CN101866482A - Panorama splicing method based on camera self-calibration technology, and device thereof - Google Patents
Panorama splicing method based on camera self-calibration technology, and device thereof Download PDFInfo
- Publication number
- CN101866482A CN101866482A CN 201010212136 CN201010212136A CN101866482A CN 101866482 A CN101866482 A CN 101866482A CN 201010212136 CN201010212136 CN 201010212136 CN 201010212136 A CN201010212136 A CN 201010212136A CN 101866482 A CN101866482 A CN 101866482A
- Authority
- CN
- China
- Prior art keywords
- picture pick
- calibration
- image
- parameter
- plane
- 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.)
- Granted
Links
Images
Landscapes
- Studio Devices (AREA)
- Stereoscopic And Panoramic Photography (AREA)
- Image Processing (AREA)
Abstract
The invention provides a panorama splicing method based on camera self-calibration technology, comprising the following steps of: using a plurality of cameras for collecting the panorama image of the scene; calibrating internal parameters and external parameters of the cameras by self-calibration algorithm according to the collected image; according to the calibrated internal parameters and external parameters of the cameras, selecting a best calibration plane, and correcting the image to the best calibration plane; and splicing all the images on the best calibration plane into a whole image, and fusing the overlapping regions of the whole image. The invention adopts the self-calibration technology based on absolute pairing quadric surface to automatically recover the internal parameters and the external parameters of the cameras, so that a hand-hold camera can be used by non-professional staff without a professional device.
Description
Technical field
The present invention relates to technical field of image processing, particularly a kind of Panoramagram montage method and device based on the picture pick-up device self-calibration technology.
Background technology
The panorama sketch technology is a kind of form of expression of virtual reality.The panorama sketch of general meaning is meant the wide-angle image performance of real world, can be drawing, photography, and the video or the three-dimensional model of scene, the panorama sketch of mentioning among the present invention are meant based on the panoramic picture of photography or video to be represented.Splicing technology of panorama drawing is a kind of virtual reality technology based on image rendering technology generation photo realism graphic, and splicing technology of panorama drawing mainly is by the splicing to image, realizes looking around scene.
Existing Panoramagram montage algorithm need be known the position relation of image sequence mostly.Thus image is proofreaied and correct and mated.This in practice position relation is difficult to determine, in general takes high-quality panorama sketch if desired, then needs professional and expensive equipment, looks about shooting etc. such as camera is done on the fixed triangle frame.And the Panoramagram montage algorithm that does not need picture position relation poor effect often can not generate high-quality panorama sketch.This makes the application of panorama sketch and popularization be very limited.
Summary of the invention
Purpose of the present invention is intended to solve above-mentioned technological deficiency at least, has proposed a kind of Panoramagram montage method and device based on the picture pick-up device self-calibration technology.
For achieving the above object, one aspect of the present invention has proposed a kind of Panoramagram montage method based on the picture pick-up device self-calibration technology, may further comprise the steps: adopt a plurality of picture pick-up devices that the panoramic picture of scene is gathered; According to the image of gathering adopt from calibration algorithm demarcate described picture pick-up device intrinsic parameter and outside parameter; According to the intrinsic parameter and the outer selection of parameter best alignment plane of the described picture pick-up device of demarcating, and all images calibrated to described best alignment plane; With on described best alignment plane, all images is spliced into an entire image, and the overlapping region of described entire image is merged.
The present invention has also proposed a kind of Panoramagram montage device based on the picture pick-up device self-calibration technology on the other hand, comprise: demarcating module, be used for panoramic picture to the scene of a plurality of picture pick-up device collections adopt from calibration algorithm demarcate described picture pick-up device intrinsic parameter and outside parameter; Calibration module is used for intrinsic parameter and outer selection of parameter best alignment plane according to the described picture pick-up device of described demarcating module demarcation, and all images is calibrated to described best alignment plane; And concatenation module, be used on described best alignment plane, all images being spliced into an entire image, and the overlapping region of described entire image is merged.
The present invention adopts and to recover the inside and outside parameter of picture pick-up device automatically based on the quadric self-calibration technology of absolute antithesis, can use hand-held apparatus for making a video recording and does not need professional and equipment.And the present invention also uses the ransac algorithm to estimate optimum calibration plane automatically, guarantee that the panorama sketch that finally obtains has optimum visual angle, and panorama sketch meets projection relation.In addition, the present invention carries out corresponding point matching to the image after calibrating, and realizes image mosaic according to the gained matching relationship.Secondly, the present invention uses nature transition fusion method that the overlapping region is merged, thereby can realize the natural transition of whole panorama sketch.
Aspect that the present invention adds and advantage part in the following description provide, and part will become obviously from the following description, or recognize by practice of the present invention.
Description of drawings
Above-mentioned and/or additional aspect of the present invention and advantage are from obviously and easily understanding becoming the description of embodiment below in conjunction with accompanying drawing, wherein:
Fig. 1 is the Panoramagram montage method process flow diagram based on the picture pick-up device self-calibration technology of the embodiment of the invention;
Fig. 2 is that the position of the multiple image calibration plane of the embodiment of the invention concerns synoptic diagram;
Fig. 3 carries out the Calibration Method synoptic diagram for the embodiment of the invention to single image; With
Fig. 4 is the Panoramagram montage structure drawing of device based on the picture pick-up device self-calibration technology of the embodiment of the invention.
Embodiment
Describe embodiments of the invention below in detail, the example of described embodiment is shown in the drawings, and wherein identical from start to finish or similar label is represented identical or similar elements or the element with identical or similar functions.Below by the embodiment that is described with reference to the drawings is exemplary, only is used to explain the present invention, and can not be interpreted as limitation of the present invention.
The present invention is applied to Panoramagram montage with self-calibration technology, can allow the user to use hand-held picture pick-up device that scene is carried out freely taking, and the inside and outside parameter that calculates each width of cloth image by aftertreatment realizes the splicing and the fusion of panorama sketch then afterwards.Wherein, the picture pick-up device calibration technique is important branch in the computer vision field, the inside and outside parameter that is used to recover and demarcate camera.The tradition calibration technique need be used calibrated reference, thereby in use is subject to many limitations.And the picture pick-up device self-calibration technology can realize that by the utmost point is retrained between the image the no calibrated reference of image sequence is demarcated certainly.
As shown in Figure 1, the Panoramagram montage method process flow diagram based on the picture pick-up device self-calibration technology for the embodiment of the invention may further comprise the steps:
Step S101 adopts a plurality of picture pick-up devices that the panoramic picture of scene is gathered.Wherein, in an embodiment of the present invention, need guarantee during collection has bigger overlapping region between each width of cloth image, and the view directions of each width of cloth image is substantially parallel.In embodiments of the present invention, can use hand-held or other picture pick-up devices are taken scene, the locality of gathering shooting is not strict with.
Step S102 carries out pre-service to the image of gathering.Specifically comprise:
21) use Gaussian filter that image is carried out denoising.Filter equation is:
22) use histogram equalizing method to recover to lose by the overexposure or the image detail that causes of owing to expose to the sun that illumination causes.
Step S103, according to the image of gathering adopt from calibration algorithm demarcate described picture pick-up device intrinsic parameter and outside parameter.Specifically may further comprise the steps:
31) use the SIFT algorithm that all images is carried out feature point detection, obtain 128 dimension descriptors of unique point, the unique point in per two width of cloth views is mated.Concrete matching process is: in two images between descriptor two the shortest unique points of Euclidean distance think match point.According to the constraint one to one of coupling, matching result is screened the matching relationship of deletion error.Certainly those skilled in the art should recognize and also can adopt other algorithms to carry out feature point detection, and these all should be included within protection scope of the present invention.
32), adopt the ransac algorithm that the fundamental matrix between two picture pick-up devices is carried out Robust Estimation, and be classified as the matching characteristic point deletion of exterior point in will calculating according to above-mentioned Feature Points Matching result.If matching characteristic point do not satisfy that the fundamental matrix calculate describes to utmost point geometrical constraint, then be considered to error matching points.
33) the robust features point matching relationship that obtained according to the last step carries out projective reconstruction.At first determine two width of cloth initialization views, set up world coordinate system, rebuild according to the triangle projection relation and obtain the corresponding three dimensional space coordinate of matching characteristic point.Circulation adds new images, and all joins in the projective reconstruction until all images.
34) adopt linear calibration's algorithm directly to calibrate the transformation matrix that projective space is rebuild to tolerance.Directly do not calculate absolute antithesis quadric surface in an embodiment of the present invention, but earlier with absolute antithesis quadric surface Ω
*Be decomposed into SS
T, wherein S is 4 * 3 companion matrix, can will be converted into linear restriction to S to the linear restriction of confidential reference items matrix K according to K=PS like this, can prove SS in theory
TThe Ω that obtains
*Have orthotropicity, and its order is 3.
35) S is mended rows of vectors, the 4 rank square formations that obtain are reversible, and this square formation contrary is exactly this projection to be rebuild a transformation matrix that tolerance is rebuild of conversion.
36) tolerance that conversion is obtained is rebuild the picture pick-up device projection matrix under the meaning, carries out RQ and decomposes, and obtains the intrinsic parameter and the outer parameter of picture pick-up device respectively, and finishes picture pick-up device from the demarcation task.In one embodiment of the invention, the intrinsic parameter of picture pick-up device and outer parameter can comprise the confidential reference items matrix K, rotation matrix R and translation vector t.
Step S104 according to the intrinsic parameter and the outer selection of parameter best alignment plane of the described picture pick-up device of demarcating, and calibrates to described best alignment plane with all images.Specifically may further comprise the steps:
41) the normal direction Z of the optimum calibration plane of use ransac algorithm computation
*Ransac algorithm here and general ransac algorithm are slightly different, sampling each time only needs piece image, normal direction with this plane is as the criterion, calculate normal and this normal angle in all images less than the number of the image of certain threshold value as counting in this time sampling.Because each sampling piece image that only needs, once all possible employing is combined as N kind (N bitmap sheet number), once can get all over all sampling combinations, and not have too big calculation cost.As shown in Figure 2, the position for the multiple image calibration plane of the embodiment of the invention concerns synoptic diagram.
42) according to the picture pick-up device rotation matrix R that tries to achieve before
i, and upward go on foot the optimum calibration plane normal direction of trying to achieve, calculate each picture pick-up device optical axis direction Z
iTo optimum calibration plane normal direction Z
*Rotation matrix R '
iThe concrete practice is: with optimum calibration plane normal direction Z
*Be converted to rotation matrix and represent R
*, according to formula: R '
i=R
*-1R
i, can calculate the calibration rotation matrix R ' of every width of cloth image
i
43) determine every width of cloth image calibration homograph H
iThe concrete practice is: by above-mentioned calibration rotation matrix R '
iCalculate the coordinate in calibration plane of four angle points in the original image, Fig. 3 has shown the relation between the plane of delineation and the calibration plane.By the corresponding relation of 4 points, can calculate every width of cloth image calibration homograph H
iAs shown in Figure 3, for the embodiment of the invention single image is carried out the Calibration Method synoptic diagram.
44) every width of cloth image is calibrated, the concrete practice is: to each pixel in the i clothes image, its coordinate transform is: X '
i=H
iX
i
Step S105 is spliced into all images one entire image on the best alignment plane, and the overlapping region of described entire image is merged.Specifically may further comprise the steps:
51) estimation of overmatching point coordinate obtains the correspondent transform between each width of cloth view, realizes the splicing of each width of cloth image.Because through the rectification of front, each width of cloth image here can by simple translation rotation and the first time convergent-divergent obtain.So homograph here
Be actually the similarity transformation matrix in the 2 dimension projective spaces, can be expressed as:
Here s represents scale factor, and R is rotation matrix (1 degree of freedom of plane rotation), and u is the translation translation vector.So have 3 parameters, we only need to have 3 pairs of corresponding matching relationships at least in two width of cloth images, just can pass through equation: x=Hx ' and find the solution the homograph that obtains between two width of cloth image corresponding point.Afterwards all images is estimated homograph successively and correct, finish the splicing of all images.
52) through after the image mosaic of last step, two view overlapping regions are handled, obtain the expression of this zone in composograph.Adopt the linear natural transition fusion method that overlaps the zone.This method is to the image R of overlapping region, G, and the B value calculating method is:
Wherein S is the index set of all images, I
xBe the pixel value of composograph, wherein x can get r, g, and b,
It is the pixel value of i width of cloth image.α
iBe the weight of each width of cloth image pixel value in final composograph, satisfy constraint
Its value can be tried to achieve by method once: i width of cloth image is in all pixels of this overlapping region and be ε
i, α then
iFind the solution by following formula and to obtain:
Through above-mentioned step all overlapping regions are merged, obtain complete panoramic view.
As shown in Figure 4, be the Panoramagram montage structure drawing of device based on the picture pick-up device self-calibration technology of the embodiment of the invention.Panoramagram montage device 100 comprises demarcating module 110, calibration module 120 and concatenation module 130.Demarcating module 110 be used for to the panoramic picture of the scene of a plurality of picture pick-up device collections adopt from calibration algorithm demarcate described picture pick-up device intrinsic parameter and outside parameter.Calibration module 120 is used for intrinsic parameter and the outer selection of parameter best alignment plane according to the described picture pick-up device of described demarcating module demarcation, and all images is calibrated to described best alignment plane.Concatenation module 130 is used on described best alignment plane all images being spliced into an entire image, and the overlapping region of described entire image is merged.
In one embodiment of the invention, Panoramagram montage device 100 also comprises pretreatment module 140, be used to use Gaussian filter that image is carried out denoising and use histogram equalizing method to recover to lose by the overexposure or the image detail that causes of owing to expose to the sun that illumination causes.
In one embodiment of the invention, big overlapping region is arranged between the image that described a plurality of picture pick-up devices are taken, and substantially parallel in the view directions of a plurality of picture pick-up devices described in the gatherer process.
In one embodiment of the invention, demarcating module 110 comprises matched sub-block 111, projective reconstruction submodule 112 and parameter acquiring submodule 113.Matched sub-block 111 is used for the unique point of detected image, and the unique point in per two width of cloth images mated, and adopt the ransac algorithm that the fundamental matrix between two picture pick-up devices is carried out Robust Estimation according to described Feature Points Matching result, to obtain robust features point matching relationship.Projective reconstruction submodule 112 is used for carrying out projective reconstruction according to described robust features point matching relationship, and adopts linear calibration's algorithm directly to calibrate the transformation matrix that projective space is rebuild to tolerance.Parameter acquiring submodule 113 is used for obtaining according to described transformation matrix the intrinsic parameter and the outer parameter of described picture pick-up device.Wherein, the intrinsic parameter of picture pick-up device and outer parameter comprise: confidential reference items matrix K, rotation matrix R and translation vector t.
In one embodiment of the invention, calibration module 120 comprises that normal direction calculating sub module 121, rotation matrix calculating sub module 122, calibration homograph determine submodule 123 and calibration submodule 124.Normal direction calculating sub module 121 is used to use the normal direction of the optimum calibration plane of ransac algorithm computation.Rotation matrix calculating sub module 122 is used for calculating the rotation matrix of each picture pick-up device optical axis direction to described optimum calibration plane normal direction according to the normal direction of the intrinsic parameter of described picture pick-up device and outer parameter and described optimum calibration plane.The calibration homograph determines that submodule 123 is used for determining according to described rotation matrix the calibration homograph of every width of cloth image.Calibration submodule 124 is used for according to described calibration homograph every width of cloth image being calibrated.
The present invention adopts and to recover the inside and outside parameter of picture pick-up device automatically based on the quadric self-calibration technology of absolute antithesis, can use hand-held apparatus for making a video recording and does not need professional and equipment.And the present invention also uses the ransac algorithm to estimate optimum calibration plane automatically, guarantee that the panorama sketch that finally obtains has optimum visual angle, and panorama sketch meets projection relation.In addition, the present invention carries out corresponding point matching to the image after calibrating, and realizes image mosaic according to the gained matching relationship.Secondly, the present invention uses nature transition fusion method that the overlapping region is merged, thereby can realize the natural transition of whole panorama sketch.
Although illustrated and described embodiments of the invention, for the ordinary skill in the art, be appreciated that without departing from the principles and spirit of the present invention and can carry out multiple variation, modification, replacement and modification that scope of the present invention is by claims and be equal to and limit to these embodiment.
Claims (13)
1. the Panoramagram montage method based on the picture pick-up device self-calibration technology is characterized in that, may further comprise the steps:
Adopt a plurality of picture pick-up devices that the panoramic picture of scene is gathered;
According to the image of gathering adopt from calibration algorithm demarcate described picture pick-up device intrinsic parameter and outside parameter;
According to the intrinsic parameter and the outer selection of parameter best alignment plane of the described picture pick-up device of demarcating, and all images calibrated to described best alignment plane; With
On described best alignment plane, all images is spliced into an entire image, and the overlapping region of described entire image is merged.
2. the Panoramagram montage method based on the picture pick-up device self-calibration technology as claimed in claim 1 is characterized in that, after the panoramic picture of gathering scene, also comprises:
The image of gathering is carried out pre-service.
3. the Panoramagram montage method based on the picture pick-up device self-calibration technology as claimed in claim 2 is characterized in that, described pre-service comprises:
Use Gaussian filter that image is carried out denoising; With
Use histogram equalizing method to recover to lose by the overexposure or the image detail that causes of owing to expose to the sun that illumination causes.
4. as claim 2 or 3 described Panoramagram montage methods, it is characterized in that based on the picture pick-up device self-calibration technology, described according to the image of gathering adopt from calibration algorithm demarcate described picture pick-up device intrinsic parameter and outside parameter further comprise:
The unique point of detected image, and the unique point in per two width of cloth images mated;
Adopt the ransac algorithm that the fundamental matrix between two picture pick-up devices is carried out Robust Estimation according to described Feature Points Matching result, to obtain robust features point matching relationship;
Carry out projective reconstruction according to described robust features point matching relationship, and adopt linear calibration's algorithm directly to calibrate the transformation matrix that projective space is rebuild to tolerance; With
Obtain the intrinsic parameter and the outer parameter of described picture pick-up device according to described transformation matrix.
5. the Panoramagram montage method based on the picture pick-up device self-calibration technology as claimed in claim 4 is characterized in that, the intrinsic parameter of described picture pick-up device and outer parameter comprise: confidential reference items matrix K, rotation matrix R and translation vector t.
6. the Panoramagram montage method based on the picture pick-up device self-calibration technology as claimed in claim 1, it is characterized in that, big overlapping region is arranged between the image that described a plurality of picture pick-up device is taken, and substantially parallel in the view directions of a plurality of picture pick-up devices described in the gatherer process.
7. the Panoramagram montage method based on the picture pick-up device self-calibration technology as claimed in claim 4, it is characterized in that, described intrinsic parameter and outer selection of parameter best alignment plane according to the described picture pick-up device of demarcating, and all images is calibrated to described best alignment plane further comprise:
Use the normal direction of the optimum calibration plane of ransac algorithm computation;
Calculate the rotation matrix of each picture pick-up device optical axis direction according to the intrinsic parameter of described picture pick-up device and the normal direction of outer parameter and described optimum calibration plane to described optimum calibration plane normal direction;
Determine the calibration homograph of every width of cloth image according to described rotation matrix; With
According to described calibration homograph every width of cloth image is calibrated.
8. the Panoramagram montage device based on the picture pick-up device self-calibration technology is characterized in that, comprising:
Demarcating module, be used for panoramic picture to the scene of a plurality of picture pick-up device collections adopt from calibration algorithm demarcate described picture pick-up device intrinsic parameter and outside parameter;
Calibration module is used for intrinsic parameter and outer selection of parameter best alignment plane according to the described picture pick-up device of described demarcating module demarcation, and all images is calibrated to described best alignment plane; With
Concatenation module is used on described best alignment plane all images being spliced into an entire image, and the overlapping region of described entire image is merged.
9. the Panoramagram montage device based on the picture pick-up device self-calibration technology as claimed in claim 8, it is characterized in that, also comprise pretreatment module, be used to use Gaussian filter that image is carried out denoising and use histogram equalizing method to recover to lose by the overexposure or the image detail that causes of owing to expose to the sun that illumination causes.
10. the Panoramagram montage device based on the picture pick-up device self-calibration technology as claimed in claim 8, it is characterized in that, big overlapping region is arranged between the image that described a plurality of picture pick-up device is taken, and substantially parallel in the view directions of a plurality of picture pick-up devices described in the gatherer process.
11. based on the Panoramagram montage device of picture pick-up device self-calibration technology, it is characterized in that as claimed in claim 8 or 9 described demarcating module comprises:
Matched sub-block, the unique point that is used for detected image, and the unique point in per two width of cloth images mated, and adopt the ransac algorithm that the fundamental matrix between two picture pick-up devices is carried out Robust Estimation according to described Feature Points Matching result, to obtain robust features point matching relationship;
The projective reconstruction submodule is used for carrying out projective reconstruction according to described robust features point matching relationship, and adopts linear calibration's algorithm directly to calibrate the transformation matrix that projective space is rebuild to tolerance; With
The parameter acquiring submodule is used for obtaining the intrinsic parameter of described picture pick-up device and outer parameter according to described transformation matrix.
12. the Panoramagram montage device based on the picture pick-up device self-calibration technology as claimed in claim 11 is characterized in that, the intrinsic parameter of described picture pick-up device and outer parameter comprise: confidential reference items matrix K, rotation matrix R and translation vector t.
13. the Panoramagram montage device based on the picture pick-up device self-calibration technology as claimed in claim 11 is characterized in that described calibration module comprises:
The normal direction calculating sub module is used to use the normal direction of the optimum calibration plane of ransac algorithm computation;
The rotation matrix calculating sub module is used for calculating the rotation matrix of each picture pick-up device optical axis direction to described optimum calibration plane normal direction according to the intrinsic parameter of described picture pick-up device and the normal direction of outer parameter and described optimum calibration plane;
The calibration homograph is determined submodule, is used for determining according to described rotation matrix the calibration homograph of every width of cloth image; With
The calibration submodule is used for according to described calibration homograph every width of cloth image being calibrated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010102121360A CN101866482B (en) | 2010-06-21 | 2010-06-21 | Panorama splicing method based on camera self-calibration technology, and device thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010102121360A CN101866482B (en) | 2010-06-21 | 2010-06-21 | Panorama splicing method based on camera self-calibration technology, and device thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101866482A true CN101866482A (en) | 2010-10-20 |
| CN101866482B CN101866482B (en) | 2012-02-15 |
Family
ID=42958196
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2010102121360A Active CN101866482B (en) | 2010-06-21 | 2010-06-21 | Panorama splicing method based on camera self-calibration technology, and device thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101866482B (en) |
Cited By (33)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102404598A (en) * | 2011-11-22 | 2012-04-04 | 浙江大学 | Image generation system and method for stereoscopic 3D display |
| CN103078924A (en) * | 2012-12-28 | 2013-05-01 | 华为技术有限公司 | Visual field sharing method and equipment |
| CN103150715A (en) * | 2013-03-13 | 2013-06-12 | 腾讯科技（深圳）有限公司 | Image stitching processing method and device |
| CN103530870A (en) * | 2012-07-02 | 2014-01-22 | 索尼公司 | System and method for correcting binocular photography with homographic transformations |
| CN103679676A (en) * | 2013-12-02 | 2014-03-26 | 西北工业大学 | Quick unordered image stitching method based on multi-level word bag clustering |
| CN103793891A (en) * | 2012-10-26 | 2014-05-14 | 海法科技有限公司 | Low-complexity panorama image joint method |
| CN104065863A (en) * | 2013-03-19 | 2014-09-24 | 腾讯科技（深圳）有限公司 | Image processing method and processing device |
| CN104253948A (en) * | 2013-06-25 | 2014-12-31 | 全视技术有限公司 | Method and apparatus for distributed image processing in cameras for minimizing artifacts in stitched images |
| CN104637041A (en) * | 2014-12-31 | 2015-05-20 | 浙江理工大学 | Wide fabric image acquiring and splicing method based on reference characteristics |
| CN104715482A (en) * | 2015-03-20 | 2015-06-17 | 四川大学 | Setting algorithm for calculating interior point threshold in fundamental matrix through RANSAC |
| CN105023260A (en) * | 2014-04-22 | 2015-11-04 | Tcl集团股份有限公司 | Panorama image fusion method and fusion apparatus |
| CN105094739A (en) * | 2015-08-25 | 2015-11-25 | 北京航空航天大学 | Multi-terminal-screen automatic splicing method based on front cameras of mobile terminals |
| CN105262958A (en) * | 2015-10-15 | 2016-01-20 | 电子科技大学 | Panoramic feature splicing system with virtual viewpoint and method thereof |
| CN105303615A (en) * | 2015-11-06 | 2016-02-03 | 中国民航大学 | Combination method of two-dimensional stitching and three-dimensional surface reconstruction of image |
| CN105447850A (en) * | 2015-11-12 | 2016-03-30 | 浙江大学 | Panorama stitching synthesis method based on multi-view images |
| CN106157304A (en) * | 2016-07-01 | 2016-11-23 | 成都通甲优博科技有限责任公司 | A kind of Panoramagram montage method based on multiple cameras and system |
| CN106600649A (en) * | 2016-12-07 | 2017-04-26 | 西安蒜泥电子科技有限责任公司 | Camera self-calibration method based on two-dimensional mark code |
| CN106657910A (en) * | 2016-12-22 | 2017-05-10 | 国网浙江省电力公司杭州供电公司 | Panoramic video monitoring method for power substation |
| CN106991701A (en) * | 2016-04-21 | 2017-07-28 | 深圳市圆周率软件科技有限责任公司 | A kind of calibration system and method for panorama shooting device parameter |
| CN107040783A (en) * | 2015-10-22 | 2017-08-11 | 联发科技股份有限公司 | Video coding, coding/decoding method and the device of the non-splicing picture of video coding system |
| CN107274380A (en) * | 2017-07-07 | 2017-10-20 | 北京大学 | A kind of quick joining method of unmanned plane multispectral image |
| CN107395989A (en) * | 2017-08-31 | 2017-11-24 | 广东欧珀移动通信有限公司 | Image split-joint method, mobile terminal and system for image mosaic |
| CN107689029A (en) * | 2017-09-01 | 2018-02-13 | 努比亚技术有限公司 | Image processing method, mobile terminal and computer-readable recording medium |
| CN108012155A (en) * | 2016-10-27 | 2018-05-08 | 联发科技股份有限公司 | Method for video coding, video encoding/decoding method and the relevant device of pre-splicing image |
| CN108605100A (en) * | 2016-02-17 | 2018-09-28 | 三星电子株式会社 | Method for handling image and the electronic device for supporting this method |
| CN108765493A (en) * | 2018-04-25 | 2018-11-06 | 信利光电股份有限公司 | A kind of calibrating installation and calibration method of panorama module splicing dislocation |
| CN109255754A (en) * | 2018-09-30 | 2019-01-22 | 北京宇航时代科技发展有限公司 | A kind of large scene polyphaser image mosaic and the method and system really showed |
| CN109285136A (en) * | 2018-08-31 | 2019-01-29 | 清华-伯克利深圳学院筹备办公室 | A kind of Multiscale Fusion method, apparatus, storage medium and the terminal of image |
| CN109683710A (en) * | 2018-12-20 | 2019-04-26 | 北京字节跳动网络技术有限公司 | A kind of palm normal vector determines method, apparatus, equipment and storage medium |
| CN110198438A (en) * | 2019-07-05 | 2019-09-03 | 浙江开奇科技有限公司 | Image treatment method and terminal device for panoramic video image |
| CN110945315A (en) * | 2017-04-18 | 2020-03-31 | 罗维阿克有限公司 | OCT image acquisition equipment |
| CN111813290A (en) * | 2020-09-09 | 2020-10-23 | 武汉中科通达高新技术股份有限公司 | Data processing method and device and electronic equipment |
| CN112419383A (en) * | 2020-10-30 | 2021-02-26 | 中山大学 | Depth map generation method and device and storage medium |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102595178B (en) * | 2012-02-27 | 2015-09-02 | 浙江大学 | Field stitching three dimensional rendered images corrective system and bearing calibration |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1490765A (en) * | 2002-10-18 | 2004-04-21 | �Ϻ���ͨ��ѧ | Method for calibrating camera and colour reference thereby |
| CN101706957A (en) * | 2009-10-30 | 2010-05-12 | 无锡景象数字技术有限公司 | Self-calibration method for binocular stereo vision device |
-
2010
- 2010-06-21 CN CN2010102121360A patent/CN101866482B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1490765A (en) * | 2002-10-18 | 2004-04-21 | �Ϻ���ͨ��ѧ | Method for calibrating camera and colour reference thereby |
| CN101706957A (en) * | 2009-10-30 | 2010-05-12 | 无锡景象数字技术有限公司 | Self-calibration method for binocular stereo vision device |
Non-Patent Citations (1)
| Title |
|---|
| 《中国优秀硕士论文电子期刊网信息科技辑》 20090215 高俊鑫 基于摄像机精确标定的全景图拼接 正文第8页，第18页，第30-40页 1-6、8-12 , 2 * |
Cited By (54)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102404598A (en) * | 2011-11-22 | 2012-04-04 | 浙江大学 | Image generation system and method for stereoscopic 3D display |
| CN103530870B (en) * | 2012-07-02 | 2017-12-26 | 索尼公司 | The system and method photographed with homograph correction binocular |
| CN103530870A (en) * | 2012-07-02 | 2014-01-22 | 索尼公司 | System and method for correcting binocular photography with homographic transformations |
| CN103793891A (en) * | 2012-10-26 | 2014-05-14 | 海法科技有限公司 | Low-complexity panorama image joint method |
| CN103078924A (en) * | 2012-12-28 | 2013-05-01 | 华为技术有限公司 | Visual field sharing method and equipment |
| CN103150715B (en) * | 2013-03-13 | 2016-10-19 | 腾讯科技（深圳）有限公司 | Image mosaic processing method and processing device |
| CN103150715A (en) * | 2013-03-13 | 2013-06-12 | 腾讯科技（深圳）有限公司 | Image stitching processing method and device |
| CN104065863B (en) * | 2013-03-19 | 2018-06-19 | 腾讯科技（深圳）有限公司 | Image processing method and processing unit |
| CN104065863A (en) * | 2013-03-19 | 2014-09-24 | 腾讯科技（深圳）有限公司 | Image processing method and processing device |
| CN104253948A (en) * | 2013-06-25 | 2014-12-31 | 全视技术有限公司 | Method and apparatus for distributed image processing in cameras for minimizing artifacts in stitched images |
| CN103679676A (en) * | 2013-12-02 | 2014-03-26 | 西北工业大学 | Quick unordered image stitching method based on multi-level word bag clustering |
| CN105023260A (en) * | 2014-04-22 | 2015-11-04 | Tcl集团股份有限公司 | Panorama image fusion method and fusion apparatus |
| CN104637041B (en) * | 2014-12-31 | 2017-06-23 | 浙江理工大学 | A kind of broad fabrics image based on reference feature is obtained and joining method |
| CN104637041A (en) * | 2014-12-31 | 2015-05-20 | 浙江理工大学 | Wide fabric image acquiring and splicing method based on reference characteristics |
| CN104715482B (en) * | 2015-03-20 | 2017-08-11 | 四川大学 | A kind of RANSAC calculates point thresholding automatic setting method in fundamental matrix |
| CN104715482A (en) * | 2015-03-20 | 2015-06-17 | 四川大学 | Setting algorithm for calculating interior point threshold in fundamental matrix through RANSAC |
| CN105094739A (en) * | 2015-08-25 | 2015-11-25 | 北京航空航天大学 | Multi-terminal-screen automatic splicing method based on front cameras of mobile terminals |
| CN105094739B (en) * | 2015-08-25 | 2018-06-12 | 北京航空航天大学 | A kind of multiple terminals screen method for automatically split-jointing based on mobile terminal front camera |
| CN105262958A (en) * | 2015-10-15 | 2016-01-20 | 电子科技大学 | Panoramic feature splicing system with virtual viewpoint and method thereof |
| CN105262958B (en) * | 2015-10-15 | 2018-08-21 | 电子科技大学 | A kind of the panorama feature splicing system and its method of virtual view |
| CN107040783A (en) * | 2015-10-22 | 2017-08-11 | 联发科技股份有限公司 | Video coding, coding/decoding method and the device of the non-splicing picture of video coding system |
| CN105303615A (en) * | 2015-11-06 | 2016-02-03 | 中国民航大学 | Combination method of two-dimensional stitching and three-dimensional surface reconstruction of image |
| CN105447850B (en) * | 2015-11-12 | 2018-02-09 | 浙江大学 | A kind of Panoramagram montage synthetic method based on multi-view image |
| CN105447850A (en) * | 2015-11-12 | 2016-03-30 | 浙江大学 | Panorama stitching synthesis method based on multi-view images |
| US20190037138A1 (en) * | 2016-02-17 | 2019-01-31 | Samsung Electronics Co., Ltd. | Method for processing image and electronic device for supporting same |
| CN108605100A (en) * | 2016-02-17 | 2018-09-28 | 三星电子株式会社 | Method for handling image and the electronic device for supporting this method |
| US10868959B2 (en) | 2016-02-17 | 2020-12-15 | Samsung Electronics Co., Ltd. | Method for processing image and electronic device for supporting same |
| CN106991701A (en) * | 2016-04-21 | 2017-07-28 | 深圳市圆周率软件科技有限责任公司 | A kind of calibration system and method for panorama shooting device parameter |
| WO2017181839A1 (en) * | 2016-04-21 | 2017-10-26 | 深圳市圆周率软件科技有限责任公司 | System and method of calibrating apparatus parameter for panoramic photography |
| US11024057B2 (en) | 2016-04-21 | 2021-06-01 | Shenzhen Pisoftware Technology Co., Ltd. | Calibration system and method for panoramic photographing device parameter |
| CN106157304A (en) * | 2016-07-01 | 2016-11-23 | 成都通甲优博科技有限责任公司 | A kind of Panoramagram montage method based on multiple cameras and system |
| CN108012155B (en) * | 2016-10-27 | 2020-01-07 | 联发科技股份有限公司 | Video coding method and video decoding method of pre-spliced image and related devices |
| CN108012155A (en) * | 2016-10-27 | 2018-05-08 | 联发科技股份有限公司 | Method for video coding, video encoding/decoding method and the relevant device of pre-splicing image |
| CN106600649A (en) * | 2016-12-07 | 2017-04-26 | 西安蒜泥电子科技有限责任公司 | Camera self-calibration method based on two-dimensional mark code |
| CN106657910B (en) * | 2016-12-22 | 2018-10-09 | 国网浙江省电力公司杭州供电公司 | A kind of panoramic video monitoring method of electricity substation |
| CN106657910A (en) * | 2016-12-22 | 2017-05-10 | 国网浙江省电力公司杭州供电公司 | Panoramic video monitoring method for power substation |
| CN110945315A (en) * | 2017-04-18 | 2020-03-31 | 罗维阿克有限公司 | OCT image acquisition equipment |
| CN110945315B (en) * | 2017-04-18 | 2022-07-22 | 欧库麦克斯医疗保健有限公司 | OCT image acquisition equipment |
| US11659991B2 (en) | 2017-04-18 | 2023-05-30 | Ocumax Healthcare Gmbh | OCT image capture device |
| CN107274380B (en) * | 2017-07-07 | 2019-10-11 | 北京大学 | A kind of quick joining method of unmanned plane multispectral image |
| CN107274380A (en) * | 2017-07-07 | 2017-10-20 | 北京大学 | A kind of quick joining method of unmanned plane multispectral image |
| CN107395989A (en) * | 2017-08-31 | 2017-11-24 | 广东欧珀移动通信有限公司 | Image split-joint method, mobile terminal and system for image mosaic |
| CN107689029A (en) * | 2017-09-01 | 2018-02-13 | 努比亚技术有限公司 | Image processing method, mobile terminal and computer-readable recording medium |
| CN108765493A (en) * | 2018-04-25 | 2018-11-06 | 信利光电股份有限公司 | A kind of calibrating installation and calibration method of panorama module splicing dislocation |
| CN109285136A (en) * | 2018-08-31 | 2019-01-29 | 清华-伯克利深圳学院筹备办公室 | A kind of Multiscale Fusion method, apparatus, storage medium and the terminal of image |
| CN109285136B (en) * | 2018-08-31 | 2021-06-08 | 清华-伯克利深圳学院筹备办公室 | Multi-scale fusion method and device for images, storage medium and terminal |
| CN109255754B (en) * | 2018-09-30 | 2023-03-14 | 北京宇航时代科技发展有限公司 | Method and system for splicing and really displaying large-scene multi-camera images |
| CN109255754A (en) * | 2018-09-30 | 2019-01-22 | 北京宇航时代科技发展有限公司 | A kind of large scene polyphaser image mosaic and the method and system really showed |
| WO2020124995A1 (en) * | 2018-12-20 | 2020-06-25 | 北京字节跳动网络技术有限公司 | Palm normal vector determination method, device and apparatus, and storage medium |
| CN109683710A (en) * | 2018-12-20 | 2019-04-26 | 北京字节跳动网络技术有限公司 | A kind of palm normal vector determines method, apparatus, equipment and storage medium |
| CN110198438A (en) * | 2019-07-05 | 2019-09-03 | 浙江开奇科技有限公司 | Image treatment method and terminal device for panoramic video image |
| CN111813290A (en) * | 2020-09-09 | 2020-10-23 | 武汉中科通达高新技术股份有限公司 | Data processing method and device and electronic equipment |
| CN112419383A (en) * | 2020-10-30 | 2021-02-26 | 中山大学 | Depth map generation method and device and storage medium |
| CN112419383B (en) * | 2020-10-30 | 2023-07-28 | 中山大学 | Depth map generation method, device and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101866482B (en) | 2012-02-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101866482B (en) | Panorama splicing method based on camera self-calibration technology, and device thereof | |
| CN101706957B (en) | Self-calibration method for binocular stereo vision device | |
| Wang et al. | 360sd-net: 360 stereo depth estimation with learnable cost volume | |
| CN106875451B (en) | Camera calibration method and device and electronic equipment | |
| CN105245841B (en) | A kind of panoramic video monitoring system based on CUDA | |
| WO2021004416A1 (en) | Method and apparatus for establishing beacon map on basis of visual beacons | |
| CN107705252B (en) | Method and system suitable for splicing, unfolding and correcting binocular fisheye image | |
| US9824486B2 (en) | High resolution free-view interpolation of planar structure | |
| CN107316275A (en) | A kind of large scale Microscopic Image Mosaicing algorithm of light stream auxiliary | |
| Li et al. | Large scale image mosaic construction for agricultural applications | |
| CN103761721B (en) | One is applicable to space rope system machine human stereo vision fast image splicing method | |
| CN108073857A (en) | The method and device of dynamic visual sensor DVS event handlings | |
| CN101146231A (en) | Method for generating panoramic video according to multi-visual angle video stream | |
| KR20200014858A (en) | Location measurement and simultaneous mapping method and apparatus | |
| CN106056622B (en) | A kind of multi-view depth video restored method based on Kinect cameras | |
| CN104318604A (en) | 3D image stitching method and apparatus | |
| CN102164269A (en) | Method and device for monitoring panoramic view | |
| CN110874854A (en) | Large-distortion wide-angle camera binocular photogrammetry method based on small baseline condition | |
| Fang et al. | Self-supervised camera self-calibration from video | |
| CN116579962A (en) | Panoramic sensing method, device, equipment and medium based on fisheye camera | |
| US20090059018A1 (en) | Navigation assisted mosaic photography | |
| Lao et al. | Solving rolling shutter 3d vision problems using analogies with non-rigidity | |
| CN103793891A (en) | Low-complexity panorama image joint method | |
| CN109089048A (en) | More camera lens full-view cooperative device and methods | |
| CN108765292A (en) | Image split-joint method based on the fitting of space triangular dough sheet |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |