CN114615410B - Natural disaster panoramic helmet and shooting gesture determining method for images of natural disaster panoramic helmet - Google Patents

Abstract

The present application relates to the technical field of photographing images, in particular to a natural disaster panoramic helmet and a method for determining the photographing attitude of its images, and a computer storage medium, which includes a helmet body, a panoramic fisheye camera installed on the top of the helmet body, and a The magnetometer and data processing system in the helmet body, the panoramic fisheye camera is used for fisheye images at different times; the magnetometer is used to obtain the spatial information of the helmet at different times, and the data processing system acquires images in different directions at different times , and extract matching feature points on images at different moments; and obtain the roll angle and pitch angle according to the positional relationship of the matched feature points at different moments; determine the variation of shooting attitude according to the roll angle and pitch angle. The application has the effect of facilitating operators to scan natural resources in a specific environment, and at the same time, take pictures of natural disasters in a fixed posture for scanning and recording.

Description

A natural disaster panoramic helmet and its image shooting attitude determination method

technical field

The present application relates to the technical field of photographing images, in particular to a natural disaster panoramic helmet and a method for determining the photographing posture of the image thereof.

Background technique

Natural disaster scanning is the use of various measurement methods to observe and monitor the dynamic changes of factors related to the whole process of natural disaster breeding, occurrence, development and fatal damage. , in-progress, and post-occurrence state of the target area.

In related technologies, manual inspections or unmanned aerial vehicle inspections are mainly used for natural disaster scanning. Manual inspections use tablet computers, GPS and other equipment to take photos at fixed points. This method is not only inefficient, but also easy to miss inspection points. It is also difficult to verify the location of the inspection; UAV inspections require various sensing devices and acquisition equipment on the UAV, which is limited by the maximum load of the UAV. Expensive, unable to perform long-term, large-scale natural disaster censuses in natural areas. In addition, manned/unmanned vehicle inspection systems are also widely used, but the vehicle system is limited by road conditions and is not suitable for natural disaster surveys in natural areas with poor road conditions such as mountainous areas and woodlands.

Contents of the invention

In order to facilitate operators to scan natural resources in a specific environment, and at the same time take photos of natural disasters in a fixed posture for scanning records, this application provides a method for determining the shooting posture of a natural disaster panoramic helmet and its images.

In the first aspect, a natural disaster scanning helmet provided by the application adopts the following technical scheme:

A natural disaster scanning helmet, the helmet includes: a helmet body, a panoramic fisheye camera arranged on the top of the helmet body, and a magnetometer and a data processing system arranged in the helmet body; the panoramic fisheye The camera and the magnetometer are respectively electrically connected to the data processing system, wherein,

The panoramic fisheye camera is used to acquire the first fisheye image at t1 moment and the second fisheye image at t2 moment;

The magnetometer is configured to acquire first spatial information of the helmet at time t1 and second spatial information of the helmet at time t2, wherein the first spatial information includes orientation information of the helmet at time t1, and the The second spatial information includes the orientation information of the helmet at time t2;

The data processing system is configured to acquire a first center image and a first side image according to the first fisheye image, the first center image is a projection of the first fisheye image along a preset orientation, the The first side image is the projection of the first fisheye image along the orthogonal direction of the preset orientation;

The data processing system is further configured to acquire a second center image and a second side image according to the second fisheye image, the second center image is a projection of the second fisheye image along a preset orientation, so The second side image is the projection of the second fisheye image along the orthogonal direction of the preset orientation;

The data processing system is further configured to extract at least two first feature points on the first center image and the first side image respectively; and on the second center image and the second side image extracting at least two second feature points respectively matching the at least two first feature points;

The data processing system is further configured to obtain a roll angle according to the positional relationship between the first feature point on the first center image and the second feature point on the second center image; according to the first side image Obtain the pitch angle from the positional relationship between the first feature point on the image and the second feature point on the second side image; and determine the variation of the shooting attitude at time t2 relative to time t1 according to the roll angle and pitch angle.

In the second aspect, the application provides a method for determining the shooting posture of a natural disaster scanning image, which adopts the following technical solution:

A method for determining the shooting attitude of natural disaster scanning images, which is applied to natural disaster scanning helmets, including:

Acquiring the first fisheye image and corresponding first spatial information at time t1, where the first spatial information includes the orientation information at time t1;

Obtaining a second fisheye image at time t2 and corresponding second spatial information, where the second spatial information includes orientation information at time t2;

Acquire a first center image and a first side image corresponding to the first fisheye image, the first center image is a projection of the first fisheye image along a preset orientation, and the first side image is the The projection of the first fisheye image along the orthogonal direction of the preset orientation, where both the preset orientation and the orthogonal direction of the preset orientation are included in the orientation information at the time t1;

Acquire a second center image and a second side image corresponding to the second fisheye image, the second center image is a projection of the second fisheye image along a preset orientation, and the second side image is the The projection of the second fisheye image along the orthogonal direction of the preset orientation, the first side image and the second side image are located in the same orientation, and the preset orientation and the orthogonal direction of the preset orientation are included in the In the azimuth information at the time t2;

At least two first feature points are respectively extracted on the first center image and the first side image, and according to the first feature points, are respectively extracted on the second center image and the second side image Two second feature points, the first feature point and the second feature point are respectively matched with each other;

obtaining a roll angle according to a positional relationship between a first feature point on the first center image and a second feature point on the second center image;

Acquiring a pitch angle according to the positional relationship between the first feature point on the first side image and the second feature point on the second side image;

According to the roll angle and the pitch angle, the change amount of the shooting attitude at the time t2 relative to the time t1 is determined.

In some of the embodiments, the preset orientation is determined by the magnetometer, and the preset orientation remains the same orientation at any time.

In some of these embodiments, extracting two second feature points respectively on the second center image and the second side image includes:

Obtaining a first search area centered on the first feature point, each of the first feature points corresponds to a first search area;

Obtaining a second search area on the second center image and the second side image, the second search area is set corresponding to the first search area;

A second feature point corresponding to the first feature point in the first search area is acquired in the second search area.

In some of these embodiments, obtaining the second feature points corresponding to the first feature points in the first search area in the second search area also includes the following steps:

When the second feature point corresponding to the first feature point in the first search area cannot be obtained in the second search area, increase the search area size of the first search area, and increase the The search area size of the second search area.

In some of these embodiments, obtaining the roll angle according to the positional relationship between the first feature point on the first center image and the second feature point on the second center image includes the following steps:

connecting the first feature point with the corresponding second feature point to obtain a roll feature line;

Calculate the absolute value of the included angle between the roll characteristic line and the horizontal azimuth to obtain the absolute value of the roll angle, and take the roll characteristic line to roll right along the vertical axis as positive.

In some of these embodiments, obtaining the pitch angle according to the positional relationship between the first feature point on the first side image and the second feature point on the second side image may include the following steps:

connecting the first feature point with the corresponding second feature point to obtain a pitch feature line;

Calculate the absolute value of the included angle between the pitch feature line and the horizontal azimuth to obtain the absolute value of the pitch angle, and take the vertically upward azimuth as positive.

In the third aspect, a computer-readable storage medium provided by the present application adopts the following technical solution:

A computer-readable storage medium stores a method for determining the shooting attitude of any one of the above natural disaster scanning images that can be loaded by a processor and executed.

Through the method for determining the shooting posture of a natural disaster panoramic helmet and its image provided by the embodiment of the present application, during the natural disaster scanning process, some patrol vehicles cannot pass through, and there is a maximum load that is limited by people. When unmanned aerial vehicles cannot be used due to power and battery problems, manual inspection is required. The operator wears a natural disaster panoramic helmet to explore, which reduces the inconvenience caused by the original need for handheld shooting equipment, and the panoramic fisheye camera on the panoramic helmet automatically monitors the natural disasters. Disasters are photographed and scanned, and at the same time, the shooting posture is adjusted by the method of determining the shooting posture of the images taken during the natural disaster scanning process, and the panoramic images taken within a predetermined time period are spatially transformed to obtain a panoramic image with a preset fixed posture. To a certain extent, the work effect of natural disaster scanning has been improved.

Description of drawings

Fig. 1 is a schematic diagram of the overall steps of the method for determining the shooting posture of the natural disaster scanning image in the embodiment of the present application;

Fig. 2 is a schematic diagram of the steps of extracting two second feature points respectively on the second center image and the second side image;

Fig. 3 is a schematic diagram of the steps of obtaining the roll angle;

Figure 4 is a schematic diagram of the steps for obtaining the pitch angle.

Detailed ways

In order to understand the purpose, technical solution and advantages of the present application more clearly, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. However, it will be understood by one of ordinary skill in the art that the present application may be practiced without these details. In some instances, well-known methods, procedures, systems, components and/or circuits have been described at a high level without unnecessary description, in order to avoid obscuring aspects of the present application. repeat. It is obvious to those skilled in the art that various changes can be made to the embodiments disclosed in the application, and the general principles defined in the application can be applied to other applications without departing from the principle and scope of the application. Examples and application scenarios. Thus, the application is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with what is claimed herein.

Unless otherwise defined, the technical terms or scientific terms involved in the application shall have the general meanings understood by those skilled in the technical field to which the application belongs. The terminology used in the present application is for the purpose of describing specific embodiments only, and is not intended to limit the present application. As used in this application, "a", "an", "an", "the", "these" and similar words do not denote a limitation on quantity, and they may be singular or plural. The terms "comprising", "comprising", "having" and any variants thereof referred to in this application are intended to cover non-exclusive inclusion; for example, processes, methods and The system, product, or apparatus is not limited to the steps or modules (units) listed, but may include steps or modules (units) that are not listed, or may include other steps or modules that are inherent to the process, method, product, or apparatus (unit).

"Plurality" referred to in this application means two or more. Usually, the character "/" indicates that the objects associated before and after are in an "or" relationship. The terms "first", "second", "third" and the like involved in this application are only for distinguishing similar objects, and do not represent a specific ordering of objects.

The terms "system", "engine", "unit", "module" and/or "block" referred to in this application are used to classify different components, elements, parts, components, assemblies, or a method of function. These terms may be replaced by other expressions that serve the same purpose. Generally, a "module", "unit" or "block" referred to in this application refers to a collection of logic or software instructions embodied in hardware or firmware. The "module", "unit" or "block" described in this application can be implemented as software and/or hardware, and in the case of being implemented as software, they can be stored in any type of non-volatile computer-readable storage medium or storage device.

In some embodiments, a software module/unit/block may be compiled and linked into an executable program. It will be appreciated that a software module may be callable from other modules/units/blocks or from itself, and/or may be called in response to a detected event or interrupt. A software module/unit/block configured to execute on a computing device may be provided on a computer-readable storage medium such as an optical disc, digital video disc, flash drive, magnetic disk, or any other tangible medium, or as a digital download (and may initially stored in a compressed or installable format that requires installation, decompression, or decryption before execution). Such software codes may be stored in part or in whole on the memory device of the executing computing device and employed in the operation of the computing device. Software instructions may be embedded in firmware, such as EPROM. It will also be appreciated that hardware modules/units/blocks may be included in connected logic components, such as gates and flip-flops, and/or may be included in programmable elements, such as programmable gate arrays or processors. The modules/units/blocks or computing device functions described herein may be implemented as software modules/units/blocks, and may also be represented in hardware or firmware. In general, the modules/units/blocks described herein, they may be combined with other modules/units/blocks, or be divided into sub-modules/subunits/sub-blocks despite their physical organization or storage. The description may apply to a system, an engine, or a portion thereof.

It will be understood that when a unit, engine, module or block is referred to as being "on", "connected" or "coupled to" another unit, engine, module or block, its Other units, engines, modules or blocks may be directly on, connected or coupled to, or in communication with, other units, engines, modules or blocks, or intervening units, engines, modules or blocks may be present, unless the context clearly dictates otherwise. In this application, the term "and/or" may include any one or the above related listed items or a combination thereof.

The present application will be described in further detail below in conjunction with accompanying drawings 1-4.

The embodiment of the present application discloses a natural disaster scanning helmet, which includes a helmet body, a panoramic fisheye camera, a magnetometer and a data processing system. The panoramic fisheye camera and the magnetometer are respectively electrically connected to the data processing system.

The helmet body can be made of a material with a certain rigidity, because during the natural disaster scanning process, if encountering severe weather such as strong wind or hail, the relatively hard helmet body can protect the operator's head to a certain extent .

At the same time, the weight of the helmet body can also be made light enough, so that the helmet has a certain degree of lightness while being hard, such as aluminum alloy or carbon fiber material. The inside of the helmet body can be fixedly connected with a protective pad. When the operator wears the helmet for a long time, the protective pad can reduce the burden of the helmet on the head to a certain extent.

The panoramic fisheye camera can be a common fisheye camera on the market.

The fisheye panoramic camera is used to acquire a first fisheye image at time t1 and a second fisheye image at time t2.

Magnetometer is also called geomagnetism and magnetic sensor. It can be used to test the strength and orientation of the magnetic field and locate the orientation of the device. The principle of the magnetometer is similar to that of a compass. It can measure the angle between the current equipment and the four directions of east, west, north and south.

The magnetometer is used to acquire the first spatial information of the helmet at time t1 and the second spatial information of the helmet at time t2. The first spatial information includes the orientation information of the helmet at time t1, and the second spatial information includes the orientation information of the helmet at time t2.

The data processing system includes a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the method used in the natural disaster scanning process.

The panoramic fisheye camera and the magnetometer are respectively electrically connected to the data processing system.

The data processing system is used to acquire a first center image and a first side image according to the first fisheye image, the first center image is a projection of the first fisheye image along a preset orientation, and the first side image is a projection of the first fisheye image along a Projection in the orthogonal direction of the preset orientation.

The data processing system is also used to acquire a second center image and a second side image according to the second fisheye image, the second center image is the projection of the second fisheye image along a preset orientation, and the second side image is the second fisheye image Orthogonal projection along a preset orientation.

The data processing system is also used to extract at least two first feature points on the first center image and the first side image, and extract at least two first feature points on the second center image and the second side image respectively. Match at least two second feature points.

The data processing system is also used for obtaining the roll angle according to the positional relationship between the first feature point on the first center image and the second feature point on the second center image; and according to the first side image and the second side image on the second side image. The pitch angle is obtained from the positional relationship of the two feature points; and the change amount of the shooting attitude at the time t2 relative to the time t1 is determined according to the roll angle and the pitch angle.

Further, it also includes a satellite positioning module arranged inside the helmet body. The satellite positioning module can use a GPS positioning device or a Beidou positioning device, which can be selected according to actual needs.

The satellite positioning module is used to obtain the longitude and latitude position information of the helmet at time t1 and t2, which is convenient for the background to track the helmet and obtain its position in real time.

Furthermore, the panoramic fisheye camera is also equipped with a small battery, and is connected with a replaceable pocket battery compartment. The small battery mainly plays the role of UPS. Usually, the pocket battery compartment is used to power the helmet. When the pocket battery compartment is exhausted, the small battery can guarantee short-term battery life, so that the pocket battery compartment can be easily replaced without the system having to interrupt the collection.

The images collected by the panoramic fisheye camera will be embedded into the ArcGIS map according to the positioning signal, and the image of the panoramic fisheye camera needs to be corrected to a fixed shooting posture. Different from the existing technology that uses "acceleration sensor + magnetometer" to obtain the carrier posture of the panoramic fisheye camera to correct the shooting posture of the panoramic fisheye camera, this solution uses the method of local matching of the feature points of the orthogonal projection image to obtain the panoramic fisheye The carrier pose information of the camera.

As shown in Figure 1, the embodiment of the present application also discloses a method for determining the shooting posture of natural disaster scanning images, which is applied to the above-mentioned natural disaster scanning helmets, including:

S100. Acquire a first fisheye image and corresponding first spatial information at time t1.

S200. Acquire a second fisheye image and corresponding second spatial information at time t2.

S300. Acquire a first center image and a first side image corresponding to the first fisheye image.

S400. Acquire a second center image and a second side image corresponding to the second fisheye image.

S500, respectively extracting at least two first feature points on the first center image and the first side image, respectively extracting two second feature points on the second center image and the second side image according to the first feature points, and The first feature point and the second feature point are individually matched to each other.

S600. Obtain a roll angle according to the positional relationship between the first feature point on the first center image and the second feature point on the second center image.

S700. Obtain a pitch angle according to the positional relationship between the first feature point on the first side image and the second feature point on the second side image.

S800. Determine, according to the roll angle and the pitch angle, the change amount of the shooting attitude at the time t2 relative to the time t1.

Both the first fisheye image and the second fisheye image are captured by a panoramic fisheye camera. In the embodiment of the present application, the default time t2 is after the time t1, and the time interval between t1 and t2 is relatively short.

The first spatial information includes orientation information at time t1 and latitude and longitude information at time t1. The orientation information is obtained by the magnetometer, and the latitude and longitude information is obtained by the satellite positioning module. Similarly, the second spatial information includes orientation information at time t2 and latitude and longitude information at time t2.

The first central image is a projection of the first fisheye image along a preset orientation, and the first side image is a projection of the first fisheye image along an orthogonal direction of the preset orientation. Both the preset orientation and the orthogonal direction of the preset orientation are included in the orientation information at time t1.

The preset orientation is manually selected after being obtained by the magnetometer. For example, the magnetic north orientation can be defined as the preset orientation, and the first central image is the projection of the first fisheye image along the magnetic north orientation, while the first side image is is the orthogonal direction of the first fisheye image along the magnetic north azimuth, that is, the projection on the magnetic west or magnetic east azimuth, and the preset azimuth keeps the same azimuth at any time.

Correspondingly, the second center image is the projection of the second fisheye image along the preset orientation, and the second side image is the projection of the second fisheye image along the orthogonal direction of the preset orientation. Both the preset orientation and the orthogonal direction of the preset orientation are included in the orientation information at time t2. At the same time, the selection of the preset orientation is the same as the above-mentioned rules, which will not be repeated here.

It should be noted that the orientations of the first side image and the second side image are consistent, that is to say, when the preset orientation is determined to be the magnetic north orientation, the orientations of the first side image and the second side image are both Magnetic west or magnetic east, which is perpendicular to magnetic north.

Before projecting the fisheye image, in order to improve the efficiency of projection, the fisheye image can be corrected first, and the correction is to dedistort the fisheye image. After correction, a fisheye image can be converted into several images, which cover the field of view of the fisheye image from different perspectives. It is generally believed that the fisheye image only undergoes geometric deformation without distortion.

The essence of the correction of the fisheye image is the spatial transformation of image processing (geometric transformation, geometric operation), only the points on the image are copied without modification. Space transformation is regarded as the image point moving within the image, that is, the point A (u, v) on the fisheye image is corrected to the point A (x, y) on the image.

The mapping methods include backward mapping and forward mapping.

Backward mapping: using the similar filling method, after the coordinates of the corrected image are mapped and transformed to obtain the corresponding fisheye image coordinates, the image components at the fisheye image coordinates are copied to the corrected image coordinates (u,v)T=

f

(x, y), calculate the image component of the sub-pixel coordinate point (fisheye image) from the pixel coordinate point (corrected image).

Forward mapping: After obtaining the corrected image coordinates from the fisheye image coordinates through mapping transformation, copy the image components of the fisheye image coordinates to the corrected image coordinates, (x,y)T=

G

(u, v), calculate the pixel coordinate point from the pixel sub-pixel coordinate point.

In image processing, the input to the mapping is pixel coordinates (integer coordinates), and the output is sub-pixel coordinates (non-integer coordinates).

Extract at least two first feature points on the first central image and the first side image respectively. It should be noted that when the number of feature points is greater than two, in order to improve accuracy, several feature points are not collinear with each other. .

A second feature point that matches the first feature point is extracted from the second center image and the second side image. For example, the spire of the tower and the corner of the window of the car on the first central image are used as the first feature point, and the tree tops and street lamp tops on the first side image are used as the first feature point, and at the second moment t2 The spire of the tower and the corner of the window of the car after a period of shooting angle change are extracted from the central image, which are defined as the second feature points, and the tops of trees and street lamps are extracted from the second side image as the second feature points.

Among them, for the feature extraction method of feature points, common methods such as SIFT, HOG, SURF, ORB, LBP, HAAP, and neural network learning in related technologies can be selected.

As shown in Figure 2, further, extracting two second feature points on the second center image and the second side image respectively also includes:

S510. Acquire a first search area centered on the first feature point, and each first feature point corresponds to a first search area.

S520. Acquire a second search area on the second center image and the second side image.

S530. Acquire second feature points corresponding to the first feature points in the first search area in the second search area.

Further, the second search area is set opposite to the first search area, in other words, relative to the first center image and the second center image of the same size, and the first side image and the second side image of the same size, The positions of the first search area and the second search area on the image are the same and may overlap.

Setting the first search area and the second search area can further reduce the workload when extracting the first feature point and the second feature point. Assuming that the first search area is not set and the first central image is an image of 1000*1000 pixels, then after the first search area is obtained centering on the first feature point, the size of the first search area may only be 50*50 pixels The area may also be an area of 100*100 pixels, but this also greatly reduces the amount of calculation when extracting feature points.

After the first search area is obtained, because the time interval between t1 and t2 is short, the change of the second fisheye image relative to the first fisheye image is small, and because the second search area is different from the first search area Relatively set, so there is a high probability that there are feature points in the second search area on the second center image and the second side image that are the same as the first feature point, which may be obtained by translation, rotation, and roll of the first feature point , these feature points are defined as the second feature points. It can also be said that the second feature point is obtained by a certain degree of translation, rotation, and roll of the first feature point.

Further, obtaining the second feature point corresponding to the first feature point in the first search area in the second search area also includes: when the first feature point in the second search area cannot be obtained in the second search area. When the point corresponds to the second feature point, increase the size of the search area of the first search area, and correspondingly increase the size of the search area of the second search area.

Wherein, the size of the search area refers to the size of a closed space surrounded by polygons. The larger the closed space is, the more the number of pixels in the closed space is, and the larger the extraction range of feature points is. The shape of the closed space can be set to any shape, and it is generally set as a rectangular closed space.

Because the position and size of the second search area correspond to the position and size of the first search area, when the first search area increases, the second search area will also increase accordingly.

When the range of movement is large during the time period from t1 to t2, resulting in that the second feature point corresponding to the first feature point cannot be extracted in the second search area corresponding to the first search area, it is necessary to properly Enlarging the size of the search area ensures that the second feature point corresponding to the first feature point can be extracted within the enlarged second search area on the premise of increasing a certain amount of calculation.

As shown in Figure 3, the roll angle is obtained according to the positional relationship between the first feature point on the first center image and the second feature point on the second center image, including the following steps:

S610. Connect the first feature point with its corresponding second feature point to obtain a roll feature line.

S620. Calculate the absolute value of the included angle between the roll characteristic line and the horizontal orientation to obtain the absolute value of the roll angle, and take the roll characteristic line to roll right along the vertical axis as positive.

The first feature point and the second feature point corresponding to each other are connected to obtain a roll feature line, and the roll feature line is the movement trajectory of the feature point at time t1 and time t2. The roll angle is the angle between the transverse axis of the vehicle and the horizontal line. The roll characteristic line obtained by the movement of the horizontal coordinate point and the vertical coordinate point represented by the movement trajectory of the feature point at the time t1 and time t2 represents the final shape of the carrier on the horizontal axis of the central image, so the roll The absolute value of the angle between the characteristic line and the horizontal line is the absolute value of the roll angle.

As shown in Figure 4, according to the first feature point on the first side image and the positional relationship of the second feature point on the second side image, the pitch angle is obtained, including the following steps:

S710. Connect the first feature point with the corresponding second feature point to obtain a pitch feature line.

S720. Calculate the absolute value of the included angle between the pitch feature line and the horizontal azimuth to obtain the absolute value of the pitch angle, and take the vertically upward azimuth as positive.

Connect the first feature point and the second feature point corresponding to the hometown matching to obtain the pitch feature line, and the pitch feature line is the trajectory of the feature point at time t1 and time t2. The pitch angle is the angle between the longitudinal axis of the vehicle and the horizontal. The roll feature line obtained by the movement of the horizontal coordinate point and the vertical coordinate point represented by the movement trajectory of the feature point at time t1 and time t2 represents the final shape of the vertical axis change of the vehicle on the side image, so the pitch feature The absolute value of the angle between the line and the horizontal azimuth is the absolute value of the pitch angle.

According to the size of the roll angle and the pitch angle, the attitude change of the vehicle at the time t2 relative to the time t1 can be known. After obtaining the attitude change of the panoramic fisheye camera from time t1 to time t2, the second fisheye image captured at time t2 can be spatially transformed to obtain a panoramic image with a preset fixed attitude.

Further, according to the latitude and longitude information and azimuth information, the corrected panoramic image is embedded into the map ArcGIS map to form natural disaster scanning data.

The embodiment of the present application also discloses a computer-readable storage medium, which stores the method for determining the shooting posture of the natural disaster scanning image that can be loaded by a processor and executed.

All of the above are preferred embodiments of the application, and are not intended to limit the protection scope of the application. Therefore, all equivalent changes made according to the structure, shape, and principle of the application should be covered by the protection scope of the application. Inside.

Claims (8)

1. A natural disaster scanning helmet, characterized in that: the helmet comprises: the helmet comprises a helmet body, a panoramic fisheye camera arranged at the top of the helmet body, and a magnetometer and a data processing system arranged in the helmet body; the panoramic fisheye camera and the magnetometer are respectively and electrically connected with the data processing system, wherein,

the panoramic fisheye camera is used for acquiring a first fisheye image at the time t1 and a second fisheye image at the time t 2;

the magnetometer is configured to obtain first spatial information of the helmet at a time t1 and second spatial information of the helmet at a time t2, where the first spatial information includes azimuth information of the helmet at the time t1, and the second spatial information includes azimuth information of the helmet at the time t 2;

the data processing system is used for acquiring a first center image and a first side image according to the first fisheye image, wherein the first center image is the projection of the first fisheye image along a preset azimuth, and the first side image is the projection of the first fisheye image along an orthogonal direction of the preset azimuth;

the data processing system is further configured to obtain a second center image and a second side image according to the second fisheye image, where the second center image is a projection of the second fisheye image along a preset azimuth, and the second side image is a projection of the second fisheye image along an orthogonal direction of the preset azimuth;

the data processing system is further used for respectively extracting at least two first characteristic points on the first center image and the first side image; extracting at least two second feature points respectively matched with the at least two first feature points on the second center image and the second side image;

the data processing system is further used for acquiring a roll angle according to the position relation between the first characteristic point on the first center image and the second characteristic point on the second center image; acquiring a pitch angle according to the position relation between the first characteristic point on the first side image and the second characteristic point on the second side image; and determining the variation of the shooting posture at the moment t2 relative to the moment t1 according to the roll angle and the pitch angle.

2. A method for determining shooting postures of natural disaster scanning images, which is applied to the natural disaster scanning helmet as claimed in claim 1, and is characterized by comprising the following steps:

acquiring a first fisheye image at a time t1 and corresponding first space information, wherein the first space information comprises azimuth information of the time t 1;

acquiring a second fisheye image at the time t2 and corresponding second spatial information, wherein the second spatial information comprises azimuth information of the time t 2;

acquiring a first center image and a first side image corresponding to a first fisheye image, wherein the first center image is a projection of the first fisheye image along a preset direction, the first side image is a projection of the first fisheye image along an orthogonal direction of the preset direction, and the preset direction and the orthogonal direction of the preset direction are both contained in direction information of the moment t 1;

acquiring a second center image and a second side image corresponding to a second fish-eye image, wherein the second center image is a projection of the second fish-eye image along a preset direction, the second side image is a projection of the second fish-eye image along an orthogonal direction of the preset direction, the first side image and the second side image are positioned in the same direction, and the orthogonal directions of the preset direction and the preset direction are both contained in direction information of the t2 moment;

respectively extracting at least two first characteristic points on the first center image and the first side image, respectively extracting two second characteristic points on the second center image and the second side image according to the first characteristic points, wherein the first characteristic points and the second characteristic points are respectively matched with each other;

acquiring a roll angle according to the position relation between the first characteristic point on the first center image and the second characteristic point on the second center image;

acquiring a pitch angle according to the position relation between the first characteristic point on the first side image and the second characteristic point on the second side image;

and determining the variation of the shooting posture at the moment t2 relative to the moment t1 according to the roll angle and the pitch angle.

3. The method for determining the shooting attitude of a natural disaster scanning image according to claim 2, wherein: the preset azimuth is determined by the magnetometer, and the preset azimuth is kept at the same azimuth at any time.

4. The method for determining the shooting attitude of a natural disaster scanning image according to claim 2, wherein: extracting two second feature points on the second center image and the second side image respectively, including:

acquiring a first search area by taking the first characteristic points as the center, wherein each first characteristic point corresponds to one first search area;

acquiring a second search area on the second center image and the second side image, wherein the second search area is arranged corresponding to the first search area;

and acquiring second characteristic points corresponding to the first characteristic points in the first search area in the second search area.

5. The method for determining the shooting attitude of a natural disaster scanning image according to claim 4, wherein: acquiring a second feature point corresponding to the first feature point in the first search area in the second search area, and further comprising the following steps:

and when the second characteristic points corresponding to the first characteristic points in the first search area cannot be acquired in the second search area, increasing the search area size of the first search area, and correspondingly, increasing the search area size of the second search area.

6. The method for determining the shooting attitude of a natural disaster scanning image according to claim 2, wherein: acquiring a roll angle according to the position relation between a first characteristic point on the first center image and a second characteristic point on the second center image, wherein the roll angle comprises the following steps:

connecting the first characteristic points with the corresponding second characteristic points to obtain a roll characteristic line;

and calculating the absolute value of the included angle between the transverse rolling characteristic line and the horizontal direction to obtain the absolute value of the transverse rolling angle, and taking the transverse rolling characteristic line to roll rightwards along the longitudinal axis as positive.

7. The method for determining the shooting attitude of a natural disaster scanning image according to claim 2, wherein: acquiring a pitch angle according to the position relation between a first characteristic point on the first side image and a second characteristic point on the second side image, wherein the pitch angle comprises the following steps:

connecting the first characteristic points with the corresponding second characteristic points to obtain pitching characteristic lines;

and calculating the absolute value of the included angle between the pitching characteristic line and the horizontal direction to obtain the absolute value of the pitching angle, and taking the direction along the vertical direction as positive.

8. A computer-readable storage medium, characterized by: a shooting attitude determination method in which a natural disaster relief image as claimed in any one of claims 2 to 7 can be loaded and executed by a processor is stored.

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