CN111339920A - Cash adding behavior detection method, device and system, storage medium and electronic terminal - Google Patents
Cash adding behavior detection method, device and system, storage medium and electronic terminal Download PDFInfo
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Abstract
The invention provides a method, a device and a system for detecting a money adding behavior, a storage medium and an electronic terminal, wherein the method comprises the following steps: acquiring a monitoring image; acquiring a safe box area in the monitoring image; inputting the monitoring image into a human body posture detection model to obtain coordinates of human body joint points; the human body joint point coordinates include: coordinates of human hand joint points and coordinates of human skeleton joint points; judging whether the safe box area contains the coordinates of the hand joint points of the human body; if the safe box area contains the coordinates of the joint points of the hands of the human body, judging whether two persons exist according to the coordinates of the joint points of the skeleton of the human body; if two persons exist, judging whether one face exists or not; if a face exists, determining the current bank note adding behavior standard; otherwise, determining that the current money adding behavior is not standard and giving an alarm. The invention aims to provide a technical solution which can effectively and intelligently detect whether the bank note adding behavior in the safe box area is standard or not, and ensures the security and the accuracy of the bank note adding.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a method, a device and a system for detecting a money adding behavior, a storage medium and an electronic terminal.
Background
In the financial field (such as banks, securities, insurance, etc.), a camera device is generally arranged in a safe deposit area for monitoring the safe deposit area.
However, the existing monitoring mode is only to shoot a video, and whether the operation of a worker in a safe box area is standard or not cannot be detected. For example: the presence of a single person in the safe area does not comply with the business operations specifications clearly defined by the bank, and correct operation should be possible with and only two persons present in the safe area and two persons having to stand back to back. Therefore, the existing safe box area monitoring cannot analyze and alarm the money adding behavior, and the intelligent degree and the safety are to be improved urgently.
Content of application
In view of the above-mentioned shortcomings of the prior art, it is an object of the present invention to provide a method, an apparatus, a system, a storage medium and an electronic terminal for detecting a cash adding action, which are used to solve the problems in the prior art.
To achieve the above and other related objects, a first aspect of the present invention provides a method for detecting a cash-in behavior applicable to a safe area, including: acquiring a monitoring image; acquiring a safe box area in the monitoring image; inputting the monitoring image into a human body posture detection model to obtain coordinates of human body joint points; the human body joint point coordinates include: coordinates of human hand joint points and coordinates of human skeleton joint points; judging whether the safe box area contains the coordinates of the hand joint points of the human body; if the safe box area contains the coordinates of the joint points of the hands of the human body, judging whether two persons exist according to the coordinates of the joint points of the skeleton of the human body; if two persons exist, judging whether one face exists or not; if a face exists, determining the current bank note adding behavior standard; otherwise, determining that the current money adding behavior is not standard and giving an alarm.
In some embodiments of the first aspect of the present invention, acquiring the safe area in the monitoring image includes: and acquiring pixel information of the safe in the monitored image by using an image processing algorithm, and identifying the safe area in the monitored image according to the difference between the pixels of the safe area and the background pixels of the image.
In some embodiments of the first aspect of the present invention, if the safe area includes coordinates of joint points of the hand of the human body, determining whether two persons exist according to the coordinates of joint points of the skeleton of the human body includes: judging whether two groups of different human body skeleton joint point coordinates exist in the obtained human body joint point coordinates; if two groups of different human body skeleton joint point coordinates exist, judging that two persons exist; otherwise, judging that two persons do not exist.
In some embodiments of the first aspect of the present invention, in a case that two persons are determined to be present, let the coordinates of human hand joint points in the obtained coordinates of human joint points be H1, and let two sets of coordinates of human skeleton joint points in the coordinates of human joint points be B1 and B2, respectively; the method comprises the following steps: judging an operator of the safety box according to the membership between the human hand joint point coordinate H1 and the two groups of human skeleton node coordinates B1 and B2; if the human hand joint point coordinate H1 belongs to the human skeleton joint point coordinate B1, the fact that a person corresponding to the human skeleton joint point coordinate B1 operates the safety box is judged; and if the human body hand joint point coordinate H1 belongs to the human body skeleton joint point coordinate B2, judging that the person corresponding to the human body skeleton joint point coordinate B2 operates the safety box.
In some embodiments of the first aspect of the present invention, the determining whether there is a face includes: if the human hand joint point coordinate H1 belongs to the human skeleton joint point coordinate B1, judging that a human face exists when the human face is detected in the human skeleton joint point coordinate B1 and the human face is not detected in the human skeleton joint point coordinate B2; if the human hand joint point coordinate H1 belongs to the human skeleton joint point coordinate B2, it is determined that there is a human face when a human face is detected in the human skeleton joint point coordinate B2 and a human face is not detected in the human skeleton joint point coordinate B1.
To achieve the above and other related objects, a second aspect of the present invention provides a cash loading behavior detecting apparatus adapted for a safe area, comprising: the image acquisition module is used for acquiring a monitoring image; the safety box area acquisition module is used for acquiring a safety box area in the monitoring image; the human body posture detection module is used for inputting the monitoring image into a human body posture detection model to obtain the coordinates of the human body joint points; the human body joint point coordinates include: coordinates of human hand joint points and coordinates of human skeleton joint points; judging whether the safe box area contains the coordinates of the hand joint points of the human body; if the safe box area contains the coordinates of the joint points of the hands of the human body, judging whether two persons exist according to the coordinates of the joint points of the skeleton of the human body; the face detection module is used for judging whether a face exists or not under the condition of judging that two persons exist; the standard detection module is used for determining the current banknote adding behavior standard under the condition that two persons exist and one face exists; otherwise, determining that the current money adding behavior is not standard and giving an alarm.
In order to achieve the above and other related objects, a third aspect of the present invention provides a cash-adding behavior detection system suitable for a safe area, comprising the cash-adding behavior detection apparatus provided by the second aspect of the present invention, and further comprising an alarm apparatus; the alarm device is connected with and controlled by the cash adding behavior detection device so as to give an alarm prompt after receiving an alarm instruction sent by the cash adding behavior detection device.
In some embodiments of the third aspect of the present invention, the alarm device comprises: any one or combination of a plurality of sound generating devices, light emitting devices, display devices, and vibrating devices.
To achieve the above and other related objects, a fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, where the computer program is executed by a processor to implement the method for detecting a cash-in behavior applicable to a safe area.
To achieve the above and other related objects, a fifth aspect of the present invention provides an electronic terminal comprising: a processor and a memory; the memory is used for storing computer programs, and the processor is used for executing the computer programs stored in the memory, so that the terminal executes the cash adding behavior detection method suitable for the safe area.
As described above, the method, the device, the system, the storage medium and the electronic terminal for detecting the cash adding behavior of the invention have the following advantages: the invention aims to provide a technical solution which can effectively and intelligently detect whether the bank note adding behavior in the safe box area is standard or not, and can timely send out an alarm under the condition that the bank note adding behavior is not standard, so that the security and the accuracy of adding bank notes are ensured, and the defects of the prior art are effectively overcome.
Drawings
Fig. 1 is a schematic flow chart illustrating a method for detecting a cash-in behavior in a safe area according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of a human skeletal joint according to an embodiment of the present invention.
FIG. 3 is a diagram illustrating a joint point of a human hand according to an embodiment of the present invention.
Fig. 4 is a schematic structural diagram of a cash-in behavior detection apparatus suitable for a safe area according to an embodiment of the present invention.
Fig. 5 is a schematic structural diagram of a cash-in behavior detection system suitable for a safe area according to an embodiment of the present invention.
Fig. 6 is a schematic structural diagram of an electronic terminal according to an embodiment of the invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It is noted that in the following description, reference is made to the accompanying drawings which illustrate several embodiments of the present invention. It is to be understood that other embodiments may be utilized and that mechanical, structural, electrical, and operational changes may be made without departing from the spirit and scope of the present invention. The following detailed description is not to be taken in a limiting sense, and the scope of embodiments of the present invention is defined only by the claims of the issued patent. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. Spatially relative terms, such as "upper," "lower," "left," "right," "lower," "below," "lower," "above," "upper," and the like, may be used herein to facilitate describing one element or feature's relationship to another element or feature as illustrated in the figures.
In the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "secured," "retained," and the like are to be construed broadly, e.g., as meaning fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Also, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," and/or "comprising," when used in this specification, specify the presence of stated features, operations, elements, components, items, species, and/or groups, but do not preclude the presence, or addition of one or more other features, operations, elements, components, items, species, and/or groups thereof. The terms "or" and/or "as used herein are to be construed as inclusive or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a; b; c; a and B; a and C; b and C; A. b and C ". An exception to this definition will occur only when a combination of elements, functions or operations are inherently mutually exclusive in some way.
Because the existing monitoring mode is only to shoot videos, whether the operation of workers in the safe area is standard or not cannot be detected. For example: the presence of a single person in the safe area does not comply with the business operations specifications clearly defined by the bank, and correct operation should be possible with and only two persons present in the safe area and two persons having to stand back to back. Therefore, the monitoring scheme aiming at the safe box area in the prior art cannot analyze and alarm the money adding behavior, and the intelligent degree and the safety are in urgent need to be improved.
In view of the defects in the prior art, the invention provides the method, the device, the terminal and the medium for detecting the cash adding behavior in the safe area, which can detect and analyze the cash adding behavior and give an alarm in time according to the detection and analysis result, thereby ensuring the security of the cash adding.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions in the embodiments of the present invention are further described in detail by the following embodiments in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example one
Fig. 1 shows a schematic flow chart of a method for detecting a banknote adding behavior in a safe area according to an embodiment of the present invention. The method for detecting the bill adding behavior of the embodiment mainly comprises the steps of S11-S16.
Step S11: the monitoring image is acquired, for example, the monitoring image is read from a video stream, or the image can be taken in real time.
Specifically, the types of image pickup apparatuses include, but are not limited to: a video camera, a camera, an image pickup module integrated with an optical system or a CCD chip, an image pickup module integrated with an optical system and a CMOS chip, and the like, but the present embodiment is not limited thereto.
Step S12: and acquiring the safe box area in the monitoring image.
Specifically, the image processing algorithm can be used for obtaining the pixel information of the safe in the image, and the safe area in the image to be detected is identified according to the characteristic that the pixels of the safe are different from the background pixels of the image. For example: and acquiring pixel information of a safe area in the image to be detected by using an ImageMagick image processing tool, and writing the acquired pixel information into a code so as to identify the safe area from the image. Because there are many image processing algorithms in the prior art, and the processing processes of the image processing algorithms in the embodiment are similar, they are not listed one by one.
Step S13: inputting the monitoring image into a human body posture detection model to obtain coordinates of human body joint points; the human body joint point coordinates include: the coordinates of the human hand joint points and the coordinates of the human skeleton joint points.
The human body posture detection model is a detection model for estimating the human body posture by correctly associating the detected human body key points in the picture. Human body key points generally correspond to joints on the human body with a certain degree of freedom, such as: neck, shoulder, elbow, wrist, waist, knee, or ankle, etc.
In an optional implementation manner of this embodiment, a human body detection algorithm based on openpos is used to detect whether there are human body hand features in the safe area. The OpenPose is a posture estimation model based on a convolutional neural network, can realize posture estimation of human body actions, facial expressions, finger motions and the like, is suitable for single-person detection and multi-person detection, and has good robustness.
The skeleton joint point coordinates of the human body in the OpenPose pose estimation model are denoted as bpoints, and comprise 25 joint points of the human body skeleton. As shown in fig. 2, the 25 human skeletal joint points include: nose 200, neck 201, right shoulder 202, right elbow 203, right wrist 204, left shoulder 205, left elbow 206, left wrist 207, sacrum 208, right crotch 209, right knee 210, right ankle 211, left crotch 212, left knee 213, left ankle 214, right eye 215, left eye 216, right ear 217, left ear 218, left toe (1)219, left toe (2)220, left heel 221, right toe (1)222, right toe (2)223, and right heel 224.
The coordinates of the joint points of the human hand are denoted as hpoints in the openpos pose estimation model, and comprise 42 joint points of the two hands of the human body. As shown in fig. 3, taking the left hand as an example for illustration, since the two hands of the human body are symmetrical to each other, the structure of the joint point of the right hand can be known based on the joint point of the left hand. The 21 joints of the left hand of the human body include: palm root (0), palm abdomen (1), thumb root (2), thumb middle (3), thumb tip (4), index finger root (5), index finger near (6), index finger middle (7), index finger tip (8), middle finger root (9), middle finger near (10), middle finger middle (11), middle finger tip (12), ring finger root (13), ring finger near (14), ring finger middle (15), ring finger tip (16), little finger root (17), little finger near (18), little finger middle (19) and little finger tip (20).
Optionally, the identification method of the skeleton joint point coordinates bpoints and the hand joint points hpoints of all the people in the image to be detected is as follows:
for an image frame, the corresponding detection result is expressed as:
vector<pair<vector<bpoints>,vector<hpoints>>>pose；
wherein, the detection result pos is a container, each element of which represents all the joint point information of one person; for each element in the container, two sub-containers are contained, representing the human skeleton joint point information and the hand joint point information, respectively.
In this embodiment, the image to be detected may be input into the openpos model, and it is determined whether the hand joint point coordinates hpoints of the human body are acquired in the safe area of the image to be detected. If the hand joint point coordinates hpoints of the human body cannot be acquired in the safe area of the image to be detected, the situation that hands do not appear in the safe area of the image to be detected is shown; if the hand joint point coordinates hpoints of the human body are acquired in the safe area of the image to be detected, the appearance of the human hand in the safe area of the image to be detected is indicated, and the hand is marked as H1.
It should be noted that the human body posture detection algorithm in this embodiment is not limited to the openpos-based human body detection algorithm, and may also be implemented by using other human body posture detection algorithms, for example: the gesture detection algorithm based on DNN or the cascaded DNN-based gesture detection algorithm is not limited in this embodiment, for example, to detect the hand features of a human body. The DNN deep neural network can capture all contexts of each human body skeleton joint point, and each joint point regression uses a whole image; the cascaded DNN-based attitude detection algorithm firstly carries out rough attitude estimation on the whole image and then uses a plurality of DNN-based regressors to optimize a prediction result on neighborhood sub-images (with higher resolution) of the joint points, and the algorithm can improve the positioning accuracy of the joint points.
Step S14: and judging whether the safe box area contains the coordinates of the hand joint points of the human body.
Step S15: and if the safe box area contains the coordinates of the joint points of the hands of the human body, judging whether two persons exist according to the coordinates of the joint points of the skeleton of the human body.
Specifically, the monitoring image is input into a human body posture detection model, and whether two groups of different human body skeleton joint point coordinates are obtained is judged; if two groups of different human body skeleton joint point coordinates are obtained, judging that two persons exist; if not, judging that two persons do not exist.
For example, the image to be measured is input into the OpenPose model, and the human joint node coordinates bpoints are output. If two groups of different human body skeleton joint point coordinates bpoints are obtained from the safe area of the image to be detected and are respectively marked as B1 and B2, two persons are shown in the safe area; if only one group of human body skeleton joint point coordinates or multiple groups of same human body skeleton joint point coordinates are obtained from the safe box area of the image to be detected, only one person appears in the safe box area.
Further, respectively judging the affiliation relationship between a human hand joint point coordinate H1 appearing in the safe area and two different groups of human skeleton joint point coordinates B1 and B2; if the human body hand joint point coordinate H1 belongs to the human body skeleton joint point coordinate B1, it is indicated that a person with the human body skeleton joint point coordinate B1 is operating the safety box; if the human body hand joint point coordinate H1 belongs to the human body skeleton joint point coordinate B2, the fact that the person with the human body skeleton joint point coordinate B2 is operating the safety box is indicated.
Step S16: and if two persons exist, judging whether one face exists or not.
It should be noted that the face detection algorithm in this embodiment includes, but is not limited to: an MTCNN Face detection algorithm, a Cascade CNN Face detection algorithm, a DenseBox Face detection algorithm, a Faceness-Net Face detection algorithm, an HR Face detection algorithm, a Face R-CNN Face detection algorithm, or an SSH Face detection algorithm, etc., which is not limited in this embodiment. And identifying the number of human faces in the safe box area of the image to be detected based on the human face detection algorithms.
Step S17: and if a face exists, determining the current bill adding behavior specification.
Step S18: otherwise, determining that the current money adding behavior is not standard and giving an alarm.
Specifically, if two persons and one face are not detected at the same time, it is indicated that the current banknote adding behavior is not standard, or a situation of single person operation occurs, or a situation that two persons do not stand back to back occurs, and the like, so an alarm instruction should be sent to timely correct and standardize the wrong banknote adding behavior, and the security and the accuracy of banknote adding are guaranteed.
In an optional implementation manner of this embodiment, the alarm device may be a sound-emitting device (such as a buzzer or a speaker), a light-emitting device (such as an indicator light), a display device (such as a display screen), or a vibrating device (such as a vibrating motor), and the present embodiment is not limited. The buzzer can sound to send out an alarm prompt, the loudspeaker can send out the alarm prompt through voice broadcasting, the indicator lamp can send out the alarm prompt through lighting or flickering, the display screen can send out the alarm prompt through displaying characters, and the vibrating motor can send out the alarm prompt through vibrating.
It should be understood that the cash-in action described in this embodiment may occur at various types of financial institution locations, such as banks, security companies, insurance companies, trust companies, fund management companies, or lending companies, to name a few. In fact, the technical scheme of the invention can be suitable for all financial institution business places needing to use the safe box to add the money.
In addition, the detection method provided by this embodiment may be used not only to detect the cash-in behavior of the safe area, but also to detect other behaviors that are the same as or similar to the operation specification of the cash-in behavior, for example: the safe is added with precious articles such as gold, jewelry or jewelry and the like, and the embodiment is not limited.
It should be noted that the method for detecting the banknote adding behavior in the safe area according to the embodiment can be applied to various hardware devices. Examples of the hardware devices include arm (advanced RISC machines) controllers, fpga (field programmable Gate array) controllers, soc (system on chip) controllers, dsp (digital signal processing) controllers, mcu (micro controller unit) controllers, and the like; the hardware device may also be a computer that includes components such as memory, memory controllers, one or more processing units (CPUs), peripheral interfaces, RF circuits, audio circuits, speakers, microphones, input/output (I/O) subsystems, display screens, other output or control devices, and external ports; the computer includes, but is not limited to, Personal computers such as desktop computers, notebook computers, tablet computers, smart phones, smart televisions, Personal Digital Assistants (PDAs), and the like. In other embodiments, the hardware device may also be a server, where the server may be arranged on one or more entity servers according to various factors such as functions and loads, or may be formed by a distributed or centralized server cluster, and this embodiment is not limited in this embodiment.
Therefore, the technical scheme provided by the embodiment overcomes the defects in the prior art, provides the detection method which can effectively and intelligently detect whether the money adding behavior in the safe box area is standard or not, and timely sends out an alarm under the condition of detecting that the money adding behavior is abnormal, so that the safety and the accuracy of money adding are ensured.
Example two
Fig. 4 shows a schematic structural diagram of a cash-in behavior detection apparatus suitable for a safe area according to an embodiment of the present invention. The money adding behavior detection device of the embodiment includes an image acquisition module 41, a safe area acquisition module 42, a human body posture detection module 43, a human face detection module 44 and a specification detection module 45.
The image obtaining module 41 is configured to obtain a monitoring image; the safe area obtaining module 42 is configured to obtain a safe area in the monitoring image; the human body posture detection module 43 is used for inputting the monitoring image into a human body posture detection model to obtain coordinates of human body joint points; the human body joint point coordinates include: coordinates of human hand joint points and coordinates of human skeleton joint points; judging whether the safe box area contains the coordinates of the hand joint points of the human body; if the safe box area contains the coordinates of the joint points of the hands of the human body, judging whether two persons exist according to the coordinates of the joint points of the skeleton of the human body; the face detection module 44 is configured to determine whether a face exists in a case where two persons are determined to exist; the specification detection module 45 is used for determining the current banknote adding behavior specification under the condition that two persons exist and one face exists; otherwise, determining that the current money adding behavior is not standard and giving an alarm.
It should be understood that the cash-in action described in this embodiment may occur at various types of financial institution locations, such as banks, security companies, insurance companies, trust companies, fund management companies, or lending companies, to name a few. In fact, the technical scheme of the invention can be suitable for all financial institution business places needing to use the safe box to add the money.
In addition, the detection method provided by this embodiment may be used not only to detect the cash-in behavior of the safe area, but also to detect other behaviors that are the same as or similar to the operation specification of the cash-in behavior, for example: the safe is added with precious articles such as gold, jewelry or jewelry and the like, and the embodiment is not limited.
It should be noted that, since the implementation of the cash-adding behavior detection apparatus in this embodiment is similar to the implementation of the cash-adding behavior detection method in the first embodiment, no further description is given.
It should be understood that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the image recognition module may be a processing element separately set up, or may be implemented by being integrated into a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and the function of the image recognition module may be called and executed by a processing element of the apparatus. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.
For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when one of the above modules is implemented in the form of a Processing element scheduler code, the Processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).
EXAMPLE III
Fig. 5 is a schematic structural diagram showing a banknote adding behavior detection system suitable for a safe area according to an embodiment of the present invention. The cash-in behavior detection system of the present embodiment includes a cash-in behavior detection device 51 and an alarm device 52.
The banknote adding device 51 is the device described in the second embodiment, and thus the description of this embodiment is omitted. The alarm device 52 is connected to and controlled by the cash-in behavior detection device, so as to give an alarm after receiving an alarm instruction sent by the cash-in behavior detection device.
Specifically, the alarm device 52 may be a sound device (such as a buzzer or a speaker), a light device (such as an indicator light), a display device (such as a display screen), or a vibration device (such as a vibration motor), and the like, and the embodiment is not limited. The buzzer can sound to send out an alarm prompt, the loudspeaker can send out the alarm prompt through voice broadcasting, the indicator lamp can send out the alarm prompt through lighting or flickering, the display screen can send out the alarm prompt through displaying characters, and the vibrating motor can send out the alarm prompt through vibrating.
Example four
Fig. 6 is a schematic structural diagram of an electronic terminal according to an embodiment of the present invention. This example provides an electronic terminal, includes: a processor 61, a memory 62, a communicator 63; the memory 62 is connected with the processor 61 and the communicator 63 through a system bus to complete mutual communication, the memory 62 is used for storing computer programs, the communicator 63 is used for communicating with other equipment, and the processor 61 is used for operating the computer programs, so that the electronic terminal executes the steps of the cash adding behavior detection method suitable for the safe area.
The above-mentioned system bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The system bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus. The communication interface is used for realizing communication between the database access device and other equipment (such as a client, a read-write library and a read-only library). The Memory may include a Random Access Memory (RAM), and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
EXAMPLE five
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the method for detecting a cash-in behavior applicable to a safe area.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the above method embodiments may be performed by hardware associated with a computer program. The aforementioned computer program may be stored in a computer readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
In summary, the present invention provides a method, an apparatus, a system, a storage medium and an electronic terminal for detecting a cash-in behavior, and aims to provide a technical solution capable of effectively and intelligently detecting whether the cash-in behavior in a safe is normal or not, and timely issuing an alarm when detecting that the cash-in behavior is abnormal, thereby ensuring the security and accuracy of cash-in, and effectively overcoming the defects of the prior art. Therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (9)
1. A cash adding behavior detection method suitable for a safe box area is characterized by comprising the following steps:
acquiring a monitoring image;
acquiring a safe box area in the monitoring image;
inputting the monitoring image into a human body posture detection model to obtain coordinates of human body joint points; the human body joint point coordinates include: coordinates of human hand joint points and coordinates of human skeleton joint points;
judging whether the safe box area contains the coordinates of the hand joint points of the human body;
if the safe box area contains the coordinates of the joint points of the hands of the human body, judging whether two persons exist according to the coordinates of the joint points of the skeleton of the human body;
if two persons exist, judging whether one face exists or not;
if a face exists, determining the current bank note adding behavior standard;
otherwise, determining that the current money adding behavior is not standard and giving an alarm.
2. The method of claim 1, wherein acquiring the safe area in the monitored image comprises:
and acquiring pixel information of the safe in the monitored image by using an image processing algorithm, and identifying the safe area in the monitored image according to the difference between the pixels of the safe area and the background pixels of the image.
3. The method of claim 1, wherein if the safe area contains the coordinates of the joint points of the hand of the human body, judging whether two persons exist according to the coordinates of the joint points of the skeleton of the human body comprises the following steps:
judging whether two groups of different human body skeleton joint point coordinates exist in the obtained human body joint point coordinates;
if two groups of different human body skeleton joint point coordinates exist, judging that two persons exist;
otherwise, judging that two persons do not exist.
4. The method according to claim 3, wherein in the case where it is judged that there are two persons, let the human hand joint point coordinates in the acquired human joint point coordinates be H1, and let two sets of human skeleton joint point coordinates in the human joint point coordinates be B1 and B2, respectively; the method comprises the following steps:
judging an operator of the safety box according to the membership between the human hand joint point coordinate H1 and the two groups of human skeleton node coordinates B1 and B2; if the human hand joint point coordinate H1 belongs to the human skeleton joint point coordinate B1, the fact that a person corresponding to the human skeleton joint point coordinate B1 operates the safety box is judged; and if the human body hand joint point coordinate H1 belongs to the human body skeleton joint point coordinate B2, judging that the person corresponding to the human body skeleton joint point coordinate B2 operates the safety box.
5. The method of claim 4, wherein said determining whether a face is present comprises:
if the human hand joint point coordinate H1 belongs to the human skeleton joint point coordinate B1, judging that a human face exists when the human face is detected in the human skeleton joint point coordinate B1 and the human face is not detected in the human skeleton joint point coordinate B2;
if the human hand joint point coordinate H1 belongs to the human skeleton joint point coordinate B2, it is determined that there is a human face when a human face is detected in the human skeleton joint point coordinate B2 and a human face is not detected in the human skeleton joint point coordinate B1.
6. The utility model provides a behavior detection device that adds paper money suitable for safe deposit box region which characterized in that includes:
the image acquisition module is used for acquiring a monitoring image;
the safety box area acquisition module is used for acquiring a safety box area in the monitoring image;
the human body posture detection module is used for inputting the monitoring image into a human body posture detection model to obtain the coordinates of the human body joint points; the human body joint point coordinates include: coordinates of human hand joint points and coordinates of human skeleton joint points; judging whether the safe box area contains the coordinates of the hand joint points of the human body; if the safe box area contains the coordinates of the joint points of the hands of the human body, judging whether two persons exist according to the coordinates of the joint points of the skeleton of the human body;
the face detection module is used for judging whether a face exists or not under the condition of judging that two persons exist;
the standard detection module is used for determining the current banknote adding behavior standard under the condition that two persons exist and one face exists; otherwise, determining that the current money adding behavior is not standard and giving an alarm.
7. A cash-in action detection system suitable for a safe box area is characterized by comprising:
the apparatus for detecting the loading of a safe area according to claim 6;
and the alarm device is connected with and controlled by the cash adding behavior detection device so as to give an alarm prompt after receiving an alarm instruction sent by the cash adding behavior detection device.
8. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method for detecting a refurbishment action in a safe area according to any one of claims 1 to 5.
9. An electronic terminal, comprising: a processor and a memory;
the memory is used for storing a computer program;
the processor is configured to execute the computer program stored in the memory to cause the terminal to perform the method for detecting a refurbishing action applicable to a safe area according to any one of claims 1 to 5.
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