Target detection method and system for spatial fusion of visible light image and infrared image

Abstract

The invention discloses a visible light image and infrared image space fusion target detection method and system, and relates to the technical field of target detection, and the method comprises the steps: carrying out the time alignment of a visible light camera and an infrared camera, and collecting a visible light image and an infrared image at the same time; performing target detection on the infrared image to obtain a first feature vector, and performing target detection on the visible light image to obtain a second feature vector; transforming the second feature vector by using a homography transformation matrix satisfied by a visible light image shot by a visible light camera and an infrared image shot by an infrared camera to obtain a third feature vector; combining the first feature vector and the third feature vector to obtain a fourth feature vector; and obtaining a fused target list according to the fourth feature vector. According to the method, the fused target list can be obtained without re-labeling the paired visible light image and infrared image, and the fusion process is simpler, faster and more efficient.

Description

Background Art

[0002] The dual-spectrum all-in-one machine includes a visible light camera and an infrared camera (specifically, a far-infrared camera), which complement each other during the day and night, and can also provide temperature information of the target. It is an important component of vehicle-road collaboration and digital twin systems. Therefore, it is necessary to fuse the target detection results obtained by detecting the visible light image collected by the visible light camera and the target detection results obtained by detecting the visible light image collected by the infrared camera. The existing dual-spectrum fusion detection schemes include: front fusion and feature fusion, but front fusion and feature fusion require paired visible light images and infrared images as input, and the training stage also requires a considerable number of image pairs as training sets, which cannot make full use of existing data sets. Summary of the invention

[0003] The technical problem to be solved by the present invention is to address the deficiencies of the prior art and specifically provide a target detection method and system for spatial fusion of visible light images and infrared images, as follows:

[0004] 1) In the first aspect, the present invention provides a target detection method for spatial fusion of visible light image and infrared image, and the specific technical scheme is as follows:

[0005] After the visible light camera and the infrared camera are time-aligned, the visible light camera and the infrared camera are used to collect visible light images and infrared images respectively at the same time;

[0006] Performing target detection on the infrared image to obtain a first eigenvector, and performing target detection on the visible light image to obtain a second eigenvector;

[0007] The second eigenvector is transformed using a homography transformation matrix satisfied by the visible light image taken by the visible light camera and the infrared image taken by the infrared camera to obtain a third eigenvector;

[0008] The first eigenvector and the third eigenvector are combined to obtain a fourth eigenvector;

[0009] According to the fourth eigenvector, a fused target list is obtained.

[0010] The beneficial effects of the target detection method of spatial fusion of visible light image and infrared image provided by the present invention are as follows:

[0011] The second eigenvector obtained based on the visible light image is transformed into the space of the infrared image using the homography transformation matrix to obtain the third eigenvector. The first eigenvector and the third eigenvector are then merged and processed. The fused target list can be obtained without re-labeling the paired visible light images and infrared images. The fusion process is simpler, faster and more efficient.

[0012] On the basis of the above scheme, the target detection method of spatial fusion of visible light image and infrared image of the present invention can also be improved as follows.

[0013] Further, according to the fourth eigenvector, a fused target list is obtained, including:

[0014] The fourth eigenvector is processed using the maximum suppression algorithm to obtain a fused target list.

[0015] Furthermore, the process of performing target detection on the infrared image and the process of performing target detection on the visible light image includes:

[0016] Use the trained first YOLO model to detect targets in infrared images;

[0017] Use the trained second YOLO model to detect targets in visible light images;

[0018] The network structures of the trained first YOLO model and the trained second YOLO model are the same.

[0019] Furthermore, the visible light camera and the infrared camera are: a visible light camera and an infrared camera in a dual-spectrum integrated machine.

[0020] 2) In the second aspect, the present invention also provides a target detection method for spatial fusion of visible light image and infrared image, and the specific technical scheme is as follows:

[0021] It includes an image acquisition module, a target detection module, a feature vector transformation module, a feature vector merging module and a feature vector processing module;

[0022] The image acquisition module is used to: after time alignment of the visible light camera and the infrared camera, use the visible light camera and the infrared camera to respectively collect the visible light image and the infrared image at the same time;

[0023] The target detection module is used to: perform target detection on the infrared image to obtain a first feature vector, and perform target detection on the visible light image to obtain a second feature vector;

[0024] The eigenvector transformation module is used to transform the second eigenvector using the homography transformation matrix satisfied by the visible light image taken by the visible light camera and the infrared image taken by the infrared camera to obtain a third eigenvector;

[0025] The feature vector merging module is used to: merge the first feature vector and the third feature vector to obtain a fourth feature vector;

[0026] The feature vector processing module is used to obtain a fused target list according to the fourth feature vector.

[0027] On the basis of the above scheme, the target detection method of spatial fusion of visible light image and infrared image of the present invention can also be improved as follows.

[0028] Furthermore, the feature vector processing module is specifically used to: utilize a maximum suppression algorithm to process the fourth feature vector to obtain a fused target list.

[0029] Furthermore, the target detection module is specifically used for:

[0030] Use the trained first YOLO model to detect targets in infrared images;

[0031] Use the trained second YOLO model to detect targets in visible light images;

[0032] The network structures of the trained first YOLO model and the trained second YOLO model are the same.

[0033] Furthermore, the visible light camera and the infrared camera are: a visible light camera and an infrared camera in a dual-spectrum integrated machine.

[0034] 3) In a third aspect, the present invention further provides an electronic device, comprising a processor, the processor being coupled to a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor, so that the electronic device can implement any of the above-mentioned target detection methods for spatial fusion of visible light images and infrared images.

[0035] 4) In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned target detection methods for spatial fusion of visible light images and infrared images.

[0036] It should be noted that the beneficial effects achieved by the technical solutions of the second to fourth aspects of the present invention and the corresponding possible implementation methods can be found in the above-mentioned technical effects of the first aspect and its corresponding possible implementation methods, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments of the present invention:

[0038] Figure 1 A schematic diagram of a flow chart of a target detection method for spatial fusion of a visible light image and an infrared image according to an embodiment of the present invention;

[0039] Figure 2 A schematic diagram of the structure of a target detection system for spatial fusion of a visible light image and an infrared image according to an embodiment of the present invention;

[0040] Figure 3 The figure is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The principles and features of the present invention are described below. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0042] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0043] like Figure 1 As shown, a target detection method for spatial fusion of a visible light image and an infrared image according to an embodiment of the present invention includes the following steps:

[0044] S1, after time alignment of the visible light camera and the infrared camera, use the visible light camera and the infrared camera to collect visible light images and infrared images respectively at the same time;

[0045] S2. Perform target detection on the infrared image to obtain a first eigenvector, and perform target detection on the visible light image to obtain a second eigenvector. Specifically:

[0046] 1) Use the trained first YOLO model to perform target detection on the infrared image and obtain the first eigenvector.

[0047] 2) Use the trained second YOLO model to perform target detection on the visible light image to obtain the second feature vector.

[0048] The network structures of the trained first YOLO model and the trained second YOLO model are the same.

[0049] The first feature vector specifically includes the position coordinates of each target in the coordinate system where the infrared camera is located, and the second feature vector specifically includes the position coordinates of each target in the coordinate system where the visible light camera is located.

[0050] Among them, the coordinate system used by the infrared camera is: the straight line where the bottom edge of the infrared image taken by the infrared camera is located is the x-axis, and the specified position on the infrared image taken by the infrared camera is the origin. The established rectangular coordinate system, the specified position can be the center point position of the infrared image, or it can be any position on the bottom edge of the infrared image. That is to say, the origin position can be set according to actual conditions, the straight line where the bottom edge of the infrared image is located can be used as the x-axis, or the x-axis and y-axis of the rectangular coordinate system can be set according to actual conditions.

[0051] Among them, the coordinate system used by the visible light camera is: the straight line where the bottom edge of the visible light image taken by the visible light camera is located is the x-axis, and the specified position on the visible light image taken by the visible light camera is the origin. The established rectangular coordinate system, the specified position can be the center point position of the visible light image, or it can be any position on the bottom edge of the visible light image. That is to say, the origin position can be set according to actual conditions, the straight line where the bottom edge of the visible light image is located can be used as the x-axis, or the x-axis and y-axis of the rectangular coordinate system can be set according to actual conditions.

[0052] S3, using the homography transformation matrix satisfied by the visible light image taken by the visible light camera and the infrared image taken by the infrared camera, transform the second eigenvector to obtain the third eigenvector, which is specifically implemented by the following formula:

[0053] P3=H×P1

[0054] Where H represents the homography transformation matrix, P1 represents the second eigenvector, and P3 represents the third eigenvector. h 00 、h 01 、h 02 、h 10 、h 11 、h 12 、h 20 、h 21 and h 22 is the element in the homography transformation matrix H.

[0055] The time-aligned visible light camera and infrared camera are used to track the target. The position coordinates of the same target monitored at any same time in the corresponding coordinate system satisfy:

[0056]

[0057] Among them, the position coordinates in the coordinate system used by the visible light camera are (u, v), the position coordinates in the coordinate system used by the infrared camera are (x, y), and (u, v) and (x, y) are: the position coordinates of the same target monitored by the visible light camera and the infrared camera after time alignment at any same time, and s represents the coefficient of the homogeneous coordinates.

[0058] The process of obtaining the homography transformation matrix H is as follows:

[0059] A set of equations between the position coordinates of the unified target in the coordinate system used by the visible light camera and the position coordinates in the coordinate system used by the infrared camera is constructed. The set of equations contains the elements in the homography transformation matrix H. The set of equations is transformed into a homogeneous linear system of equations. The linear algebra method (such as SVD decomposition) is used to solve the homogeneous linear system of equations, and the value of each element in the homography transformation matrix H can be calculated.

[0060] The second eigenvector is transformed into the space of the infrared image by the formula P3=H×P1 to obtain the third eigenvector.

[0061] Among them, transforming the second eigenvector to the space of the infrared image specifically means: transforming the position coordinates of each target in the second eigenvector in the coordinate system where the visible light camera is located to the coordinate system where the infrared camera is located, and the third eigenvector includes: the position coordinates of each target in the second eigenvector in the coordinate system where the visible light camera is located are transformed to the position coordinates in the coordinate system where the infrared camera is located.

[0062] S4. Merge the first eigenvector and the third eigenvector to obtain a fourth eigenvector, which is specifically achieved by the following formula:

[0063] P4=P1∪P3

[0064] Wherein, P1 represents the first eigenvector, and P4 represents the fourth eigenvector.

[0065] S5. According to the fourth eigenvector, a fused target list is obtained. Specifically:

[0066] The fourth eigenvector is processed using the maximum suppression algorithm to obtain a fused target list.

[0067] The visible light camera and the infrared camera may be a visible light camera and an infrared camera of a dual-spectrum integrated machine, or may be a visible light camera and an infrared camera that are independently arranged.

[0068] In the above embodiments, although the steps are numbered S1, S2, etc., these are only specific embodiments given by the present invention. Those skilled in the art may adjust the execution order of S1, S2, etc. according to actual conditions, which is also within the protection scope of the present invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.

[0069] like Figure 2 As shown, a target detection system 200 of a visible light image and an infrared image spatially fused in an embodiment of the present invention comprises an image acquisition module 201, a target detection module 202, a feature vector transformation module 203, a feature vector merging module 204 and a feature vector processing module 205;

[0070] The image acquisition module 201 is used to: after time alignment of the visible light camera and the infrared camera, use the visible light camera and the infrared camera to respectively collect the visible light image and the infrared image at the same time;

[0071] The target detection module 202 is used to: perform target detection on the infrared image to obtain a first feature vector, and perform target detection on the visible light image to obtain a second feature vector;

[0072] The eigenvector transformation module 203 is used to transform the second eigenvector using the homography transformation matrix satisfied by the visible light image taken by the visible light camera and the infrared image taken by the infrared camera to obtain a third eigenvector;

[0073] The feature vector merging module 204 is used to: merge the first feature vector and the third feature vector to obtain a fourth feature vector;

[0074] The feature vector processing module 205 is used to obtain a fused target list according to the fourth feature vector.

[0075] Optionally, in the above technical solution, the feature vector processing module 205 is specifically used to: process the fourth feature vector using a maximum suppression algorithm to obtain a fused target list.

[0076] Optionally, in the above technical solution, the target detection module 202 is specifically used for:

[0077] Use the trained first YOLO model to detect targets in infrared images;

[0078] Use the trained second YOLO model to detect targets in visible light images;

[0079] The network structures of the trained first YOLO model and the trained second YOLO model are the same.

[0080] Optionally, in the above technical solution, the visible light camera and the infrared camera are: a visible light camera and an infrared camera of a dual-spectrum all-in-one device.

[0081] It should be noted that the beneficial effects of the target detection system 200 for spatial fusion of visible light images and infrared images provided in the above embodiment are the same as the beneficial effects of the target detection method for spatial fusion of visible light images and infrared images, which will not be described in detail here. In addition, when the system provided in the above embodiment realizes its functions, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the system can be divided into different functional modules according to actual conditions to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be described in detail here.

[0082] Among them, the target detection system of spatial fusion of visible light image and infrared image of the present invention can be a computer program (including program code) running in a computer device. For example, the target detection system of spatial fusion of visible light image and infrared image of the present invention is an application software, which can be used to execute the corresponding steps of the target detection method of spatial fusion of visible light image and infrared image of the present invention.

[0083] In some embodiments, the target detection system for spatial fusion of visible light images and infrared images of the present invention can be implemented by a combination of software and hardware. As an example, the target detection system for spatial fusion of visible light images and infrared images of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the target detection method for spatial fusion of visible light images and infrared images of the present invention. For example, the processor in the form of a hardware decoding processor can adopt one or more application specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs) or other electronic components.

[0084] The modules involved in the embodiments of the present invention may be implemented in software or hardware. The name of a module does not limit the module itself in some cases.

[0085] An electronic device according to an embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, any of the above-mentioned target detection methods for spatial fusion of visible light images and infrared images is implemented. That is to say, an electronic device according to an embodiment of the present invention may include but is not limited to: a processor and a memory; a memory for storing a computer program; a processor for executing the target detection method for spatial fusion of visible light images and infrared images shown in any embodiment of the present invention by calling the computer program.

[0086] In an alternative embodiment, an electronic device is provided, such as Figure 3 As shown, Figure 3 The electronic device 4000 shown includes: a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, such as through a bus 4002. Optionally, the electronic device 4000 may also include a transceiver 4004, which may be used for data interaction between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in actual applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0087] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present invention. Processor 4001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0088] The bus 4002 may include a path to transmit information between the above components. The bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 4002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3In the figure, only one thick line is used to represent the bus 4002, but this does not mean that there is only one bus or one type of bus.

[0089] The memory 4003 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to this.

[0090] The memory 4003 is used to store the application code (computer program) for executing the solution of the present invention, and the execution is controlled by the processor 4001. The processor 4001 is used to execute the application code stored in the memory 4003 to implement the content shown in the above method embodiment.

[0091] Among them, the electronic device can also be a terminal device, and the terminal device can be any terminal device that can install applications, including at least one of a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, a smart TV, and a smart car device.

[0092] It should be noted that Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0093] A computer-readable storage medium according to an embodiment of the present invention stores a computer program, which, when executed by a processor, implements any of the above-mentioned target detection methods for spatial fusion of visible light images and infrared images.

[0094] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0095] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device performs any of the above-mentioned target detection methods for spatial fusion of visible light images and infrared images.

[0096] Computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0097] It should be understood that the flow charts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the module, the program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0098] The computer-readable storage medium provided by the embodiment of the present invention may be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or component.

[0099] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the method shown in the above embodiment.

[0100] The above description is only a preferred embodiment of the present invention and an explanation of the technical principles used. Those skilled in the art should understand that the disclosure scope involved in the present invention is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present invention (but not limited to) by each other.

[0101] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects and represent the definition of a specific order or sequence. The order of use of similar objects can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than the order shown or described.

[0102] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present invention can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0103] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A target detection method for spatial fusion of visible light image and infrared image, characterized in that: include: After time alignment of the visible light camera and the infrared camera, the visible light camera and the infrared camera are used to respectively collect a visible light image and an infrared image at the same time; Performing target detection on the infrared image to obtain a first eigenvector, and performing target detection on the visible light image to obtain a second eigenvector; Using a homography transformation matrix satisfied by a visible light image taken by a visible light camera and an infrared image taken by an infrared camera, transform the second eigenvector to obtain a third eigenvector; Merging the first eigenvector and the third eigenvector to obtain a fourth eigenvector; A fused target list is obtained according to the fourth eigenvector.

2. The target detection method of spatial fusion of visible light image and infrared image according to claim 1, characterized in that: According to the fourth eigenvector, a fused target list is obtained, including: The fourth eigenvector is processed by using a maximum suppression algorithm to obtain the fused target list.

3. The target detection method of spatial fusion of visible light image and infrared image according to claim 1 or 2, characterized in that: The process of performing target detection on the infrared image and the process of performing target detection on the visible light image includes: Performing target detection on the infrared image using the trained first YOLO model; Performing target detection on the visible light image using the trained second YOLO model; The trained first YOLO model and the trained second YOLO model have the same network structure.

4. The target detection method of spatial fusion of visible light image and infrared image according to claim 1 or 2, characterized in that: The visible light camera and the infrared camera are: a visible light camera and an infrared camera of a dual-spectrum integrated machine.

5. A target detection system for spatial fusion of visible light image and infrared image, characterized in that: It includes an image acquisition module, a target detection module, a feature vector transformation module, a feature vector merging module and a feature vector processing module; The image acquisition module is used to: after time alignment of the visible light camera and the infrared camera, use the visible light camera and the infrared camera to respectively collect a visible light image and an infrared image at the same time; The target detection module is used to: perform target detection on the infrared image to obtain a first feature vector, and perform target detection on the visible light image to obtain a second feature vector; The eigenvector transformation module is used to transform the second eigenvector using a homography transformation matrix satisfied by a visible light image taken by a visible light camera and an infrared image taken by an infrared camera to obtain a third eigenvector; The feature vector merging module is used to: merge the first feature vector and the third feature vector to obtain a fourth feature vector; The feature vector processing module is used to obtain a fused target list according to the fourth feature vector.

6. The target detection system for spatial fusion of visible light image and infrared image according to claim 5, characterized in that: The feature vector processing module is specifically used to: use a maximum suppression algorithm to process the fourth feature vector to obtain the fused target list.

7. The target detection system for spatial fusion of visible light image and infrared image according to claim 5 or 6, characterized in that: The target detection module is specifically used for: Performing target detection on the infrared image using the trained first YOLO model; Performing target detection on the visible light image using the trained second YOLO model; The trained first YOLO model and the trained second YOLO model have the same network structure.

8. The target detection system for spatial fusion of visible light image and infrared image according to claim 5 or 6, characterized in that: The visible light camera and the infrared camera are: a visible light camera and an infrared camera of a dual-spectrum integrated machine.

9. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the target detection method of spatial fusion of a visible light image and an infrared image as claimed in any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for target detection by spatial fusion of a visible light image and an infrared image as claimed in any one of claims 1 to 4 is implemented.

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