power transmission line unmanned machine inspection | |
| CN110189315B (en) | Unmanned aerial vehicle automatic positioning method for blades of wind turbine generator | |
| CN111899172A (en) | Vehicle target detection method oriented to remote sensing application scene | |
| CN102831446A (en) | Image appearance based loop closure detecting method in monocular vision SLAM (simultaneous localization and mapping) | |
| CN106762451A (en) | Fan blade damage detection method, device and system based on unmanned aerial vehicle | |
| CN107911429A (en) | A kind of online traffic flow monitoring method in unmanned plane high in the clouds based on video | |
| WO2014190651A1 (en) | Photovoltaic power predication method based on ground-based nephogram | |
| CN102929288A (en) | Unmanned aerial vehicle inspection head control method based on visual servo | |
| CN114529817A (en) | Unmanned aerial vehicle photovoltaic fault diagnosis and positioning method based on attention neural network | |
| CN106096621B (en) | Based on vector constraint drop position detection random character point choosing method | |
| CN105334347B (en) | A kind of particle image velocimetry detection system and method based on unmanned plane | |
| CN113158833B (en) | Unmanned vehicle control command method based on human body posture | |
| CN106327528A (en) | Moving object tracking method and operation method of unmanned aerial vehicle | |
| CN111247564A (en) | Method for constructing digital earth surface model, processing equipment and system | |
| CN112613334A (en) | High-precision autonomous inspection image identification method of unmanned aerial vehicle on power transmission line | |
| CN205829834U (en) | A kind of Intelligent aerial photography system | |
| CN114627074A (en) | Ground shooting fan blade real-time monitoring method based on deep learning | |
| CN103345765A (en) | Detecting device and detecting method for moving objects under mobile platform based on DSP+FPGA | |
| Wang et al. | Oriented object detection in optical remote sensing images using deep learning: A survey |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CB03 | Change of inventor or designer information | ||
| CB03 | Change of inventor or designer information |
Inventor after: Chen Cong Inventor before: Xie Min |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20170417 Address after: 529000 Jiangmen, Guangdong, Pengjiang District, No. 1, Donghua Road, room 20 (No. 01, No. 111) Patentee after: Pengjiang District, Jiangmen City, the exchange of goods Advertising Co., Ltd. Address before: 610000 Chengdu City, Wuhou District Province, the South Ring Road, No. two, No. 1, No. 1, floor 31, No. 5 Patentee before: CHENGDU DESHANNENG TECHNOLOGY CO., LTD. |
|
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20161221 Termination date: 20180531 |