CN107147879A - A kind of real-time video joining method - Google Patents
A kind of real-time video joining method Download PDFInfo
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- CN107147879A CN107147879A CN201710406636.XA CN201710406636A CN107147879A CN 107147879 A CN107147879 A CN 107147879A CN 201710406636 A CN201710406636 A CN 201710406636A CN 107147879 A CN107147879 A CN 107147879A
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- 238000000034 method Methods 0.000 title claims abstract description 22
- 239000011159 matrix material Substances 0.000 claims abstract description 7
- 238000001514 detection method Methods 0.000 claims description 7
- 230000004927 fusion Effects 0.000 claims description 3
- 238000002187 spin decoupling employing ultra-broadband-inversion sequences generated via simulated annealing Methods 0.000 claims description 2
- 230000009466 transformation Effects 0.000 abstract description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- G06T3/14—
Abstract
The present invention relates to generation information technology field, a kind of real-time video joining method is disclosed, including opens video equipment file, the parameter initialization of video acquisition is carried out；The frame buffer zone applied is queued up in video acquisition input rank, and starts video acquisition；Frame of video 1 and frame of video 2 are obtained, and determines whether key frame；For key frame, the characteristic matching point pair of two frame of video is found, transformation matrix is obtained, the frame after deformation is merged to form spliced map.Using existing video acquisition hardware and computer, algorithm and software approach are succinct, and computer performs speed soon, with higher practical value.
Description
Technical field
The present invention relates to generation information technology field, relate more specifically to a kind of real-time video joining method.
Background technology
With multimedia technology develop it is increasingly faster, various video processing techniques enter people's life, wherein more
Popular is exactly video-splicing.Either military domain or civil area, such as monitoring, commander, scheduling system, public security, fire-fighting,
In the monitoring system such as military affairs, meteorology, railway, aviation, video conference, inquiry system etc., be directed to video-splicing.
Research both at home and abroad on image mosaic is a lot, is broadly divided into the image mosaic based on frequency domain, gray scale and characteristic value
Algorithm.The wherein stitching algorithm based on frequency domain is realized relatively simple, but can produce high fdrequency component, therefore the scope of application is smaller；Base
Slower in the stitching algorithm matching speed of gray scale, operand is larger, and applicability is general；Feature based value matching algorithm then have compared with
Good imaging results, applicability is higher.
Existing Video processing software, can be handled video file, including realize video-splicing function, but nothing
Method accomplishes real time video collection, real-time video splicing.
In existing achievement in research and open source literature, a kind of real-time video joining method is not yet found, real-time video is adopted
Collection, real-time video splicing.
The content of the invention
Goal of the invention
The present invention proposes a kind of real-time video joining method, can utilize existing video acquisition hardware and computer, enter
While row real time video collection, video-splicing is carried out in real time.
The technical solution adopted in the present invention
A kind of real-time video joining method proposed by the present invention, comprises the following steps：
(1) video equipment file is opened, the parameter initialization of video acquisition is carried out；
(2) apply for the frame buffer zone of some video acquisitions, and these frame buffer zones are mapped to user's space from kernel spacing, just
In application program reading process video data；
(3) frame buffer zone applied is queued up in video acquisition input rank, and starts video acquisition；
(4) frame buffer zone is taken out from video acquisition output queue, frame buffer zone is reentered into video acquisition input rank, circulated
Back and forth gather continuous video data；
(5) frame of video 1 and frame of video 2 are obtained, and determines whether key frame；
(6) if key frame, then the characteristic matching point pair of two frame of video is found using algorithm 1, change is obtained using algorithm 2
Matrix is changed, the frame after deformation is formed spliced map using the fusion of algorithm 3；
(7) if not key frame, then directly merge to form spliced map by two frame of video;
(8) file system is arrived into the storage of spliced video.
Further, in the step (1), the acquisition window of api interface setting video image, the dot matrix of collection are passed through
Size and form.
Further, in the step (5), the image lap of frame of video 1 and frame of video 2 20%-30% it
Between.
Further, in the step (6), algorithm 1 is calculated using Moravec Corner Detection Algorithms, SUSAN Corner Detections
One kind in method and Harris Corner Detection Algorithms.
Further, in the step (6), algorithm 2 comprises the following steps：Selected characteristic matching double points in order,
The point that matching centering feature point principal direction and length are all matched is remained, and incongruent matching double points are all given up, Zhi Daojian
All characteristic matching points pair are surveyed.
Further, in the step (6), algorithm 3 is using direct average algorithm, Weighted Average Algorithm, distance weighting
One kind in algorithm, Poisson algorithm and contrast modulation algorithm.
Technique effect produced by the present invention
A kind of real-time video joining method proposed by the present invention, using existing video acquisition hardware and computer, algorithm and soft
Part method is succinct, and computer performs speed soon, with higher practical value.
Brief description of the drawings
Fig. 1 real time video collection splicing systems.
Embodiment
Embodiment
Using existing video acquisition hardware, Haikang prestige regards DS-2CD4024F-SDI, day and night type gun shaped digital camera,
H.264, realtime graphic is using encoding, and highest resolution is up to 2,000,000 pixels（1920×1080）.
(1) video equipment file is opened, the parameter initialization of video acquisition is carried out, video image is set by api interface
Acquisition window, collection dot matrix size and form；
(2) apply for the frame buffer zone of some video acquisitions, and these frame buffer zones are mapped to user's space from kernel spacing, just
In application program reading process video data；
(3) frame buffer zone applied is queued up in video acquisition input rank, and starts video acquisition；
(4) frame buffer zone is taken out from video acquisition output queue, frame buffer zone is reentered into video acquisition input rank, circulated
Back and forth gather continuous video data；
(5) frame of video 1 and frame of video 2 are obtained, and determines whether the image lap of key frame, frame of video 1 and frame of video 2
Between 20%-30%；
(6) if key frame, then find the characteristic matching point pair of two frame of video using Moravec Corner Detection Algorithms,
Selected characteristic matching double points in order, the point that matching centering feature point principal direction and length are all matched is remained, and is not inconsistent
The matching double points of conjunction are all given up, and until having detected all characteristic matching points pair, obtain transformation matrix, and the frame after deformation is utilized and added
Weight average algorithm fusion formation spliced map；
(7) if not key frame, then directly merge to form spliced map by two frame of video;
(8) file system is arrived into the storage of spliced video.
The experimental results are shown inthe following table, splicing number of times, matching number and characteristic value number.
| Splice number of times | Match number | Characteristic value number |
| 1 | 88 | 1857×1623 |
| 2 | 67 | 1726×1438 |
| 3 | 59 | 1692×1254 |
Embodiment of above is merely to illustrate the present invention, and not limitation of the present invention, about the common of technical field
Technical staff, without departing from the spirit and scope of the present invention, can also make a variety of changes and modification, therefore all
Equivalent technical scheme falls within scope of the invention, and scope of patent protection of the invention should be defined by the claims.
Claims (6)
1. a kind of real-time video joining method, it is characterised in that：Comprise the following steps：
(1) video equipment file is opened, the parameter initialization of video acquisition is carried out；
(2) apply for the frame buffer zone of some video acquisitions, and these frame buffer zones are mapped to user's space from kernel spacing, just
In application program reading process video data；
(3) frame buffer zone applied is queued up in video acquisition input rank, and starts video acquisition；
(4) frame buffer zone is taken out from video acquisition output queue, frame buffer zone is reentered into video acquisition input rank, circulated
Back and forth gather continuous video data；
(5) frame of video 1 and frame of video 2 are obtained, and determines whether key frame；
(6) if key frame, then the characteristic matching point pair of two frame of video is found using algorithm 1, change is obtained using algorithm 2
Matrix is changed, the frame after deformation is formed spliced map using the fusion of algorithm 3；
(7) if not key frame, then directly merge to form spliced map by two frame of video;
(8) file system is arrived into the storage of spliced video.
2. a kind of real-time video joining method according to claim 1, it is characterised in that：In the step (1), pass through
Api interface sets acquisition window, the dot matrix size of collection and the form of video image.
3. a kind of real-time video joining method according to claim 1, it is characterised in that：In the step (5), video
Frame 1 and the image lap of frame of video 2 are between 20%-30%.
4. a kind of real-time video joining method according to claim 1, it is characterised in that：In the step (6), algorithm
1 using one kind in Moravec Corner Detection Algorithms, SUSAN Corner Detection Algorithms and Harris Corner Detection Algorithms.
5. a kind of real-time video joining method according to claim 1, it is characterised in that：In the step (6), algorithm
2 comprise the following steps：Selected characteristic matching double points in order, the point that matching centering feature point principal direction and length are all matched is protected
Stay, and incongruent matching double points are all given up, until having detected all characteristic matching points pair.
6. a kind of real-time video joining method according to claim 1, it is characterised in that：In the step (6), algorithm
3 using one kind in direct average algorithm, Weighted Average Algorithm, distance weighting algorithm, Poisson algorithm and contrast modulation algorithm.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201710406636.XA CN107147879A (en) | 2017-06-02 | 2017-06-02 | A kind of real-time video joining method |
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| CN201710406636.XA CN107147879A (en) | 2017-06-02 | 2017-06-02 | A kind of real-time video joining method |
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| CN107147879A true CN107147879A (en) | 2017-09-08 |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109348140A (en) * | 2018-10-12 | 2019-02-15 | 西安理工大学 | The joining method of real-time video under a kind of monitoring scene |
| CN109919971A (en) * | 2017-12-13 | 2019-06-21 | 北京金山云网络技术有限公司 | Image processing method, device, electronic equipment and computer readable storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201947404U (en) * | 2010-04-12 | 2011-08-24 | 范治江 | Panoramic video real-time splice display system |
| CN102201115A (en) * | 2011-04-07 | 2011-09-28 | 湖南天幕智能科技有限公司 | Real-time panoramic image stitching method of aerial videos shot by unmanned plane |
| CN103856727A (en) * | 2014-03-24 | 2014-06-11 | 北京工业大学 | Multichannel real-time video splicing processing system |
| CN103985254A (en) * | 2014-05-29 | 2014-08-13 | 四川川大智胜软件股份有限公司 | Multi-view video fusion and traffic parameter collecting method for large-scale scene traffic monitoring |
| CN103997609A (en) * | 2014-06-12 | 2014-08-20 | 四川川大智胜软件股份有限公司 | Multi-video real-time panoramic fusion splicing method based on CUDA |
-
2017
- 2017-06-02 CN CN201710406636.XA patent/CN107147879A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201947404U (en) * | 2010-04-12 | 2011-08-24 | 范治江 | Panoramic video real-time splice display system |
| CN102201115A (en) * | 2011-04-07 | 2011-09-28 | 湖南天幕智能科技有限公司 | Real-time panoramic image stitching method of aerial videos shot by unmanned plane |
| CN103856727A (en) * | 2014-03-24 | 2014-06-11 | 北京工业大学 | Multichannel real-time video splicing processing system |
| CN103985254A (en) * | 2014-05-29 | 2014-08-13 | 四川川大智胜软件股份有限公司 | Multi-view video fusion and traffic parameter collecting method for large-scale scene traffic monitoring |
| CN103997609A (en) * | 2014-06-12 | 2014-08-20 | 四川川大智胜软件股份有限公司 | Multi-video real-time panoramic fusion splicing method based on CUDA |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109919971A (en) * | 2017-12-13 | 2019-06-21 | 北京金山云网络技术有限公司 | Image processing method, device, electronic equipment and computer readable storage medium |
| CN109919971B (en) * | 2017-12-13 | 2021-07-20 | 北京金山云网络技术有限公司 | Image processing method, image processing device, electronic equipment and computer readable storage medium |
| CN109348140A (en) * | 2018-10-12 | 2019-02-15 | 西安理工大学 | The joining method of real-time video under a kind of monitoring scene |
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Application publication date: 20170908 |