CN113536984B - Image target identification and tracking system based on unmanned aerial vehicle - Google Patents
Image target identification and tracking system based on unmanned aerial vehicle Download PDFInfo
- Publication number
- CN113536984B CN113536984B CN202110722945.4A CN202110722945A CN113536984B CN 113536984 B CN113536984 B CN 113536984B CN 202110722945 A CN202110722945 A CN 202110722945A CN 113536984 B CN113536984 B CN 113536984B
- Authority
- CN
- China
- Prior art keywords
- target
- image
- aerial vehicle
- unmanned aerial
- module
- 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.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/30—Transforming light or analogous information into electric information
- H04N5/33—Transforming infrared radiation
Landscapes
- Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Theoretical Computer Science (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Engineering & Computer Science (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Physics & Mathematics (AREA)
- Artificial Intelligence (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Closed-Circuit Television Systems (AREA)
- Image Analysis (AREA)
Abstract
The application provides an image target identification and tracking system based on unmanned aerial vehicle, adopts the shooting mode that visible light and infrared light switch to carry out target image acquisition to obtain the image of target under the visual angle that relative coordinate corresponds according to the relative coordinate of unmanned aerial vehicle and target, adopt the iterative target identification algorithm of regional convergence to discern the target in the image. Meanwhile, according to the historical motion track and the motion posture of the target, the position of the target at the current moment and the relative angle between the target and the unmanned aerial vehicle are predicted, and the target image is superposed on the faded shelter so as to realize the continuous tracking of the target. Through the design of the system, the accuracy and efficiency of target identification can be improved, and the target can be continuously tracked, so that the target is not lost in the image, and good manipulation experience is provided for an operator.
Description
Technical Field
The method is applied to the field of unmanned aerial vehicle image recognition and tracking.
Background
Unmanned aerial vehicle is as the flight equipment that can remove in a flexible way, and its wide application is in each trade field. Currently, tracking and shooting a target by adopting an unmanned aerial vehicle becomes a research hotspot. The unmanned aerial vehicle can track and shoot the target under the conditions of multiple visual angles and multiple distances by virtue of the flexible control performance of the unmanned aerial vehicle.
However, since both the drone and the target are moving objects, various problems are easily caused in the process of identifying and tracking the target in the photographed picture for the drone. If the unmanned aerial vehicle and the target both move, the target is easily lost; the switching of the unmanned aerial vehicle and the target from different visual angles causes great changes in the characteristics of the target image, which causes great difficulty in identifying the target; the recognition efficiency of the target in the image can be greatly reduced by the movement of the unmanned aerial vehicle and the target; when the target is occluded by a building or the like, a brief loss of the target may result. Based on the above problem, this application has provided an image target identification and tracker based on unmanned aerial vehicle.
Disclosure of Invention
The purpose of the invention is realized by the following technical scheme.
In order to solve the problems, the invention provides an image target recognition and tracking system based on an unmanned aerial vehicle.
The system comprises: the system comprises an unmanned aerial vehicle camera, an unmanned aerial vehicle camera control module, an unmanned aerial vehicle image preprocessing module, an unmanned aerial vehicle target identification module, a position adjusting module, a target tracking module and a target display module; wherein each module comprises the following functions:
the unmanned aerial vehicle camera acquires a high-resolution image containing a tracking target and an environment;
further, the unmanned aerial vehicle camera comprises a visible light shooting device and an infrared light shooting device; the infrared light shooting device can shoot an infrared image of the target object;
the unmanned aerial vehicle camera control module is used for adjusting the shooting mode of the camera;
further, unmanned aerial vehicle camera control module shoots the mode to the camera and adjusts, specifically includes:
when the unmanned aerial vehicle is in a night flight mode, controlling the infrared light shooting device to be started, and taking an image shot by the infrared light shooting device as a high-resolution image;
when the unmanned aerial vehicle is in a daytime flight mode, if the unmanned aerial vehicle is shot by a visible light shooting device at present, an environment color temperature value and a high-resolution image color temperature value are obtained, a brightness parameter value in an image HSV (hue, saturation and value) model is obtained, and whether the shooting mode is switched or not is determined by a threshold comparison method;
when unmanned aerial vehicle is in daytime flight mode, if adopt the infrared light to shoot when the device shoots, acquire environment colour temperature value, decide whether to switch shooting mode through threshold value comparison method.
The unmanned aerial vehicle image preprocessing module is used for preprocessing the high-resolution image;
the unmanned aerial vehicle target identification module is used for identifying a tracking target in the image;
further, unmanned aerial vehicle target identification module discerns the tracking target in the image, specifically includes:
acquiring three-dimensional space relative coordinates (x, y, z) of the unmanned aerial vehicle relative to the target;
further, the target position is a coordinate origin (0,0, 0);
acquiring a target image under the relative coordinate position visual angle from an unmanned aerial vehicle target object three-dimensional image library, wherein the pixel matrix size of the target image is n x n;
and searching a target image in a central area m × m of the pixel matrix of the high-resolution image.
The position adjusting module is used for controlling the target to be positioned in the central area of the image;
the target tracking module is used for realizing real-time tracking of a target and drawing a target motion track to form a target moving log;
further, the target tracking module is configured to track a target in real time, draw a target motion trajectory, and form a target movement log, and specifically includes:
storing the target motion track and the motion posture of the target, and storing to form a target movement log;
when a blocking object blocks the target or the target is not identified in the high-resolution image, predicting the position of the target at the current moment and the relative angle between the target and the unmanned aerial vehicle according to the historical motion track and the motion attitude of the target;
acquiring a predicted target position and a target image of the unmanned aerial vehicle and the target at a predicted relative coordinate view angle from an unmanned aerial vehicle database;
and fading the shelters in the image, and displaying the image of the target under the relative coordinate viewing angle on the faded shelters.
And the target display module is used for realizing the clear display of the tracked target.
Further, the target display module realizes the clear display of the tracked target, and specifically includes:
when a target image is identified in the image, the target image under the relative coordinate view angle acquired in the unmanned aerial vehicle database and the target image identified in the image are displayed in an overlapping mode;
when the target image is not identified in the image, the target image at the perspective of the predicted relative coordinates acquired in the drone database is displayed on the obstruction.
The invention has the advantages that:
1. the target can be accurately identified and tracked in the day and at night through the arrangement of the double cameras of the visible light camera and the infrared light camera; moreover, through a double-parameter comparison algorithm of the brightness parameter and the color temperature value of the color model, more accurate shooting mode switching can be realized, and the accuracy of target identification is further improved;
2. acquiring an image of a target in a three-dimensional image database according to the relative position and distance of the unmanned aerial vehicle relative to the target, and acquiring an accurate target image according to the visual angle of the unmanned aerial vehicle observation target; the inaccuracy caused by target recognition of the fixed target reference image under the condition that the unmanned aerial vehicle and the target both move is avoided; meanwhile, the target image is identified at the center position of the high-resolution image acquired by the unmanned aerial vehicle, so that the target identification efficiency is improved;
3. under the condition that the target is shielded, the position of the target is predicted, the observation visual angle is calculated through the relative coordinates of the unmanned aerial vehicle and the target, the target is displayed on the faded shielding object, the target is prevented from being lost in the image, and a continuous target moving image is provided for an observer.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 shows a structural block diagram of an unmanned aerial vehicle target recognition and tracking system.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
According to the embodiment of the invention, an image target recognition and tracking system based on an unmanned aerial vehicle is provided.
The system comprises: the system comprises an unmanned aerial vehicle camera, an unmanned aerial vehicle camera control module, an unmanned aerial vehicle image preprocessing module, an unmanned aerial vehicle target identification module, a position adjusting module, a target tracking module and a target display module; wherein each module comprises the following functions:
the unmanned aerial vehicle camera acquires a high-resolution image containing a tracking target and an environment;
further, the unmanned aerial vehicle camera comprises a visible light shooting device and an infrared light shooting device; the infrared light shooting device can shoot an infrared image of the target object;
the unmanned aerial vehicle camera control module is used for adjusting the shooting mode of the camera;
further, unmanned aerial vehicle camera control module shoots the mode to the camera and adjusts, specifically includes:
when the unmanned aerial vehicle is in a night flight mode, controlling the infrared light shooting device to be started, and taking an image shot by the infrared light shooting device as a high-resolution image;
when the unmanned aerial vehicle is in a daytime flight mode, if the unmanned aerial vehicle is shot by a visible light shooting device at present, an environment color temperature value and a high-resolution image color temperature value are obtained, a brightness parameter value in an image HSV (hue, saturation and value) model is obtained, and whether the shooting mode is switched or not is determined by a threshold comparison method;
when the shooting mode needs to be switched, switching the mode of shooting by the current visible light shooting device into the mode of shooting by the infrared light shooting device;
further, the method for acquiring the environmental color temperature value and the high-resolution image color temperature value, acquiring the brightness parameter value in the image HSV model, and determining whether to switch the shooting mode through a threshold comparison method comprises the following specific steps:
obtaining an ambient color temperature value E1And the image color temperature value E2；
Acquiring a brightness parameter V in an image color model HSV;
the current luminance value C is calculated using the following formula:
wherein λ1、λ2Is a weighting coefficient;
when the current brightness value C is larger than a preset threshold value D, the current shooting mode is not switched; and when the current brightness value C is smaller than a preset threshold value D, switching the mode of shooting by the current visible light shooting device to the mode of shooting by the infrared light shooting device.
When the unmanned aerial vehicle is in a daytime flight mode, if an infrared light shooting device is adopted for shooting at present, an environment color temperature value is obtained, and whether the shooting mode is switched or not is determined through a threshold comparison method;
when the shooting mode needs to be switched, the mode of shooting by the current infrared light shooting device is switched to the mode of shooting by the visible light shooting device.
Further, the obtaining of the ambient color temperature value determines whether to switch the shooting mode by a threshold comparison method, and the specific method is as follows:
obtaining an ambient color temperature value E1；
When the environmental color temperature value is larger than the current threshold value DEWhen the infrared light shooting device shoots, switching the mode of shooting by the current infrared light shooting device into the mode of shooting by the visible light shooting device; when the environmental color temperature value is less than the current threshold value DEWhen the current shooting mode is switched, the current shooting mode is not switched.
The unmanned aerial vehicle image preprocessing module is used for preprocessing the high-resolution image;
the unmanned aerial vehicle target identification module is used for identifying a tracking target in the image;
further, unmanned aerial vehicle target identification module discerns the tracking target in the image, specifically includes:
acquiring three-dimensional space relative coordinates (x, y, z) of the unmanned aerial vehicle relative to the target;
furthermore, a locator is installed on the target, and the unmanned aerial vehicle can calculate the space relative coordinate of the unmanned aerial vehicle relative to the target according to the locator;
acquiring a target image under the relative coordinate position visual angle from an unmanned aerial vehicle target object three-dimensional image library, wherein the pixel matrix size of the target image is n x n;
further, a three-dimensional stereo structure image of the target, and visible light images and infrared light images of the target under various visual angles are stored in the unmanned aerial vehicle target object three-dimensional image library;
further, acquiring three-dimensional space relative coordinates (x, y, z) of the unmanned aerial vehicle relative to the target, and acquiring a target image under a relative coordinate position view angle in an unmanned aerial vehicle target object three-dimensional image library, specifically:
storing three-dimensional image data of a target in an unmanned aerial vehicle database in advance;
taking the target as a coordinate origin (0,0,0), and acquiring a three-dimensional space relative coordinate (x, y, z) of the unmanned aerial vehicle relative to the target;
calculating a three-dimensional visual angle of the unmanned aerial vehicle relative to the target;
acquiring a target image under the three-dimensional visual angle from a database;
and adjusting the size of the pixel matrix of the acquired target image under the three-dimensional visual angle according to the relative distance between the unmanned aerial vehicle and the target so as to obtain the target image with the matrix size of n x n.
And performing target search in a central area of the pixel matrix of the high-resolution image, wherein the central area is m by adopting the following algorithm.
Taking the central point of the high-resolution image as the central point of the m-m central area, and taking the central point coordinate as an origin coordinate (0, 0); the method adopts an iterative target identification algorithm of area convergence to identify the target, and comprises the following specific steps:
s1: in that
Performing target similarity matching in a square area serving as coordinates of the upper left corner and the lower right corner;
s2 at
Performing target similarity matching in the square area serving as the coordinates of the upper right corner and the lower left corner;
s3 at
Performing target similarity matching in a square area serving as coordinates of the lower left corner and the upper right corner;
s4 at
Performing target similarity matching in a square area serving as coordinates of a lower right corner and an upper left corner;
s5 is in
Performing target similarity matching in a square area serving as coordinates of the upper left corner and the lower right corner;
wherein m is 16 × n;
s6, when the similarity obtained by calculation at the current square area position is larger than a preset threshold value DpTaking the position center of the current square area as the center, reducing m to half of the original value to obtain a new m value, and repeating the steps S1-S6 in the square area with the new m value as the side length;
s7: when m is equal to n, finishing the algorithm, and obtaining the current square area image as the target image;
the position adjusting module is used for controlling the target to be positioned in the central area of the image;
the target tracking module is used for realizing real-time tracking of a target and drawing a target motion track to form a target moving log;
further, the target tracking module is configured to track a target in real time, draw a target motion trajectory, and form a target movement log, and specifically includes:
storing the target motion track and the motion posture of the target, and storing to form a target movement log;
when a blocking object blocks the target or the target is not identified in the high-resolution image, predicting the position of the target at the current moment and the relative angle between the target and the unmanned aerial vehicle according to the historical motion track and the motion attitude of the target;
acquiring a predicted target position and a target image of the unmanned aerial vehicle and the target at a predicted relative coordinate view angle from an unmanned aerial vehicle database;
and fading the shelters in the image, and displaying the image of the target under the relative coordinate viewing angle on the faded shelters.
And the target display module is used for realizing the clear display of the tracked target.
Further, the target display module realizes the clear display of the tracked target, and specifically includes:
when a target image is identified in the image, the target image under the relative coordinate view angle acquired in the unmanned aerial vehicle database and the target image identified in the image are displayed in an overlapping mode;
when the target image is not identified in the image, the target image at the perspective of the predicted relative coordinates acquired in the drone database is displayed on the obstruction.
The invention has the advantages that:
1. the target can be accurately identified and tracked in the day and at night through the arrangement of the double cameras of the visible light camera and the infrared light camera; moreover, through a double-parameter comparison algorithm of the brightness parameter and the color temperature value of the color model, more accurate shooting mode switching can be realized, and the accuracy of target identification is further improved;
2. acquiring an image of a target in a three-dimensional image database according to the relative position and distance of the unmanned aerial vehicle relative to the target, and acquiring an accurate target image according to the visual angle of the unmanned aerial vehicle observation target; the inaccuracy caused by target recognition of the fixed target reference image under the condition that the unmanned aerial vehicle and the target both move is avoided; meanwhile, a target image is identified at the center position of the high-resolution image acquired by the unmanned aerial vehicle, and an iterative target identification algorithm of area convergence is adopted, so that the target identification efficiency is improved;
3. under the condition that the target is shielded, the position of the target is predicted, the observation visual angle is calculated through the relative coordinates of the unmanned aerial vehicle and the target, the image of the target acquired in the unmanned aerial vehicle database under the visual angle is displayed on the faded shielding object, the target is prevented from being lost in the image, and a continuous target moving image is provided for an observer.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (6)
1. An unmanned aerial vehicle-based image target recognition and tracking system, the system comprising: the system comprises an unmanned aerial vehicle camera, an unmanned aerial vehicle camera control module, an unmanned aerial vehicle preprocessing module, an unmanned aerial vehicle target recognition module, a position adjusting module, a target tracking module and a target display module; wherein each module comprises the following functions:
the unmanned aerial vehicle camera acquires a high-resolution image containing a tracking target and an environment;
the unmanned aerial vehicle camera control module is used for adjusting the shooting mode of the camera;
the unmanned aerial vehicle preprocessing module is used for preprocessing the high-resolution image;
the unmanned aerial vehicle target identification module is used for identifying a tracking target in the image;
the position adjusting module is used for controlling the target to be positioned in the central area of the image;
the target tracking module is used for realizing real-time tracking of a target and drawing a target motion track to form a target moving log;
the target display module is used for realizing clear display of the tracked target; wherein, unmanned aerial vehicle camera control module shoots the mode to the camera and adjusts, includes:
when the unmanned aerial vehicle is in a night flight mode, controlling the infrared light shooting device to be started, and taking an image shot by the infrared light shooting device as a high-resolution image;
when the unmanned aerial vehicle is in a daytime flight mode, if the unmanned aerial vehicle is shot by a visible light shooting device at present, an environment color temperature value and a high-resolution image color temperature value are obtained, a brightness parameter value in an image HSV (hue, saturation and value) model is obtained, and whether the shooting mode is switched or not is determined by a threshold comparison method;
when the shooting mode needs to be switched, switching the mode of shooting by the current visible light shooting device into the mode of shooting by the infrared light shooting device;
when the unmanned aerial vehicle is in a daytime flight mode, if an infrared light shooting device is adopted for shooting at present, an environment color temperature value is obtained, and whether the shooting mode is switched or not is determined through a threshold comparison method;
when the shooting mode needs to be switched, the mode of shooting by the current infrared light shooting device is switched to the mode of shooting by the visible light shooting device.
2. The system of claim 1, wherein the drone camera includes a visible light camera and an infrared light camera.
3. The system of claim 1, wherein the unmanned aerial vehicle target recognition module recognizes a tracking target in the image, and specifically comprises:
acquiring three-dimensional space relative coordinates (x, y, z) of the unmanned aerial vehicle relative to the target;
acquiring a target image under the relative coordinate position visual angle from an unmanned aerial vehicle target object three-dimensional image library, wherein the pixel matrix size of the target image is n x n;
and performing target search in a central area with the pixel matrix of the high-resolution image as m by adopting the following algorithm:
taking the central point of the high-resolution image as the central point of the m-m central area, and taking the central point coordinate as an origin coordinate (0, 0); the target recognition is carried out according to the following steps:
s1: in that
Performing target similarity matching in a square area serving as coordinates of the upper left corner and the lower right corner;
s2 at
Performing target similarity matching in the square area serving as the coordinates of the upper right corner and the lower left corner;
s3 at
Performing target similarity matching in a square area serving as coordinates of the lower left corner and the upper right corner;
s4 at
Performing target similarity matching in a square area serving as coordinates of a lower right corner and an upper left corner;
s5 is in
Performing target similarity matching in a square area serving as coordinates of the upper left corner and the lower right corner;
wherein m is 16 × n;
s6, when the similarity obtained by calculation at the current square area position is larger than a preset threshold value DpThen, using the position center of the current square area as the center, reducing m to half of the original value to obtain a new m value, and repeating the above steps in the square area with the new m value as the side lengthSteps S1-S6;
s7: and when m is equal to n, finishing the algorithm, and obtaining the current square area image which is the target image.
4. The system according to claim 3, characterized in that three-dimensional relative coordinates (x, y, z) of the drone with respect to the target are acquired, and in that the images of the target are acquired in the library of three-dimensional images of the drone target at the positions of said relative coordinates, in particular:
storing three-dimensional image data of a target in an unmanned aerial vehicle database in advance;
taking the target as a coordinate origin (0,0,0), and acquiring a three-dimensional space relative coordinate (x, y, z) of the unmanned aerial vehicle relative to the target;
calculating a three-dimensional visual angle of the unmanned aerial vehicle relative to the target;
acquiring a target image under the three-dimensional visual angle from a database;
and adjusting the size of the pixel matrix of the acquired target image under the three-dimensional visual angle according to the relative distance between the unmanned aerial vehicle and the target so as to obtain the target image with the matrix size of n x n.
5. The system of claim 1, wherein the target tracking module is configured to track the target in real time, draw a target motion trajectory, and form a target movement log, and specifically includes:
storing the motion trail of the target and the motion posture of the target to form a target movement log;
when a blocking object blocks the target or the target is not identified in the high-resolution image, predicting the position of the target at the current moment and the relative angle between the target and the unmanned aerial vehicle according to the historical motion track and the motion attitude of the target;
acquiring a predicted target position and a target image of the unmanned aerial vehicle and the target at a predicted relative coordinate view angle from an unmanned aerial vehicle database;
and fading the shelters in the image, and displaying the image of the target under the relative coordinate viewing angle on the faded shelters.
6. The system of claim 5, wherein the target display module implements a clear display of the tracked target, and specifically comprises:
when a target image is identified in the image, the target image under the relative coordinate view angle acquired in the unmanned aerial vehicle database and the target image identified in the image are displayed in an overlapping mode;
when the target image is not identified in the image, the target image at the perspective of the predicted relative coordinates acquired in the drone database is displayed on the obstruction.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110722945.4A CN113536984B (en) | 2021-06-28 | 2021-06-28 | Image target identification and tracking system based on unmanned aerial vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110722945.4A CN113536984B (en) | 2021-06-28 | 2021-06-28 | Image target identification and tracking system based on unmanned aerial vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113536984A CN113536984A (en) | 2021-10-22 |
| CN113536984B true CN113536984B (en) | 2022-04-26 |
Family
ID=78126143
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110722945.4A Active CN113536984B (en) | 2021-06-28 | 2021-06-28 | Image target identification and tracking system based on unmanned aerial vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113536984B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114281096A (en) * | 2021-11-09 | 2022-04-05 | 中时讯通信建设有限公司 | Unmanned aerial vehicle tracking control method, device and medium based on target detection algorithm |
| CN114384052A (en) * | 2021-12-22 | 2022-04-22 | 重庆盾银科技有限公司 | Tracking imaging system and imaging method |
| CN115297351B (en) * | 2022-08-03 | 2023-11-17 | 抖音视界有限公司 | Panoramic video playing method and device, storage medium and electronic equipment |
| CN116091959B (en) * | 2022-11-21 | 2024-03-22 | 武汉坤达安信息安全技术有限公司 | Double-light linkage identification method and device based on all-weather smoke and fire |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7113619B1 (en) * | 1999-09-07 | 2006-09-26 | Fuji Photo Film Co., Ltd. | Image reading method, image reading apparatus and method of discriminating defect of image data |
| CN201498915U (en) * | 2009-07-02 | 2010-06-02 | 浙江省电力公司 | Carrier operation platform of helicopter polling system |
| CN106274617A (en) * | 2016-08-26 | 2017-01-04 | 湖南航天远望科技有限公司 | Ship, machine combination monitoring method and monitoring system |
| CN110428008A (en) * | 2019-08-02 | 2019-11-08 | 深圳市唯特视科技有限公司 | A kind of target detection and identification device and method based on more merge sensors |
Family Cites Families (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9814446B2 (en) * | 2015-04-22 | 2017-11-14 | Siemens Medical Solutions Usa, Inc. | Method and system for automatic estimation of shear modulus and viscosity from shear wave imaging |
| CN107026967A (en) * | 2016-02-01 | 2017-08-08 | 杭州海康威视数字技术股份有限公司 | A kind of camera operation mode switching method and device |
| CN109952812B (en) * | 2016-09-14 | 2022-03-01 | 路创技术有限责任公司 | Lighting system for controlling color temperature as a function of brightness |
| CN108121358B (en) * | 2017-08-21 | 2020-08-28 | 中国人民解放军陆军工程大学 | Unmanned aerial vehicle control method |
| CN115620545A (en) * | 2017-08-24 | 2023-01-17 | 北京三星通信技术研究有限公司 | Augmented reality method and device for driving assistance |
| CN108093183B (en) * | 2018-02-11 | 2020-10-23 | 普联技术有限公司 | Camera day and night mode switching method and terminal equipment |
| CN108759837A (en) * | 2018-05-22 | 2018-11-06 | 北京和协导航科技有限公司 | Unmanned plane multi computer communication combat system and method |
| CN108919819B (en) * | 2018-05-22 | 2023-10-27 | 北京和协导航科技有限公司 | Unmanned aerial vehicle navigation communication integrated system and method |
| US11740630B2 (en) * | 2018-06-12 | 2023-08-29 | Skydio, Inc. | Fitness and sports applications for an autonomous unmanned aerial vehicle |
| CN110603535B (en) * | 2019-07-29 | 2023-02-28 | 香港应用科技研究院有限公司 | Iterative multi-directional image search supporting large template matching |
| CN211055366U (en) * | 2019-09-27 | 2020-07-21 | 南昌航空大学 | Campus patrol system of rotor unmanned aerial vehicle based on visual identification |
| CN110796686B (en) * | 2019-10-29 | 2022-08-09 | 浙江大华技术股份有限公司 | Target tracking method and device and storage device |
| CN111103608A (en) * | 2020-01-02 | 2020-05-05 | 东南大学 | Positioning device and method used in forestry surveying work |
| CN111901563A (en) * | 2020-07-21 | 2020-11-06 | 河南中光学集团有限公司 | Multifunctional intelligent monitoring system and monitoring method |
-
2021
- 2021-06-28 CN CN202110722945.4A patent/CN113536984B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7113619B1 (en) * | 1999-09-07 | 2006-09-26 | Fuji Photo Film Co., Ltd. | Image reading method, image reading apparatus and method of discriminating defect of image data |
| CN201498915U (en) * | 2009-07-02 | 2010-06-02 | 浙江省电力公司 | Carrier operation platform of helicopter polling system |
| CN106274617A (en) * | 2016-08-26 | 2017-01-04 | 湖南航天远望科技有限公司 | Ship, machine combination monitoring method and monitoring system |
| CN110428008A (en) * | 2019-08-02 | 2019-11-08 | 深圳市唯特视科技有限公司 | A kind of target detection and identification device and method based on more merge sensors |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113536984A (en) | 2021-10-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113536984B (en) | Image target identification and tracking system based on unmanned aerial vehicle | |
| CN109151439B (en) | Automatic tracking shooting system and method based on vision | |
| US10953545B2 (en) | System and method for autonomous navigation using visual sparse map | |
| CN106981073B (en) | A kind of ground moving object method for real time tracking and system based on unmanned plane | |
| CN111583136A (en) | Method for simultaneously positioning and establishing image of autonomous mobile platform in rescue scene | |
| CN106973221B (en) | Unmanned aerial vehicle camera shooting method and system based on aesthetic evaluation | |
| CN112207821B (en) | Target searching method of visual robot and robot | |
| CN111474953A (en) | Multi-dynamic-view-angle-coordinated aerial target identification method and system | |
| CN109483507B (en) | Indoor visual positioning method for walking of multiple wheeled robots | |
| CN112927264B (en) | Unmanned aerial vehicle tracking shooting system and RGBD tracking method thereof | |
| CN111338382A (en) | Unmanned aerial vehicle path planning method guided by safety situation | |
| CN111612823A (en) | Robot autonomous tracking method based on vision | |
| Civera et al. | Drift-free real-time sequential mosaicing | |
| CN113486697A (en) | Forest smoke and fire monitoring method based on space-based multi-modal image fusion | |
| CN111780744A (en) | Mobile robot hybrid navigation method, equipment and storage device | |
| CN118334085A (en) | Unmanned aerial vehicle target tracking method and system based on improved machine learning | |
| CN114429435A (en) | Wide-field-of-view range target searching device, system and method in degraded visual environment | |
| CN114022562A (en) | Panoramic video stitching method and device capable of keeping integrity of pedestrians | |
| CN108122243B (en) | Method for robot to detect moving object | |
| Yagi et al. | Route representation for mobile robot navigation by omnidirectional route panorama Fourier transformation | |
| CN113776540B (en) | Control method for vehicle-mounted tethered unmanned aerial vehicle to track moving vehicle in real time based on visual navigation positioning | |
| CN113438399B (en) | Target guidance system, method for unmanned aerial vehicle, and storage medium | |
| WO2022088072A1 (en) | Visual tracking method and apparatus, movable platform, and computer-readable storage medium | |
| Vámossy et al. | PAL Based Localization Using Pyramidal Lucas-Kanade Feature Tracker | |
| WO2020172878A1 (en) | Method and device for shooting and aiming control of movable platform, and readable storage medium |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |