CN109584512A - A kind of mountain region disaster method for early warning and early warning system - Google Patents
A kind of mountain region disaster method for early warning and early warning system Download PDFInfo
- Publication number
- CN109584512A CN109584512A CN201811550115.2A CN201811550115A CN109584512A CN 109584512 A CN109584512 A CN 109584512A CN 201811550115 A CN201811550115 A CN 201811550115A CN 109584512 A CN109584512 A CN 109584512A
- Authority
- CN
- China
- Prior art keywords
- mountain region
- panorama
- region disaster
- disaster
- early warning
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 56
- 230000003068 static effect Effects 0.000 claims abstract description 25
- 230000008569 process Effects 0.000 claims abstract description 15
- 238000004445 quantitative analysis Methods 0.000 claims abstract description 14
- 230000033001 locomotion Effects 0.000 claims abstract description 13
- 230000015572 biosynthetic process Effects 0.000 claims abstract description 12
- 238000003786 synthesis reaction Methods 0.000 claims abstract description 12
- 238000010276 construction Methods 0.000 claims abstract description 11
- 238000006073 displacement reaction Methods 0.000 claims abstract description 10
- 238000001914 filtration Methods 0.000 claims description 7
- 239000000284 extract Substances 0.000 claims description 6
- 238000012544 monitoring process Methods 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 4
- 239000004615 ingredient Substances 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 241000288673 Chiroptera Species 0.000 claims description 2
- 230000006399 behavior Effects 0.000 claims description 2
- 238000004519 manufacturing process Methods 0.000 claims description 2
- 239000000203 mixture Substances 0.000 claims description 2
- 238000001308 synthesis method Methods 0.000 claims 1
- 239000011435 rock Substances 0.000 abstract description 7
- 238000004540 process dynamic Methods 0.000 abstract description 3
- 230000005167 amoeboid movement Effects 0.000 description 2
- 230000008030 elimination Effects 0.000 description 2
- 238000003379 elimination reaction Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 238000000342 Monte Carlo simulation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/10—Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4038—Image mosaicing, e.g. composing plane images from plane sub-images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
- G06T2207/20032—Median filtering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
- G06T2207/30184—Infrastructure
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Theoretical Computer Science (AREA)
- Computing Systems (AREA)
- Life Sciences & Earth Sciences (AREA)
- Environmental & Geological Engineering (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geology (AREA)
- Alarm Systems (AREA)
Abstract
The present invention provides a kind of mountain region disaster method for early warning and early warning system, include the following steps: that mountain region disaster data acquire under same viewpoint；The splicing and synthesis of static panorama figure；The generation of mountain region disaster motion process video texture；Both static panorama figure and video texture are combined and generate construction Dynamic Panorama；More phase images are superimposed, the variation of quantitative analysis mountain region disaster deformation front and back elevation and horizontal displacement.This method is by combining video texture and panorama sketch, the mountain region disasters deformation process Dynamic Panorama such as construction landslide, mud-rock flow, while more phase images being superimposed, and obtains mountain region disaster deformation data quantitative analysis achievement, realizes the early warning to mountain region disaster.
Description
Technical field
The present invention relates to Geological Hazards Monitoring early warning fields, in particular to a kind of mountain region disaster method for early warning and in advance
Alert system.
Background technique
Currently, mountain region disaster, to come down, based on mud-rock flow, in most cases landslide and mud-rock flow are all the shadows in heavy rain
Under sound, occur that sliding and flowing occur rapidly under gravity.
Mountain region disaster often has sudden and catastrophic, generation rapidly in a relatively short period of time, with biggish broken
Bad property.The generating process of mountain region disaster is of short duration, and by taking landslide as an example, entire sliding process is usually at 1 minute or so, once landslide calamity
Evil occurs, and escapes within the so of short duration time extremely difficult.Therefore, mountain region disaster give warning in advance it is particularly important.
Summary of the invention
The present invention provides a kind of mountain region disaster method for early warning, it is intended to improve mountain region disaster early warning problem.
The present invention is implemented as follows:
A kind of mountain region disaster dynamic panorama obtains and the method for early warning, includes the following steps:
Step 1: mountain region disaster data acquire under same viewpoint；
Step 2: the splicing and synthesis of static panorama figure；
Step 3: the generation of mountain region disaster motion process video texture；
Step 4: both static panorama figure and video texture being combined and generate construction Dynamic Panorama；
Step 5: more phase images being superimposed, the variation of quantitative analysis mountain region disaster deformation front and back elevation and horizontal displacement.
Preferably, the above method further includes step 6: using cloud software editing, uploading Dynamic Panorama, more phase image superpositions
Achievement realizes that internet type is shared.
Preferably, in the step 1 under same viewpoint mountain region disaster material collection method are as follows: using unmanned plane fixed point clap
It takes the photograph acquisition data and shooting mountain region disaster moves preceding more phase images.
It is furthermore preferred that utilizing the method for unmanned plane fixed point shooting, collecting data in the step 1 specifically:
A. four circle of unmanned plane fixed point shooting acquires data, first lap: holder, which is faced upward, appears in 3 equal subnettings to mountain region disaster body
Ruling bottom 8-10 photos of one line parallel transverse shooting, 30 ° every turn are clapped one；Second circle: this circle laterally shoots photo 8
, 45 ° every turn are clapped one；Third circle: since shooting is no longer horizontal, laterally bat 6, every turn of 60 ° of bats one；4th circle:
Downward pitching with regard to face ground, is spaced 60 degree and claps 2 substantially.
Preferably, static panorama figure is realized using PTGUI software in the step 2 or using hyperbola interpolation algorithm
Splicing and synthesis, the hyperbola interpolation algorithm realize the splicing and synthesis of static panorama figure method particularly includes:
(1) it obtains spherical panorama sketch: the serial-gram (totally 360 degree) of multiple certain angular intervals of unmanned plane acquisition is existed
Spherical panorama sketch is obtained using the central point of camera lens, focal length as successive projection on the corresponding spherome surface of radius；
(2) hyperbola interpolation algorithm obtains column panorama sketch: any point on photo is closed according to the geometry of formula 1, formula 2
System is coordinately transformed to obtain the coordinate for projecting to spherome surface, after obtaining the corresponding relationship of pixel, to each pixel of photo
Gray value carries out interpolation, obtains the gray value of each pixel of cylinder,
(3) day and image procossing are mended: carrying out mending day and image processing operations using subsequent pictures software for editing, obtain more
True static panorama figure.
Preferably, above-mentioned subsequent pictures software for editing is Adobe or Photoshop.
The basic principle of above-mentioned acquisition column panorama sketch be according to camera imaging principle, camera lens center to egative film away from
From being approximately equal to lens focus, and the central point of lens is exactly imaginary panorama observation point, is half with focal length centered on being put by this
The corresponding spherome surface of diameter is exactly panoramic projection face, by the serial-gram of multiple certain angular intervals, unmanned plane shooting totally 360
Degree, the image that successive projection goes out on this perspective plane is exactly spherical panorama sketch.
Preferably, in the step 3 mountain region disaster motion process video texture generation method specifically:
(1) video production: the image for the mountain region disaster motion process that step 1 is shot is made using video production software
At video clip；
(2) background modeling: defining background is ingredient static in video sequence, extracts background using time shaft filtering method
Figure, each frame of video sequence image subtract background image and obtain error image only comprising moving object；
(3) video texture synthesizes: the distance between any two frame in calculating difference image sequence is stored in two-dimensional array
In, synthesis obtains video texture.There are two types of broadcast modes for video texture: shuffle and loop play, the former is general according to transfer
Rate determines which frame plays after the current frame with Monte Carlo Method, and the latter selects some frame sequence shapes with harmonic(-)mean cost
At circulation.
Preferably, the filtering algorithm is median filtering or gaussian filtering, using this filtering to image procossing, elimination noise
Influence, smooth error image, sequence image be represented as only include moving object error image.
The image of the mountain region disasters motion process such as above-mentioned landslide, mud-rock flow is difficult to be recorded to, therefore can be by acquiring mountainous region calamity
Evil amoeboid movement process and deformation front and back image, obtain its motion process image using post-processing software.Background is defined as
Static ingredient in video sequence, extracting background image can detecte the moving object in video sequence, and then enhance video line
Manage the stability of synthesis.Classical background modeling method include median filter method, mean value on time shaft add Variance Method with
And mixed Gauss model method etc..Since the sampling time of video texture is shorter, change without apparent optical illumination condition, it is excellent
Choosing extracts background image using simplest time shaft median filter method.Each frame of sequence image subtracts background image and obtains
Error image, the pixel only covered by moving object have the value for being significantly greater than 0, select suitable threshold value, will be less than threshold value
Pixel be set to 0.Using the smooth error image of simple filtering algorithm, by above-mentioned processing, sequence image is represented as only wrapping
Error image containing moving object.In video texture synthesis below, the similarity of interframe is calculated using these error images,
Guarantee to find next frame from original video after playing present frame, not cause visual discontinuous.
Preferably, video texture is compressed using the method for entropic spueezing in step 4.
Each frame of above-mentioned video texture and the difference of background image are very small, in the difference of video texture and background image
There was only the pixel of moving object in image has biggish value, and the redundancy of image is further reduced with suitable threshold filter
The region of moving object can also be extracted.
Preferably, both static panorama figure and video texture are combined in the step 4 and generates construction Dynamic Panorama
Method specifically include: by the static panorama figure and video texture that are shot under the same viewpoint alignment, using color blend algorithm
Color is inconsistent between elimination video texture and panorama sketch, and the two is synthesized Dynamic Panorama.
User changes the focal length of video camera when shooting video texture when above-mentioned construction Dynamic Panorama, in such case
Under, the variation of graphical rule is extracted using a kind of technique of alignment based on FFT.Then video texture is projected according to alignment parameter
Onto panorama sketch.
Preferably, more phase images are superimposed in the step 5, quantitative analysis mountain region disaster deformation front and back elevation and horizontal position
The method of the variation of shifting specifically includes: deformation front and back image being imported Arcgis, extracts longitude, latitude, the coordinate of elevation will become
Image subtracts each other before and after shape, obtains the horizontal and vertical change in displacement of disaster body, and the deformation behaviour of quantitative analysis disaster body is disaster body
Monitoring and warning provides quantitative data.
It is obtained the present invention also provides a kind of mountain region disaster dynamic panorama and pre-warning system, including memory and processor,
Wherein:
The memory is for storing program instruction；
The processor is for running described program instruction, to execute following steps:
Mountain region disaster data acquire under same viewpoint；
The splicing and synthesis of static panorama figure；
The generation of mountain region disaster stream motion process video texture；
Both static panorama figure and video texture are combined and generate construction Dynamic Panorama；
More phase images are superimposed, the variation of quantitative analysis mountain region disaster deformation front and back elevation and horizontal displacement.
Preferably, above-mentioned processor is also used to run described program instruction: using cloud software editing, uploading dynamic panorama
Figure, more phase images are superimposed achievement, realize that internet type is shared.
Compared with the prior art, the invention has the following advantages:
By the way that video texture and panorama sketch are combined, the mountain region disasters deformation process dynamic such as construction landslide, mud-rock flow
Panorama sketch, while more phase images being superimposed, mountain region disaster deformation data quantitative analysis achievement is obtained, before deforming according to mountain region disaster
The variation of elevation and horizontal displacement afterwards realizes the early warning to mountain region disaster.
Detailed description of the invention
It, below will be to use required in embodiment in order to illustrate more clearly of the technical solution of embodiment of the present invention
Attached drawing be briefly described, it should be understood that the following drawings illustrates only certain embodiments of the present invention, therefore is not to be seen as
It is the restriction to range, it for those of ordinary skill in the art, without creative efforts, can be with root
Other relevant attached drawings are obtained according to these attached drawings.
Fig. 1 is that unmanned plane pinpoints figure part selection figure of taking photo by plane in the embodiment of the present invention；
Fig. 2 is spherical static panorama figure in the embodiment of the present invention；
Fig. 3 is that video texture extracts result and with lines indicates result figure in the embodiment of the present invention；
Fig. 4 is video texture result result figure in conjunction with the static panorama figure in December in the embodiment of the present invention；
Fig. 5 is Chinese and Western of embodiment of the present invention mountain village deformation data result figure.
Specific embodiment
To keep the purposes, technical schemes and advantages of embodiment of the present invention clearer, implement below in conjunction with the present invention
The technical solution in embodiment of the present invention is clearly and completely described in attached drawing in mode, it is clear that described reality
The mode of applying is some embodiments of the invention, rather than whole embodiments.Based on the embodiment in the present invention, ability
Domain those of ordinary skill every other embodiment obtained without creative efforts, belongs to the present invention
The range of protection.
It is noted that described further below be all exemplary, it is intended to provide further instruction to the application.Unless another
It indicates, all technical and scientific terms used herein has usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
Present invention will be further explained below with reference to the attached drawings and examples, in order to the reason of those of ordinary skill in the art
Solution:
Embodiment 1
To the west of for the landslide of mountain village, according to geological researching data, come down to Western Hills village and implement monitoring and warning.A kind of mountainous region calamity
Evil method for early warning, including the following steps:
(1) 720 ° of panorama sketch of taking photo by plane are pinpointed using unmanned plane, carries out live shadow in Septembers, 2017 and in December, 2017 respectively
As acquisition.Establish corresponding document folder, such as Fig. 1, wherein (a) be September part take photo by plane figure selection, (b) for October take photo by plane figure selection.
(2) according to camera imaging principle, by unmanned plane respectively in September and multiple serial-grams of acquisition in December on perspective plane
Upper successive projection goes out spherical static panorama figure, while carrying out mending day and image procossing.As shown in Fig. 2, wherein picture is long: wide=2:
1。
(3) landslide video texture is extracted makes with dynamic panoramic scene: two Zhang Quanjing's figures that step (2) make are fabricated to
Video sequence image is represented as error image only comprising moving object by corresponding video.In video texture synthesis below
When, the similarity of interframe is calculated using these error images.It is visual discontinuous according to caused by two frames, it extracts sliding in video
Slope motion texture.For convenience of expression, the texture of extraction is indicated with lines, as shown in figure 3, wherein solid line indicates the September
Come down texture curve；Dotted line indicates December landslide texture curve.
(4) video texture and the static panorama figure in December extracted step (3) combines, as shown in Figure 4.
(5) two phase images are overlapped deformation characteristic in advance: the coordinate elevation of two phase images in advance, before quantitative analysis deformation
The variation of elevation and horizontal displacement afterwards provides quantitative data for mountain region disaster monitoring, provides disaster timely predictive information, such as scheme
Shown in 5, subtract each other elevation in December and September part elevation to obtain its elevation deformation data.
(6) Dynamic Panorama is edited using 720 cloud softwares, adds the deformation data of two phase images as hot spot,
Internet is shared with local resident, allow they understand in time Western Hills village landslide dynamic, and select reasonable escape time, route and
It saves oneself means.
The present invention at least has the advantages that
By the way that video texture and panorama sketch are combined, the mountain region disasters motion process dynamic such as construction landslide, mud-rock flow
Panorama sketch, while mountain region disaster deformation data quantitative analysis achievement is added, it realizes the acquisition of mountain region disaster dynamic panorama, simultaneously will
More phase image superpositions, obtain mountain region disaster deformation data quantitative analysis achievement, realize the early warning to mountain region disaster.Pass through interconnection
Net is by information sharing, predominately by the motion process and deformation monitoring of the mountain region disasters actual examples such as mountainous region landslide, mud-rock flow
Quantitative data takes in face of people, and local resident is allowed more really to recognize the amoeboid movement situation of disaster, so that selection is reasonable
Escape time, route and means of saving oneself.
The above is only the preferred embodiment of the present invention, are not intended to restrict the invention, for the technology of this field
For personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, made any to repair
Change, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of mountain region disaster method for early warning, which comprises the steps of:
Step 1: mountain region disaster data acquire under same viewpoint；
Step 2: the splicing and synthesis of static panorama figure；
Step 3: the generation of mountain region disaster motion process video texture；
Step 4: both static panorama figure and video texture being combined and generate construction Dynamic Panorama；
Step 5: more phase images being superimposed, the variation of quantitative analysis mountain region disaster deformation front and back elevation and horizontal displacement.
2. a kind of mountain region disaster method for early warning as described in claim 1, which is characterized in that the above method further includes step 6: benefit
With cloud software editing, Dynamic Panorama is uploaded, more phase images are superimposed achievement, realize that internet type is shared.
3. a kind of mountain region disaster method for early warning as described in claim 1, which is characterized in that in the step 1 under same viewpoint
The method of mountain region disaster data acquisition are as follows: more phase images before being moved using unmanned plane fixed point shooting, collecting data and mountain region disaster.
4. a kind of mountain region disaster method for early warning as claimed in claim 3, which is characterized in that utilize unmanned plane in the step 1
The method for pinpointing shooting, collecting data specifically:
A. four circle acquisition data of unmanned plane fixed point shooting, first lap: holder, which is faced upward, to be appeared in 3 etc. to mountain region disaster body and divides grid lines
Bottom 8-10 photos of one line parallel transverse shooting, 30 ° every turn are clapped one；Second circle: this circle laterally open by shooting photo 8,
45 ° every turn are clapped one；Third circle: since shooting is no longer horizontal, laterally bat 6, every turn of 60 ° of bats one；4th circle: downward
Pitching with regard to face ground, is spaced 60 degree and claps 2 substantially.
5. a kind of mountain region disaster method for early warning as described in claim 1, which is characterized in that soft using PTGUI in the step 2
Part or the splicing and synthesis that static panorama figure is realized using hyperbola interpolation algorithm, the hyperbola interpolation algorithm is realized quiet
The splicing of state panorama sketch and synthesis method particularly includes:
(1) spherical panorama sketch is obtained: by the serial-gram (totally 360 degree) of multiple certain angular intervals of unmanned plane acquisition with phase
Central point, the focal length of machine lens are that successive projection obtains spherical panorama sketch on the corresponding spherome surface of radius；
(2) hyperbola interpolation algorithm obtain column panorama sketch: by any point on photo according to formula 1, the geometrical relationship of formula 2 into
Row coordinate transform obtains projecting to the coordinate of spherome surface, after obtaining the corresponding relationship of pixel, to each pixel grey scale of photo
Value carries out interpolation, obtains the gray value of each pixel of cylinder；
(3) day and image procossing are mended: carrying out mending day and image processing operations using subsequent pictures software for editing, is obtained more true
Static panorama figure.
6. a kind of mountain region disaster method for early warning as described in claim 1, which is characterized in that mountain region disaster becomes in the step 3
The generation method of shape process video texture specifically:
(1) video production: the image for the mountain region disaster motion process that step 1 is shot is fabricated to view using video production software
Frequency segment；
(2) background modeling: defining background is ingredient static in video sequence, extracts Background using time shaft filtering method,
Each frame of video sequence image subtracts background image and obtains error image only comprising moving object；
(3) video texture synthesizes: the distance between any two frame in calculating difference image sequence is stored in two-dimensional array, is closed
At obtaining video texture.
7. a kind of mountain region disaster method for early warning as claimed in claim 6, which is characterized in that use the side of entropic spueezing in step 4
Method compresses video texture.
8. a kind of mountain region disaster method for early warning as described in claim 1, which is characterized in that will be static complete in the step 4
Both scape figure and video texture combine the method for generating construction Dynamic Panorama to specifically include: quiet by what is shot under the same viewpoint
The inconsistent of color between video texture and panorama sketch is eliminated in state panorama sketch and video texture alignment using color blend algorithm,
The two is synthesized into Dynamic Panorama.
9. a kind of mountain region disaster method for early warning as described in claim 1, which is characterized in that by more phase images in the step 5
The method of the variation of superposition, quantitative analysis mountain region disaster deformation front and back elevation and horizontal displacement, specifically includes: by deformation front and back shadow
As importing Arcgis, longitude, latitude are extracted, deformation front and back image is subtracted each other, it is horizontal and vertical to obtain disaster body by the coordinate of elevation
Change in displacement, the deformation behaviour of quantitative analysis disaster body provide quantitative data for disaster body monitoring and warning.
10. a kind of mountain region disaster early warning system, which is characterized in that including memory and processor, in which:
The memory is for storing program instruction；
The processor is for running described program instruction, to execute following steps:
Mountain region disaster data acquire under same viewpoint；
The splicing and synthesis of static panorama figure；
The generation of mountain region disaster motion process video texture；
Both static panorama figure and video texture are combined and generate construction Dynamic Panorama；
More phase images are superimposed, the variation of quantitative analysis mountain region disaster deformation front and back elevation and horizontal displacement.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811550115.2A CN109584512A (en) | 2018-12-18 | 2018-12-18 | A kind of mountain region disaster method for early warning and early warning system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811550115.2A CN109584512A (en) | 2018-12-18 | 2018-12-18 | A kind of mountain region disaster method for early warning and early warning system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109584512A true CN109584512A (en) | 2019-04-05 |
Family
ID=65930806
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811550115.2A Pending CN109584512A (en) | 2018-12-18 | 2018-12-18 | A kind of mountain region disaster method for early warning and early warning system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109584512A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111006593A (en) * | 2019-12-13 | 2020-04-14 | 武汉纵横天地空间信息技术有限公司 | Method and system for monitoring mountain landform and predicting landslide by using unmanned aerial vehicle |
| CN113538524A (en) * | 2021-06-18 | 2021-10-22 | 云南电网有限责任公司 | 5G-fused intelligent early warning method and system for debris flow of power transmission line |
| CN114676907A (en) * | 2022-01-17 | 2022-06-28 | 中国地质大学（北京） | Regional geological disaster early warning method and device, storage medium and equipment |
| CN117058628A (en) * | 2023-10-13 | 2023-11-14 | 东华理工大学南昌校区 | Landslide hazard monitoring method, system and storage medium based on image recognition |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105444740A (en) * | 2016-01-01 | 2016-03-30 | 三峡大学 | Landslide emergency treatment engineering exploration design method based on remote sensing assistance of small unmanned aerial vehicle |
| CN105783878A (en) * | 2016-03-11 | 2016-07-20 | 三峡大学 | Small unmanned aerial vehicle remote sensing-based slope deformation detection and calculation method |
| CN105865427A (en) * | 2016-05-18 | 2016-08-17 | 三峡大学 | Individual geological disaster emergency investigation method based on remote sensing of small unmanned aerial vehicle |
| CN106791634A (en) * | 2016-12-14 | 2017-05-31 | 天津文康科技有限公司 | A kind of unmanned plane based on optical, mechanical and electronic integration pans the method and device of figure |
| CN108416985A (en) * | 2018-04-20 | 2018-08-17 | 北京航天控制仪器研究所 | A kind of Geological Hazards Monitoring early warning system and method for early warning based on image recognition |
-
2018
- 2018-12-18 CN CN201811550115.2A patent/CN109584512A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105444740A (en) * | 2016-01-01 | 2016-03-30 | 三峡大学 | Landslide emergency treatment engineering exploration design method based on remote sensing assistance of small unmanned aerial vehicle |
| CN105783878A (en) * | 2016-03-11 | 2016-07-20 | 三峡大学 | Small unmanned aerial vehicle remote sensing-based slope deformation detection and calculation method |
| CN105865427A (en) * | 2016-05-18 | 2016-08-17 | 三峡大学 | Individual geological disaster emergency investigation method based on remote sensing of small unmanned aerial vehicle |
| CN106791634A (en) * | 2016-12-14 | 2017-05-31 | 天津文康科技有限公司 | A kind of unmanned plane based on optical, mechanical and electronic integration pans the method and device of figure |
| CN108416985A (en) * | 2018-04-20 | 2018-08-17 | 北京航天控制仪器研究所 | A kind of Geological Hazards Monitoring early warning system and method for early warning based on image recognition |
Non-Patent Citations (2)
| Title |
|---|
| 杜威: "一种用于动态场景的全景表示方法", 《计算机学报》 * |
| 高轶: "全景照片合成技术及PTGUI的运用", 《电脑知识与技术》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111006593A (en) * | 2019-12-13 | 2020-04-14 | 武汉纵横天地空间信息技术有限公司 | Method and system for monitoring mountain landform and predicting landslide by using unmanned aerial vehicle |
| CN113538524A (en) * | 2021-06-18 | 2021-10-22 | 云南电网有限责任公司 | 5G-fused intelligent early warning method and system for debris flow of power transmission line |
| CN114676907A (en) * | 2022-01-17 | 2022-06-28 | 中国地质大学（北京） | Regional geological disaster early warning method and device, storage medium and equipment |
| CN114676907B (en) * | 2022-01-17 | 2022-09-20 | 中国地质大学（北京） | Regional geological disaster early warning method and device, storage medium and equipment |
| CN117058628A (en) * | 2023-10-13 | 2023-11-14 | 东华理工大学南昌校区 | Landslide hazard monitoring method, system and storage medium based on image recognition |
| CN117058628B (en) * | 2023-10-13 | 2024-01-26 | 东华理工大学南昌校区 | Landslide hazard monitoring method, system and storage medium based on image recognition |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11037365B2 (en) | Method, apparatus, medium, terminal, and device for processing multi-angle free-perspective data | |
| CN109584512A (en) | A kind of mountain region disaster method for early warning and early warning system | |
| CN103168315B (en) | Solid (3D) panorama sketch on portable equipment creates | |
| CN109615703B (en) | Augmented reality image display method, device and equipment | |
| CN104699842B (en) | Picture display method and device | |
| CN105939481A (en) | Interactive three-dimensional virtual reality video program recorded broadcast and live broadcast method | |
| JP5725953B2 (en) | Imaging apparatus, control method therefor, and information processing apparatus | |
| US10586378B2 (en) | Stabilizing image sequences based on camera rotation and focal length parameters | |
| Yen et al. | Maintaining temporal coherence in video retargeting using mosaic-guided scaling | |
| JP6610535B2 (en) | Image processing apparatus and image processing method | |
| US11622072B2 (en) | Systems and methods for suggesting video framing | |
| US11818467B2 (en) | Systems and methods for framing videos | |
| TW201701051A (en) | Panoramic stereoscopic image synthesis method, apparatus and mobile terminal | |
| Schenkel et al. | Natural scenes datasets for exploration in 6DOF navigation | |
| TW201824178A (en) | Image processing method for immediately producing panoramic images | |
| CN109756675A (en) | A kind of mountain region disaster dynamic panorama analogy method and system | |
| JP6544970B2 (en) | IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND PROGRAM | |
| Zhang et al. | Coherent video generation for multiple hand-held cameras with dynamic foreground | |
| Yu et al. | Human pose estimation in monocular omnidirectional top-view images | |
| Calagari et al. | Sports VR content generation from regular camera feeds | |
| Heindl et al. | Capturing photorealistic and printable 3d models using low-cost hardware | |
| KR102571876B1 (en) | Method and device for refocusing at least one plenoptic video | |
| US20230222635A1 (en) | Cloud based intelligent image enhancement system | |
| Yacoub | Quality evaluation for stitched panoramic videos | |
| Ito | Video Stabilisation Based on Spatial Transformer Networks |
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 | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190405 |
|
| WD01 | Invention patent application deemed withdrawn after publication |