CN114882120A - Ocean structure swaying measurement system and method based on binocular image processing - Google Patents

Ocean structure swaying measurement system and method based on binocular image processing Download PDF

Info

Publication number
CN114882120A
CN114882120A CN202210519388.0A CN202210519388A CN114882120A CN 114882120 A CN114882120 A CN 114882120A CN 202210519388 A CN202210519388 A CN 202210519388A CN 114882120 A CN114882120 A CN 114882120A
Authority
CN
China
Prior art keywords
camera
binocular
swaying
water surface
marine structure
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202210519388.0A
Other languages
Chinese (zh)
Inventor
张兵华
邓涛
魏汉迪
肖龙飞
金茂瑞
史东亚
田新亮
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Mairun Intelligent Technology Shanghai Co ltd
Shanghai Jiao Tong University
Original Assignee
Mairun Intelligent Technology Shanghai Co ltd
Shanghai Jiao Tong University
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Mairun Intelligent Technology Shanghai Co ltd, Shanghai Jiao Tong University filed Critical Mairun Intelligent Technology Shanghai Co ltd
Priority to CN202210519388.0A priority Critical patent/CN114882120A/en
Publication of CN114882120A publication Critical patent/CN114882120A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/80Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical techniques
    • G01B11/22Measuring arrangements characterised by the use of optical techniques for measuring depth
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01HMEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H9/00Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by using radiation-sensitive means, e.g. optical means
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/80Geometric correction
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/50Depth or shape recovery
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74Image or video pattern matching; Proximity measures in feature spaces
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02ATECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/30Assessment of water resources

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
  • Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Databases & Information Systems (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Multimedia (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

本发明提供一种基于双目图像处理的海洋结构物摇荡测量系统及方法,其中系统包括一双目相机、一海洋结构物摇荡测量系统PC端和一支撑平台;所述支撑平台固定在一船舶的舷侧且正对所述舷侧的外侧设置,所述双目相机固定在所述支撑平台上;所述双目相机与所述海洋结构物摇荡测量系统PC端通信连接。本发明的一种基于双目图像处理的海洋结构物摇荡测量系统及方法,用于在海洋实测的风浪条件下,通过双目相机还原波浪真实的深度信息,进而拟合得到平均水面,再以双目相机相对平均水面的位置得到海洋结构物的摇荡。

Figure 202210519388

The present invention provides a system and method for swaying measurement of marine structures based on binocular image processing, wherein the system includes a binocular camera, a PC end of a swaying measurement system for marine structures, and a support platform; the support platform is fixed on a ship The side of the ship is disposed facing the outer side of the side, the binocular camera is fixed on the support platform; the binocular camera is communicatively connected with the PC terminal of the marine structure swaying measurement system. A system and method for measuring the sway of marine structures based on binocular image processing of the present invention are used to restore the real depth information of waves through binocular cameras under the conditions of wind and waves measured in the ocean, and then fit to obtain the average water surface, and then use the binocular camera to restore the real depth information of waves. The position of the binocular camera relative to the mean water surface results in the shaking of marine structures.

Figure 202210519388

Description

Ocean structure swaying measurement system and method based on binocular image processing
Technical Field
The invention relates to the field of situation perception of marine structures, in particular to a binocular image processing-based marine structure swaying measurement system and method.
Background
In recent years, with the rapid development of technologies such as electronic information, automatic control, artificial intelligence and the like, the research of unmanned ships and aircrafts is gradually maturing, and great application prospects are shown. Unmanned ships and craft with intelligent navigation ability are core components of future intelligent navigation network, and will play an important role in ocean engineering. Wherein the motion perception of the marine structure plays an important role in the safe operation and unmanned control of the marine structure.
The shaking of the marine structure comprises pitching and rolling, the current sensing mode mainly comprises the steps that sensors such as an inertia measuring unit are fixed on a certain plane of the floating body, and the shaking of the floating body is measured through the inclination of the measuring plane. However, the conventional measurement method has great limitations:
a. due to the fact that the sizes of structures such as ships are large, the structures can generate large deformation when the structures navigate in waves, the inclination of each plane of the floating body is inconsistent with the shaking of the floating body, sensors such as an inertia measurement unit estimate the shaking of the floating body by measuring the inclination of a certain point, and accordingly the deformation of the floating body has large influence on a measurement result.
b. The application field has larger limitation. Sensor devices such as inertial measurement units are expensive and, due to the above-mentioned disadvantages, a plurality of such devices need to be arranged on the floating body, which requires a large communication overhead.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a binocular image processing-based marine structure sway measuring system and method, which are used for restoring the real depth information of waves by using a binocular camera under the condition of actually measured wind waves of the sea, further fitting to obtain an average water surface, and then obtaining the sway of the marine structure by using the position of the binocular camera relative to the average water surface.
In order to achieve the aim, the invention provides a binocular image processing-based marine structure sway measuring system, which comprises a binocular camera, a PC end of the marine structure sway measuring system and a supporting platform, wherein the PC end is connected with the binocular camera; the support platform is fixed on a side of a ship and is arranged opposite to the outer side of the side, and the binocular camera is fixed on the support platform; and the binocular camera is in communication connection with the PC end of the marine structure swaying measurement system.
Preferably, the binocular camera comprises two camera unit assemblies fixed on the support platform; the two camera unit components are positioned at the same height.
The invention relates to a binocular image processing ocean structure swaying measurement method, which comprises the following steps:
s1: the binocular camera transmits the acquired wave images to the PC end of the marine structure swaying measurement system;
s2: the PC end of the marine structure oscillation measuring system processes the wave image in real time;
the step of S2 further includes the steps of:
s21: carrying out binocular calibration on the wave image;
s22: performing stereo correction on the current wave image;
s23: carrying out stereo matching on the current wave image;
s24: calculating the depth information of the current wave image;
s25: calculating world coordinates of the characteristic points of the wave image;
s26: fitting the characteristic points of the current wave image to obtain an average water surface;
s27: the swaying of the marine structure is measured.
Preferably, the wave image collected by the binocular camera is restored to real depth information by the PC end of the marine structure swaying measurement system through an average wave surface based on binocular vision and a ship situation measurement algorithm, an average water surface is obtained through fitting, and the swaying of the marine structure is obtained according to the position of the binocular camera relative to the average water surface.
Preferably, in the step S23:
comparing the wave images shot by the two camera unit assemblies of the binocular camera, matching the same pixel blocks in the wave images, finding corresponding feature points, and calculating parallax disparity:
disparity=X R -X T
wherein X R And X T Is the column coordinate of the imaging point of the feature point on the photoreceptors of the two camera unit assemblies.
Preferably, in the step S24:
after the parallax is obtained, the real distance Z between the point P and the optical center of the camera can be obtained by applying the principle of triangulation:
Figure BDA0003642643040000031
wherein f is the focal length of the camera, and B is the center-to-center distance between the two camera unit components.
Preferably, in the step S25:
conversion relationship using camera coordinate system:
Figure BDA0003642643040000032
and obtaining world coordinates (X, Y, Z) of the characteristic points.
Wherein Z c The coordinates of the camera are u and v, the coordinates of the pixel are dx and dy, which are intrinsic parameters of the camera and respectively represent how many millimeters each pixel occupies in the x and y directions, f is the focal length of the camera, R is a rotation matrix, t is a displacement matrix, and X, Y, Z is the coordinate value of the world coordinate.
Preferably, in the step S26:
in the camera coordinate system, the average water surface equation is expressed as:
z m =[α 1 α 2 α 3 ][x m y m 1] T
wherein [ x ] m ,y m ,z m ]Is the coordinate of each feature point on the average water surface relative to the camera coordinate system, z m Also known as mean water depth; alpha is alpha i Is the coefficient of the plane of the mean water surface, provided that the depths of a sufficient number of characteristic points, alpha, on the wave surface are known i Can be obtained by least square fitting;
and after an equation expression of the average water surface is obtained, a depth map of the average water surface is further obtained.
Preferably, in the step S27:
obtaining the normal vector of the average water surface according to the average water surface equation
Figure BDA0003642643040000033
The roll angle of the marine structure may be determined by the camera's vector along the optical axis
Figure BDA0003642643040000034
Normal vector to mean water surface
Figure BDA0003642643040000035
The pitch angle can be obtained from the vector of the camera along the x-axis direction of the camera coordinate system
Figure BDA0003642643040000036
Normal vector to mean water surface
Figure BDA0003642643040000037
The included angle between the two is obtained, and the swaying of the ocean structure is obtained.
Due to the adoption of the technical scheme, the invention has the following beneficial effects:
1. and (4) introducing binocular image processing into ocean structure swing measurement of ocean actual measurement. Due to the fact that the sizes of structures such as ships are large, the structures can generate large deformation when the structures navigate in waves, the inclination of each plane of the floating body is inconsistent with the shaking of the floating body, sensors such as an inertia measurement unit estimate the shaking of the floating body by measuring the inclination of a certain point, and accordingly the deformation of the floating body has large influence on a measurement result. However, the binocular image processing-based sea structure swaying measurement system can restore the real depth information of waves through the binocular camera, further fit to obtain the average water surface, and then obtain the swaying of the sea structure according to the position of the binocular camera relative to the average water surface to avoid the problem.
2. Has wide application field. In comparison, sensor devices such as an inertial measurement unit are expensive, and the application field is limited greatly, so that a plurality of floating bodies need to be arranged, and a large communication overhead is required. The ocean structure oscillation measuring system based on binocular image processing can be suitable for various non-extreme sea conditions, is low in cost and can be carried on ships, unmanned aerial vehicles and other equipment.
3. The binocular vision-based average wave surface and ship situation measurement algorithm is used for processing the binocular images, and the method has the advantages of being high in speed, high in precision and real-time.
Drawings
Fig. 1 and fig. 2 are schematic structural diagrams of a marine structure swaying measurement system based on binocular image processing according to an embodiment of the invention;
fig. 3 is a flowchart of the marine structure sway measurement based on binocular image processing according to the embodiment of the present invention.
Fig. 4 is a schematic coordinate system diagram of a binocular camera according to an embodiment of the invention.
Detailed Description
The following description of the preferred embodiments of the present invention will be provided in conjunction with the accompanying drawings, which are set forth in the accompanying drawings and figures 1-4, to provide a better understanding of the function and features of the invention.
Referring to fig. 1 to 4, an ocean structure swaying measurement system based on binocular image processing according to an embodiment of the present invention includes a binocular camera 1, a PC end of the ocean structure swaying measurement system, and a support platform; the support platform is fixed on the side of a ship 2 and is arranged opposite to the outer side of the side, and the binocular camera 1 is fixed on the support platform; the binocular camera 1 is in communication connection with a PC end of the marine structure swaying measurement system.
The binocular camera 1 comprises two camera unit components fixed on a supporting platform; the two camera unit components are located at the same height.
The image obtained by the binocular camera 1 is transmitted to the PC end of the marine structure swaying measurement system through a network cable.
The PC end of the marine structure swaying measurement system runs an average wave surface and ship situation measurement algorithm program based on binocular vision, wave images of the sea level 3 collected by the binocular camera 1 can be processed in real time and fitted to obtain an average water surface, and swaying of the marine structure is obtained according to the position of the binocular camera 1 relative to the average water surface.
The invention uses a binocular image processing method to measure the swaying of marine structures, and the core algorithm based on the binocular image processing method is an average wave surface and ship situation measuring algorithm based on binocular vision. After the binocular device is built, an average wave surface based on binocular vision and a ship situation measuring program are operated to measure the swaying of the marine structure.
The binocular image processing ocean structure swaying measurement method comprises the following steps:
s1: the binocular camera 1 transmits the collected wave images to a PC end of the marine structure swaying measurement system;
s2: the PC end of the marine structure oscillation measurement system processes the wave image in real time;
the step of S2 further includes the steps of:
s21: carrying out binocular calibration on the wave image;
for the left and right two lenses of the binocular camera 1Respectively calibrating to obtain the internal reference, external reference and distortion coefficient of the left and right lenses, wherein the internal reference comprises the focal length f of the left and right lenses x ,f y Offset C of the lens optical axis in the image coordinate system x ,C y The external parameter comprises a rotation matrix R and a translation vector t of the left lens relative to the right lens, and the distortion coefficient comprises a radial distortion coefficient k 1 ,k 2 ,k 3 And tangential distortion coefficient p 1 ,p 2
S22: performing stereo correction on the current wave image;
the purpose of stereo correction is to perform mathematical projection transformation on the left view and the right view shot in the same scene, so that two imaging planes are parallel to a base line, and the same point is located in the same line in the left view and the right view, which are called coplanar line alignment for short. The distance can be calculated using trigonometric principles only after alignment of the coplanar rows is achieved.
S23: carrying out stereo matching on the current wave image;
comparing wave images shot by two camera unit components of the binocular camera 1, matching the same color blocks in the wave images, finding corresponding feature points, and calculating parallax disparity:
disparity=X R -X T
wherein X R And X T Is the column coordinate of the imaged point of the feature point on the photoreceptors of the two camera unit assemblies.
S24: calculating the depth information of the current wave image;
after the parallax is obtained, the real distance Z between the point P and the optical center of the camera can be obtained by applying the principle of trigonometry:
Figure BDA0003642643040000061
wherein f is the focal length of the camera, and B is the center distance of the two camera unit components.
S25: calculating world coordinates of the characteristic points of the wave image;
after the feature points are found by matching the pixel blocks in S23, the pixel coordinates corresponding to each feature point and the depth information of each feature point in S24 are obtained simultaneously using the transformation relationship of the camera coordinate system:
Figure BDA0003642643040000062
world coordinates (X, Y, Z) of the feature points are obtained.
Wherein Z c The coordinates of the camera are u and v, the coordinates of the pixel are dx and dy, which are intrinsic parameters of the camera and respectively represent how many millimeters each pixel occupies in the x and y directions, f is the focal length of the camera, R is a rotation matrix, t is a displacement matrix, and X, Y, Z is the coordinate value of the world coordinate.
S26: fitting the characteristic points of the current wave image to obtain an average water surface;
in the camera coordinate system, the plane of the average water surface can be represented mathematically by a three-dimensional plane, and the equation is as follows:
z m =[α 1 α 2 α 3 ][x m y m 1] T
wherein [ x ] m ,y m ,z m ]Is the coordinate of each feature point on the average water surface relative to the camera coordinate system, z m Also known as mean water depth; alpha is alpha i Is the coefficient of the plane of the mean water surface, provided that the depths of a sufficient number of characteristic points, alpha, on the wave surface are known i Can be obtained by least square fitting;
and after an equation expression of the average water surface is obtained, a depth map of the average water surface is further obtained.
S27: the swaying of the marine structure is measured.
According to the mean water surface equation z m =[α 1 α 2 α 3 ][x m y m 1] T
Normal vector of average water surface can be obtained
Figure BDA0003642643040000063
The roll angle of the marine structure may be determined by the camera's vector along the optical axis (z-axis)
Figure BDA0003642643040000071
Normal vector to mean water surface
Figure BDA0003642643040000072
The pitch angle can be obtained from the vector of the camera along the x-axis direction of the camera coordinate system
Figure BDA0003642643040000073
Normal vector to mean water surface
Figure BDA0003642643040000074
The included angle between the two is obtained, and the swaying of the marine structure is obtained.
While the present invention has been described in detail and with reference to the embodiments thereof as illustrated in the accompanying drawings, it will be apparent to one skilled in the art that various changes and modifications can be made therein. Therefore, certain details of the embodiments are not to be interpreted as limiting, and the scope of the invention is to be determined by the appended claims.

Claims (9)

1. A marine structure swaying measurement system based on binocular image processing is characterized by comprising a binocular camera, a PC end of the marine structure swaying measurement system and a supporting platform; the support platform is fixed on a side of a ship and is arranged opposite to the outer side of the side, and the binocular camera is fixed on the support platform; and the binocular camera is in communication connection with the PC end of the marine structure swaying measurement system.
2. The binocular image processing based marine structure sway measurement system of claim 1, wherein the binocular camera comprises two camera unit assemblies fixed to the support platform; the two camera unit components are positioned at the same height.
3. A binocular image processing ocean structure swaying measurement method comprises the following steps:
s1: a binocular camera transmits the collected wave image to a PC end of an ocean structure swaying measurement system;
s2: the PC end of the marine structure oscillation measuring system processes the wave image in real time;
the step of S2 further includes the steps of:
s21: carrying out binocular calibration on the wave image;
s22: performing stereo correction on the current wave image;
s23: carrying out stereo matching on the current wave image;
s24: calculating the depth information of the current wave image;
s25: calculating world coordinates of the characteristic points of the wave image;
s26: fitting the characteristic points of the current wave image to obtain an average water surface;
s27: the swaying of the marine structure is measured.
4. The binocular image processing sea structure swaying measurement method according to claim 3, characterized in that the wave images collected by the PC end of the sea structure swaying measurement system by the binocular camera are restored to real depth information by an average wave surface based on binocular vision and a ship posture measurement algorithm, then an average water surface is obtained by fitting, and the swaying of the sea structure is obtained by the position of the binocular camera relative to the average water surface.
5. The binocular image processed marine structure swaying measurement method according to claim 3, wherein in the step of S23:
comparing the wave images shot by the two camera unit assemblies of the binocular camera, matching the same color blocks in the wave images, finding corresponding feature points, and calculating parallax disparity:
disparity=X R -X T
wherein X R And X T Is the column coordinate of the imaging point of the feature point on the photoreceptors of the two camera unit assemblies.
6. The binocular image processed marine structure swaying measurement method according to claim 5, wherein in the step of S24:
after the parallax is obtained, the real distance Z between the point P and the optical center of the camera can be obtained by applying the principle of triangulation:
Figure FDA0003642643030000021
wherein f is the focal length of the camera, and B is the center-to-center distance between the two camera unit components.
7. The binocular image processed marine structure swaying measurement method according to claim 6, wherein in the step of S25:
conversion relationship using camera coordinate system:
Figure FDA0003642643030000022
and obtaining world coordinates (X, Y, Z) of the characteristic points.
Wherein Z c The coordinates of the camera are u and v, the coordinates of the pixel are dx and dy, which are intrinsic parameters of the camera and respectively represent how many millimeters each pixel occupies in the x and y directions, f is the focal length of the camera, R is a rotation matrix, t is a displacement matrix, and X, Y, Z is the coordinate value of the world coordinate.
8. The binocular image-processed marine structure sway measuring method of claim 7, wherein in said step of S26:
in the camera coordinate system, the average water surface equation is expressed as:
z m =[α 1 α 2 α 3 ][x m y m 1] T
wherein [ x ] m ,y m ,z m ]Is the phase of each characteristic point on the average water surfaceFor the coordinates of the camera coordinate system, z m Also known as mean water depth; alpha is alpha i Is the coefficient of the plane of the mean water surface, provided that the depths of a sufficient number of characteristic points, alpha, on the wave surface are known i Can be obtained by least square fitting;
and after an equation expression of the average water surface is obtained, a depth map of the average water surface is further obtained.
9. The binocular image processed marine structure swaying measurement method according to claim 8, wherein in the step of S27:
obtaining the normal vector of the average water surface according to the average water surface equation
Figure FDA0003642643030000031
The roll angle of the marine structure may be determined by the camera's vector along the optical axis
Figure FDA0003642643030000032
Normal vector to mean water surface
Figure FDA0003642643030000033
The pitch angle can be obtained from the vector of the camera along the x-axis direction of the camera coordinate system
Figure FDA0003642643030000034
Normal vector to mean water surface
Figure FDA0003642643030000035
The included angle between the two is obtained, and the swaying of the ocean structure is obtained.
CN202210519388.0A 2022-05-13 2022-05-13 Ocean structure swaying measurement system and method based on binocular image processing Pending CN114882120A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210519388.0A CN114882120A (en) 2022-05-13 2022-05-13 Ocean structure swaying measurement system and method based on binocular image processing

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210519388.0A CN114882120A (en) 2022-05-13 2022-05-13 Ocean structure swaying measurement system and method based on binocular image processing

Publications (1)

Publication Number Publication Date
CN114882120A true CN114882120A (en) 2022-08-09

Family

ID=82675981

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210519388.0A Pending CN114882120A (en) 2022-05-13 2022-05-13 Ocean structure swaying measurement system and method based on binocular image processing

Country Status (1)

Country Link
CN (1) CN114882120A (en)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110473260A (en) * 2019-06-28 2019-11-19 国家海洋技术中心 A kind of wave video measuring device and method
CN110763189A (en) * 2019-10-15 2020-02-07 哈尔滨工程大学 Sea wave elevation measurement experimental device and method based on binocular vision
CN111829435A (en) * 2019-08-27 2020-10-27 北京伟景智能科技有限公司 Multi-binocular camera and line laser cooperative detection method
CN113483730A (en) * 2021-07-02 2021-10-08 迈润智能科技(上海)有限公司 Marine wave actual measurement device and method based on binocular stereo vision
US20210394883A1 (en) * 2020-06-17 2021-12-23 Yamaha Hatsudoki Kabushiki Kaisha Hull behavior control system and marine vessel

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110473260A (en) * 2019-06-28 2019-11-19 国家海洋技术中心 A kind of wave video measuring device and method
CN111829435A (en) * 2019-08-27 2020-10-27 北京伟景智能科技有限公司 Multi-binocular camera and line laser cooperative detection method
CN110763189A (en) * 2019-10-15 2020-02-07 哈尔滨工程大学 Sea wave elevation measurement experimental device and method based on binocular vision
US20210394883A1 (en) * 2020-06-17 2021-12-23 Yamaha Hatsudoki Kabushiki Kaisha Hull behavior control system and marine vessel
CN113483730A (en) * 2021-07-02 2021-10-08 迈润智能科技(上海)有限公司 Marine wave actual measurement device and method based on binocular stereo vision

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
李汪讳等: "水下爆炸兴波及其对结构物作用问题的数值模拟", 水动力学研究与进展A辑, no. 06, 15 November 2010 (2010-11-15) *
王珍珍: ""基于双目视觉的海浪参数观测技术研究"", 《CNKI优秀硕士学位论文全文库》, no. 4, 15 April 2022 (2022-04-15), pages 5 - 11 *
田福庆等: "《舰载激光武器跟踪与瞄准控制》", 30 April 2015, 国防工业出版社, pages: 52 - 53 *

Similar Documents

Publication Publication Date Title
CN111462236A (en) A method and system for detecting relative pose between ships
CN111750853B (en) Map establishing method, device and storage medium
CN106960454B (en) Depth of field obstacle avoidance method and equipment and unmanned aerial vehicle
CN110470226A (en) A kind of bridge structure displacement measurement method based on UAV system
CN111091076B (en) Measurement method of tunnel boundary data based on stereo vision
JPH11230745A (en) Altitude measurement device
CN114112297B (en) Vision-based on-ship sea wave observation device and method
JP2025534947A (en) 3D reconstruction method for underwater damage of marine equipment based on fusion of vision and IMU
CN111524174A (en) Binocular vision three-dimensional construction method for moving target of moving platform
CN111307046B (en) Tree height measuring method based on hemispherical image
CN116977445B (en) Ocean column pile attitude detection method based on dynamic binocular vision
CN113483730A (en) Marine wave actual measurement device and method based on binocular stereo vision
CN113177918A (en) Intelligent and accurate inspection method and system for electric power tower by unmanned aerial vehicle
CN103929635B (en) Binocular vision image compensation method when a kind of UUV shakes in length and breadth
CN112461213B (en) Multi-mode wave monitoring device and monitoring method
CN118691997A (en) A method for constructing ship berthing and unberthing scene maps based on stereoscopic perception
CN118967795A (en) Visual inertial navigation tightly coupled SLAM method based on four panoramic cameras
CN111105467A (en) Image calibration method and device and electronic equipment
JP4132068B2 (en) Image processing apparatus, three-dimensional measuring apparatus, and program for image processing apparatus
CN113483739B (en) Offshore target position measuring method
CN114882120A (en) Ocean structure swaying measurement system and method based on binocular image processing
CN115876099A (en) Ship height measuring system based on inclination early warning type wide-range binocular camera
CN114463444A (en) Non-contact type relative pose detection method and system
CN113340272A (en) Ground target real-time positioning method based on micro-group of unmanned aerial vehicle
CN114663486A (en) Building height measurement method and system based on binocular vision

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
RJ01 Rejection of invention patent application after publication

Application publication date: 20220809

RJ01 Rejection of invention patent application after publication