Object detection method, device and equipment and storage medium

Abstract

The invention discloses an object detection method, device and equipment and a storage medium, when an object passes through a landing door of an elevator, a depth sensor is controlled to scan the object line by line to obtain a depth image of the object, and the occupied area of the object is calculated based on the number of pixels of the depth image; the physical height of the pixel is calculated based on the depth information of the pixel of the depth image, the integral of the occupied area on the physical height of the pixel is calculated, the occupied volume of the object is obtained, the object entering and exiting the car is scanned line by line through the depth sensor, the occupied area and volume of the object can be accurately calculated, and the detection accuracy is improved. And a reliable basis is provided for elevator dispatching.

Description

Technical Field

[0001] The present invention relates to object detection technology, and in particular to an object detection method, device, equipment and storage medium. Background Art

[0002] An elevator is a permanent transportation device that serves several specific floors of a building and whose car runs on at least two rows of rigid guide rails that are perpendicular to the horizontal plane or have an inclination angle of less than 15° to the plumb line.

[0003] In order to improve the transportation efficiency of elevators, some elevators are installed with two-dimensional or three-dimensional sensors to detect the volume occupied by objects in the car, and evaluate the congestion in the car based on the occupied volume. The elevator is further dispatched based on the congestion in the car, thereby improving the transportation efficiency of the elevator.

[0004] When the object is relatively small, the error may not be large. Once the object is large, due to the sensor's field of view and the object's self-occlusion, the sensor cannot fully image the large object, resulting in a large measurement error. Summary of the invention

[0005] The present invention provides an object detection method, device, equipment and storage medium to improve detection accuracy and provide a reliable basis for elevator dispatching.

[0006] In a first aspect, the present invention provides an object detection method, comprising:

[0007] When an object passes through a landing door of an elevator, the depth sensor is controlled to scan the object line by line to obtain a depth image of the object;

[0008] Calculating an occupied area of ​​the object based on the number of pixels of the depth image;

[0009] Calculating a physical height of a pixel based on depth information of the pixel of the depth image;

[0010] The integral of the occupied area and the physical height of the pixel is calculated to obtain the occupied volume of the object.

[0011] Optionally, controlling the depth sensor to scan the object line by line to obtain a depth image of the object includes:

[0012] Determine whether the width of the scanned data of the current line is greater than a preset width, and whether the depth of the scanned data of the current line is less than a preset depth;

[0013] If yes, the scan data of the current row is used as the starting boundary of the object;

[0014] Taking each subsequent row of scan data as target row of scan data, and determining whether a width difference between the target row of scan data and a row of scan data next to the target row of scan data is less than a preset value;

[0015] If so, the target row scan data is used as the termination boundary of the object.

[0016] Optionally, calculating the occupied area of ​​the object based on the number of pixels of the depth image includes:

[0017] Counting the number of pixels of the depth image of the object;

[0018] Calculate the actual area corresponding to a single pixel in the depth image based on the ground sampling interval of the depth sensor;

[0019] The occupied area of ​​the object is obtained by multiplying the number of pixels of the depth image by the actual area corresponding to a single pixel.

[0020] Optionally, calculating the actual area corresponding to a single pixel in the depth image based on a ground sampling interval of the depth sensor includes:

[0021] Calculating the product of the pixel size of the depth sensor and the installation height of the depth sensor to obtain a first value;

[0022] Calculating a quotient of the first value and the focal length of the depth sensor to obtain a ground sampling interval of the depth sensor;

[0023] The square of the ground sampling interval is calculated to obtain the actual area corresponding to a single pixel in the depth image.

[0024] Optionally, calculating the physical height of the pixel based on the depth information of the pixel of the depth image includes:

[0025] The difference between the distance from the depth sensor to the ground and the depth information of the pixel is calculated to obtain the physical height of the pixel.

[0026] Optionally, the depth sensor is a multi-row line scanning depth sensor, and the process of controlling the depth sensor to scan the object line by line also includes:

[0027] Get the characteristic attributes of each row of scan data;

[0028] Each line of scan data is tracked based on the characteristic attribute, and a moving direction of each line of scan data is determined as a moving direction of the object.

[0029] Optionally, the object detection method further includes:

[0030] Obtain scanning data of the lobby area and scanning data of the car interior area;

[0031] Determining the boundary of the object based on the scanning data of the lobby area and the scanning data of the car interior area;

[0032] The moving direction of the boundary is used as the moving direction of the object.

[0033] In a second aspect, the present invention further provides an object detection device, comprising:

[0034] A scanning module, used to control the depth sensor to scan the object line by line when the object passes through the elevator door, so as to obtain a depth image of the object;

[0035] An occupied area calculation module, used to calculate the occupied area of ​​the object based on the number of pixels of the depth image;

[0036] A physical height calculation module, configured to calculate the physical height of a pixel based on the depth information of the pixel of the depth image;

[0037] The occupied volume calculation module is used to calculate the integral of the occupied area and the physical height of the pixel to obtain the occupied volume of the object.

[0038] In a third aspect, the present invention further provides an electronic device, comprising:

[0039] one or more processors;

[0040] A storage device for storing one or more programs;

[0041] When the one or more programs are executed by the one or more processors, the one or more processors implement the object detection method provided in the first aspect of the present invention.

[0042] 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 the object detection method provided in the first aspect of the present invention.

[0043] The object detection method provided by the present invention controls the depth sensor to scan the object line by line when the object passes through the floor door of the elevator to obtain a depth image of the object, calculates the occupied area of ​​the object based on the number of pixels in the depth image, calculates the physical height of the pixel based on the depth information of the pixel of the depth image, calculates the integral of the occupied area and the physical height of the pixel to obtain the occupied volume of the object, and scans the object entering and exiting the car line by line through the depth sensor, so as to accurately calculate the occupied area and volume of the object, improve the detection accuracy, and provide a reliable basis for elevator scheduling.

[0044] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0046] Figure 1 A flow chart of an object detection method provided by the present invention;

[0047] Figure 2 A plane projection diagram of an object detection provided by the present invention;

[0048] Figure 3 A schematic diagram of the structure of the object detection device provided by the present invention;

[0049] Figure 4 The present invention provides a schematic structural diagram of an electronic device.

[0050] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0052] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0053] Figure 1 This is a flow chart of an object detection method provided by the present invention. This embodiment can be used to detect objects entering and exiting an elevator to provide a basis for elevator scheduling. The method can be executed by an object detection device provided by an embodiment of the present invention. The device can be implemented by software and / or hardware, and is usually configured in an electronic device, such as Figure 1 As shown, the object detection method includes the following steps:

[0054] S101. When an object passes through a landing door of an elevator, a depth sensor is controlled to scan the object line by line to obtain a depth image of the object.

[0055] Figure 2 The present invention provides an object detection plane projection diagram, such as Figure 2 As shown, a depth sensor is installed above the floor door of the elevator lobby on each floor. The scanning coverage area of ​​the depth sensor can at least cover the area near the floor door. In the present invention, this area is called the door area, the area on the side where the door area extends to the elevator lobby is called the area outside the lobby, and the area on the side where the door area extends to the car is called the area inside the car.

[0056] In the embodiment of the present invention, in the object ( Figure 2 When the object (the shaded part in the figure) passes through the elevator door, the depth sensor is controlled to scan the object line by line to obtain the depth image of the object. Exemplarily, each time the elevator door is opened, the depth sensor is triggered to start working, and the object passing through the door area is scanned line by line. When the object completely moves out of the door area and the door is closed, the depth sensor stops working to obtain the depth image of the object.

[0057] Exemplarily, in an embodiment of the present invention, after the depth sensor starts scanning, it is determined whether the width of the current row of scan data is greater than the preset width, and whether the depth of the current row of scan data is less than the preset depth. If so, the current row of scan data is used as the starting boundary of the object; if not, it is continued to be determined whether the width of the row of scan data is greater than the preset width until the starting boundary of the object is found. After finding the starting boundary of the object, each subsequent row of scan data is used as the target row of scan data, and it is determined whether the difference in width between the target row of scan data and the next row of scan data of the target row of scan data is less than the preset value. If so, the target row of scan data is used as the ending boundary of the object; if not, it means that the object is still continuous, and the ending boundary is continued to be found until the ending boundary of the object is found.

[0058] After determining the starting boundary and the ending boundary of the object, the area between the starting boundary and the ending boundary, which is composed of pixels whose depth values ​​are greater than a threshold, is used as the depth image of the object.

[0059] S102: Calculate the occupied area of ​​the object based on the number of pixels in the depth image.

[0060] In the embodiment of the present invention, there is a certain relationship between the size of a single pixel of the depth image and the physical size in the physical world. Therefore, the actual occupied area of ​​the object can be calculated based on the number of pixels of the depth image of the object.

[0061] Exemplarily, in an embodiment of the present invention, the number of pixels of the depth image of the object is counted, the actual area corresponding to a single pixel in the depth image is calculated based on the ground sampling distance (GSD) of the depth sensor, and the number of pixels in the depth image is multiplied by the actual area corresponding to a single pixel to obtain the occupied area of ​​the object. The ground sampling distance refers to the ground size corresponding to a single pixel in a digital image, which describes the distance between the center points of two consecutive pixels.

[0062] Specifically, the product of the pixel size of the depth sensor and the installation height of the depth sensor is calculated to obtain a first value, the quotient of the first value and the focal length of the depth sensor is calculated to obtain the ground sampling interval of the depth sensor, and the square of the ground sampling interval is calculated to obtain the actual area corresponding to a single pixel in the depth image. Exemplarily, the calculation formula of the ground sampling interval is as follows:

[0063]

[0064] Among them, GSD is the ground sampling interval, H is the installation height of the depth sensor (that is, the height from the depth sensor to the ground), a is the pixel size of the depth sensor (that is, the side length of the pixel), and f is the focal length of the depth sensor.

[0065] S103: Calculate the physical height of the pixel based on the depth information of the pixel in the depth image.

[0066] In the embodiment of the present invention, the depth information of the pixel of the depth image includes the depth value of the pixel, that is, the distance from the object to the depth sensor, so the physical height of the pixel can be calculated based on the depth information of the pixel of the depth image. Specifically, the difference between the distance from the depth sensor to the ground (that is, the installation height) and the depth information of the pixel is calculated to obtain the physical height of the pixel.

[0067] S104: Calculate the integral of the occupied area and the physical height of the pixel to obtain the occupied volume of the object.

[0068] In the embodiment of the present invention, after the occupied area of ​​the object and the physical height of each pixel are calculated, the occupied volume of the object is obtained by calculating the integral of the occupied area with respect to the physical height of the pixel. Specifically, the product of the actual area corresponding to each pixel and the physical height of the pixel is calculated to obtain the micro volume of the part of the object corresponding to the pixel, and the micro volumes corresponding to all pixels are summed to obtain the occupied volume of the object.

[0069] The object detection method provided by the present invention controls the depth sensor to scan the object line by line when the object passes through the floor door of the elevator to obtain a depth image of the object, calculates the occupied area of ​​the object based on the number of pixels in the depth image, calculates the physical height of the pixel based on the depth information of the pixel of the depth image, calculates the integral of the occupied area and the physical height of the pixel to obtain the occupied volume of the object, and scans the object entering and exiting the car line by line through the depth sensor, so as to accurately calculate the occupied area and volume of the object, improve the detection accuracy, and provide a reliable basis for elevator scheduling.

[0070] In some embodiments of the present invention, the depth sensor is a multi-row line scanning depth sensor. In the process of controlling the depth sensor to scan the object line by line, the moving direction of the object can also be determined, that is, whether the object is entering or exiting the car. Specifically, the characteristic attributes of each line of scan data are obtained. The characteristic attributes may include the width of each line of scan data (that is, the number of pixels of each line of the object), the offset of each line of scan data relative to a reference (for example, the center line of the door), and the depth value of the pixel. The embodiments of the present invention are not limited here. Each line of scan data is tracked based on the characteristic attributes, and the moving direction of each line of scan data is determined as the moving direction of the object.

[0071] In some special cases, if the objects entering and exiting the car are regular in shape, that is, the characteristic attributes of each line of scan data are the same, it is impossible to track the moving direction of the object through the characteristic attributes. In this case, a depth sensor with a larger scanning coverage area can be used. The scanning coverage area can cover the lobby area, the door area, and the car area. When the moving direction of the object cannot be determined through the scanning data in the door area, the scanning data of the lobby area and the car area are obtained, and the boundary of the object is determined based on the scanning data of the lobby area and the car area, and the moving direction of the boundary is used as the moving direction of the object.

[0072] The present invention also provides an object detection device, Figure 3 The structure diagram of the object detection device provided by the present invention is as follows: Figure 3 As shown, the object detection device includes:

[0073] The scanning module 201 is used to control the depth sensor to scan the object line by line when the object passes through the elevator door to obtain a depth image of the object;

[0074] An occupied area calculation module 202, configured to calculate the occupied area of ​​the object based on the number of pixels of the depth image;

[0075] A physical height calculation module 203, configured to calculate the physical height of a pixel based on the depth information of the pixel of the depth image;

[0076] The occupied volume calculation module 204 is used to calculate the integral of the occupied area and the physical height of the pixel to obtain the occupied volume of the object.

[0077] In some embodiments of the present invention, the scanning module 201 includes:

[0078] A first judgment submodule, used to judge whether the width of the scanned data of the current line is greater than a preset width, and whether the depth of the scanned data of the current line is less than a preset depth;

[0079] A starting boundary determination submodule, configured to use the current row of scan data as the starting boundary of the object when the width of the current row of scan data is greater than a preset width and the depth of the current row of scan data is less than a preset depth;

[0080] A second judgment submodule is used to use each subsequent row of scan data as target row of scan data, and judge whether a width difference between the target row of scan data and a row of scan data next to the target row of scan data is less than a preset value;

[0081] The termination boundary determination submodule is used to use the target row scan data as the termination boundary of the object when the difference between the width of the target row scan data and the next row scan data of the target row scan data is less than a preset value.

[0082] In some embodiments of the present invention, the occupied area calculation module 202 includes:

[0083] A pixel number counting submodule, used to count the number of pixels of the depth image of the object;

[0084] An actual area calculation submodule, used to calculate the actual area corresponding to a single pixel in the depth image based on the ground sampling interval of the depth sensor;

[0085] The occupied area calculation submodule is used to multiply the number of pixels of the depth image by the actual area corresponding to a single pixel to obtain the occupied area of ​​the object.

[0086] In some embodiments of the present invention, the actual area calculation submodule includes:

[0087] A product unit, used to calculate the product of the pixel size of the depth sensor and the installation height of the depth sensor to obtain a first value;

[0088] a division unit, configured to calculate a quotient of the first value and the focal length of the depth sensor to obtain a ground sampling interval of the depth sensor;

[0089] The squaring unit is used to calculate the square of the ground sampling interval to obtain the actual area corresponding to a single pixel in the depth image.

[0090] In some embodiments of the present invention, the physical height calculation module 203 includes:

[0091] The difference calculation submodule is used to calculate the difference between the distance from the depth sensor to the ground and the depth information of the pixel to obtain the physical height of the pixel.

[0092] In some embodiments of the present invention, the depth sensor is a multi-row line scanning depth sensor, and in the process of controlling the depth sensor to scan the object line by line, the object detection device further includes:

[0093] A feature attribute acquisition module is used to acquire the feature attributes of each line of scan data;

[0094] The first moving direction determining module is used to track each line of scanning data based on the characteristic attribute, and determine the moving direction of each line of scanning data as the moving direction of the object.

[0095] In some embodiments of the present invention, the object detection device further includes:

[0096] A data acquisition module, used to acquire scanning data of the lobby area and scanning data of the car interior area;

[0097] A boundary determination module, configured to determine the boundary of the object based on the scanning data of the lobby area and the scanning data of the car interior area;

[0098] The second moving direction determining module is used to use the moving direction of the boundary as the moving direction of the object.

[0099] The above-mentioned object detection device can execute the object detection method provided by the aforementioned embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the object detection method.

[0100] Figure 4 A schematic diagram of the structure of an electronic device provided by the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0101] like Figure 4 As shown, the electronic device includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0102] A number of components in the electronic device are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0103] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as an object detection method.

[0104] In some embodiments, the object detection method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the object detection method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the object detection method in any other appropriate manner (e.g., by means of firmware).

[0105] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0106] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0107] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 of the foregoing.

[0108] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0109] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0110] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0111] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the object detection method provided in any embodiment of the present application.

[0112] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can 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 the case of a remote computer, the remote computer can 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 can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0113] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0114] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An object detection method, characterized in that: include: When an object passes through a landing door of an elevator, the depth sensor is controlled to scan the object line by line to obtain a depth image of the object; Calculating an occupied area of ​​the object based on the number of pixels of the depth image; Calculating a physical height of a pixel based on depth information of the pixel of the depth image; The integral of the occupied area and the physical height of the pixel is calculated to obtain the occupied volume of the object.

2. The object detection method according to claim 1, characterized in that: Controlling the depth sensor to scan the object line by line to obtain a depth image of the object, including: Determine whether the width of the scanned data of the current line is greater than a preset width, and whether the depth of the scanned data of the current line is less than a preset depth; If yes, the scan data of the current row is used as the starting boundary of the object; Taking each subsequent row of scan data as target row of scan data, and determining whether a width difference between the target row of scan data and a row of scan data next to the target row of scan data is less than a preset value; If so, the target row scan data is used as the termination boundary of the object.

3. The object detection method according to claim 1, characterized in that: Calculating the occupied area of ​​the object based on the number of pixels of the depth image, comprising: Counting the number of pixels of the depth image of the object; Calculate the actual area corresponding to a single pixel in the depth image based on the ground sampling interval of the depth sensor; The occupied area of ​​the object is obtained by multiplying the number of pixels of the depth image by the actual area corresponding to a single pixel.

4. The object detection method according to claim 3, characterized in that: Calculating an actual area corresponding to a single pixel in the depth image based on a ground sampling interval of the depth sensor includes: Calculating the product of the pixel size of the depth sensor and the installation height of the depth sensor to obtain a first value; Calculating a quotient of the first value and the focal length of the depth sensor to obtain a ground sampling interval of the depth sensor; The square of the ground sampling interval is calculated to obtain the actual area corresponding to a single pixel in the depth image.

5. The object detection method according to any one of claims 1 to 4, characterized in that: Calculating the physical height of the pixel based on the depth information of the pixel of the depth image includes: The difference between the distance from the depth sensor to the ground and the depth information of the pixel is calculated to obtain the physical height of the pixel.

6. The object detection method according to any one of claims 1 to 4, characterized in that: The depth sensor is a multi-line scanning depth sensor, and in the process of controlling the depth sensor to scan the object line by line, the process further includes: Get the characteristic attributes of each row of scan data; Each line of scan data is tracked based on the characteristic attribute, and a moving direction of each line of scan data is determined as a moving direction of the object.

7. The object detection method according to claim 6, characterized in that: Also includes: Obtain scanning data of the lobby area and scanning data of the car interior area; Determining the boundary of the object based on the scanning data of the lobby area and the scanning data of the car interior area; The moving direction of the boundary is used as the moving direction of the object.

8. An object detection device, characterized in that: include: A scanning module, used to control the depth sensor to scan the object line by line when the object passes through the elevator door, so as to obtain a depth image of the object; An occupied area calculation module, used to calculate the occupied area of ​​the object based on the number of pixels of the depth image; A physical height calculation module, configured to calculate the physical height of a pixel based on the depth information of the pixel of the depth image; The occupied volume calculation module is used to calculate the integral of the occupied area and the physical height of the pixel to obtain the occupied volume of the object.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the object detection method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the object detection method as described in any one of claims 1 to 7 is implemented.

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