Patent Publication Number: US-2023162576-A1

Title: Monitoring device and monitoring method

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is based upon and claims the benefit of priority from Japanese Patent Application No. 2021-191259, filed Nov. 25, 2021, the entire contents of which are incorporated herein by reference. 
     FIELD 
     Embodiments described herein relate generally to a monitoring device, a monitoring method, and a non-transitory computer readable medium storing a program causing a computer to execute a monitoring method. 
     BACKGROUND 
     There are checkout systems of a self-service type with which a customer himself or herself performs the operations necessary for commodity registration and a sales transaction settlement (payment) after commodity registration. With the checkout system of this type, a customer may leave a store before completing checkout processing. Therefore, there has been a technique adopted for sensing or detecting whether a customer is present in a checkout area during checkout processing, and then issuing an alert if a customer leaves the checkout area before the checkout processing is completed. 
     With such related art, a store clerk can be made aware that a customer left the checkout area before completing checkout processing. However, if there are two or more customers who leave the checkout area at about the same time as the store clerk is alerted, it is not easy for the clerk to identify which customer is the one who failed to complete checkout processing. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a schematic diagram illustrating a checkout system of a self-service type. 
         FIG.  2    is a perspective view illustrating an exterior of a checkout terminal. 
         FIG.  3    is a hardware block diagram of a checkout terminal. 
         FIG.  4    is a hardware block diagram of a monitoring device according to a first embodiment. 
         FIG.  5    is a functional block diagram of a monitoring device according to a first embodiment. 
         FIG.  6    is a flowchart of information processing executed by a monitoring device according to a first embodiment. 
         FIG.  7    is an example of an alert screen. 
         FIG.  8    is a hardware block diagram of a monitoring device according to a second embodiment. 
         FIG.  9    is a functional block diagram of a monitoring device according to a second embodiment. 
         FIG.  10    is a flowchart of information processing executed by a monitoring device according to a second embodiment. 
         FIG.  11    is a hardware block diagram of a monitoring device according to a third embodiment. 
         FIG.  12    is a functional block diagram of a monitoring device according to a third embodiment. 
         FIG.  13    is a flowchart of information processing executed by a monitoring device according to a third embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     One or more embodiments provide a monitoring device that can easily specify a customer who left a checkout area in a store before completing checkout processing. 
     According to an embodiment, a monitoring device for monitoring a customer operating a checkout terminal in a store is provided. The monitoring device includes a network interface configured to communicate with the checkout terminal configured to perform checkout processing and an attendant terminal. The monitoring device includes a camera interface through which an image captured by a camera is received. The camera is installed so as to image the customer operating the checkout terminal. The monitoring device includes a processor configured to, upon receipt of a first command indicating that the checkout processing has been started from the checkout terminal, begin monitoring the image captured by the camera, upon detection of presence of the customer in the image, acquire feature information representing features of the customer from the image, and upon detection of absence of the customer in the image after the feature information is acquired, control the network interface to output to the attendant terminal an alert signal with the acquired feature information. 
     Certain example embodiments relating to a customer monitoring device are explained below with reference to the drawings. The particular examples described concern a checkout system of a self-service type that can be introduced at a retail store such as a supermarket. In a self-service type checkout system, a customer can complete a transaction by performing commodity registration and checkout processing by himself or herself, generally without intervention of a store clerk or the like. 
     First Embodiment 
     First, a checkout system  100  according to a first embodiment is explained with reference to  FIGS.  1  to  6   . 
       FIG.  1    is a schematic diagram illustrating the checkout system  100  of a self-service type. The checkout system  100  includes a plurality of checkout terminals  10  and a store server  20 . In the checkout system  100 , the checkout terminals  10  and the store server  20  are connected by a communication network  30  such as a LAN (Local Area Network). In the checkout system  100 , an attendant terminal  40  for monitoring by a store clerk is also connected to the communication network  30 . 
     The checkout terminals  10  are installed in a checkout are in a store. Customers who have finished shopping operate the checkout terminals  10  for checkout. A customer who has put purchased commodities in a shopping basket or the like in a selling floor where commodities are displayed moves to the checkout area, operates the checkout terminal  10 , and performs commodity registration and checkout processing by himself or herself. The store server  20  communicates with the checkout terminal  10  to complete the transaction. The attendant terminal  40  is installed in a monitoring area near an exit of the checkout area and displays, for example, a list of purchased commodities registered in each of the checkout terminals  10  on a display device. If an error occurs in the checkout terminal  10 , the attendant terminal  40  displays information concerning the error. A store clerk present in the monitoring area checks the checkout area based on the error information informed by the attendant terminal  40 . In  FIG.  1   , one attendant terminal  40  is illustrated. However, a plurality of attendant terminals  40  may be connected to the communication network  30 . 
     The checkout system further includes a plurality of monitoring devices  50  each connected to a corresponding one of the checkout terminals  10 . The monitoring device  50  may be installed outside of the checkout terminal  10  or may be embedded in the checkout terminal  10 . In this example, the monitoring device  50  is provided outside of the checkout terminal  10 , and the checkout terminal  10  and the monitoring device  50  are connected to each other by a signal cable  60 . 
     The monitoring device  50  is a device for monitoring a movement of a customer, who operates the checkout terminal  10  corresponding to the monitoring device  50 . Specifically, the monitoring device  50  monitors the customer who is operating the checkout terminal  10  corresponding to the monitoring device  50  and performing checkout processing and notifies an alert if the customer has left the checkout area before completing the checkout processing. A notification destination of the alert is, for example, the attendant terminal  40 . The monitoring devices  50  are connected to the attendant terminal  40  by a signal cable  70  and outputs an alert signal to the attendant terminal  40 . 
       FIG.  2    is a perspective view illustrating an exterior of the checkout terminal  10 .  FIG.  3    is a hardware block diagram of the checkout terminal  10 . A main configuration of the checkout terminal  10  is explained below with reference to  FIGS.  2  and  3   . 
     As illustrated in  FIG.  2   , the checkout terminal  10  includes a main body  101  and a first commodity placing table  102  and a second commodity placing table  103  disposed on the left and the right of the main body  101 . The first commodity placing table  102  disposed on the right side of the main body  101  is a place for a customer to place purchased commodities before registration. The purchased commodities before registration are usually stored in a shopping basket and placed on the first commodity placing table  102 . The purchased commodities before registration may be located above the first commodity placing table  102  in a state in which the purchased commodities before registration are stored in a shopping cart. 
     The second commodity placing table  103  disposed on the left side of the main body  101  is a place for the customer to place the purchased commodities after registration. The purchased commodities after registration are stored in, for example, a shopping bag (a register bag, a reusable shopping bag, or the like) placed on the second commodity placing table  103 . The purchased commodities after registration may be directly placed on the second commodity placing table  103 . In  FIG.  2   , a temporary placing table  104  is provided above the second commodity placing table  103  via a column. The temporary placing table  104  is, for example, a table for temporarily placing commodities before storing the commodities in a shopping bag. Two holding arms  105  separated to the left and the right are attached to the temporary placing table  104 . The customer can hang the shopping bag on the holding arms  105 . 
     The main body  101  includes a touch panel  11 , a card reader  12 , a printer  13 , a scanner  14 , a hand scanner  15 , a cash processing machine  16 , and a speaker  17  as input and output devices. 
     The touch panel  11  includes a display functioning as a display device and a touch sensor functioning as an input device. The display displays various kinds of screen information such as a checkout start screen, a registration details screen, a payment method selection screen, and a checkout screen. The checkout start screen is a screen for receiving a checkout start operation. A start key for instructing the checkout start operation is disposed on the checkout start screen. A customer who starts registration of purchased commodities touches the start key. If the touch sensor detects that the start key is touched, a processor  181  (see  FIG.  3   ) of the checkout terminal  10  controls the display to shift the screen from the checkout start screen to the registration details screen. 
     The registration details screen is a screen for displaying detailed information such as commodity names, prices, and a total amount of registered purchased commodities. A payment key for proceeding to payment for the registered purchased commodities is disposed on the registration details screen. A customer who has finished the registration of purchased commodities touches the payment key. If the touch sensor detects that the payment key is touched, the processor  181  of the checkout terminal  10  controls the display to shift the screen from the registration details screen to the payment method selection screen. 
     The payment method selection screen is a screen for receiving a selection input for a payment method such as a cash payment, a credit card payment, or an electronic money payment. A cash key for instructing the cash payment, a credit key for instructing the credit card payment, an electronic money key for instructing the electronic money payment, and the like are disposed on the payment method selection screen. For example, a customer desiring the cash payment touches the cash key. If the touch sensor detects that the cash key is touched, the processor  181  of the checkout terminal  10  controls the display to shift the screen from the payment method selection screen to the checkout screen. The checkout screen is a screen for displaying a total amount of a transaction, a deposit amount of cash, a change amount, and the like. 
     The card reader  12  reads data recorded in a card medium such as a credit card, an electronic money card, or a point card. If the card medium is a magnetic card, the card reader  12  is a magnetic card reader. If the card medium is an IC card, the card reader  12  is an IC card reader. The checkout terminal  10  may include one or both of the magnetic card reader and the IC card reader as the card reader  12 . The card reader  12  may be a card reader writer including a function of writing data into a card. 
     The printer  13  prints data relating to a purchase receipt, a credit card slip, or the like on receipt paper. The receipt paper on which various data are printed by the printer  13  is cut by a cutter and dispensed from a receipt dispensing port. The printer  13  is, for example, a thermal printer or a dot impact printer. 
     The scanner  14  and the hand scanner  15  read information for identifying a commodity. In this embodiment, the scanner  14  and the hand scanner  15  read a barcode attached to a commodity as information for identifying the commodity. The scanner  14  optically reads the barcode of the commodity held over a reading window such that the barcode attached to the commodity is opposed to the reading window. The hand scanner  15  is held and operated by a customer. The hand scanner  15  optically reads the barcode when brought close to the barcode attached to the commodity. The scanner  14  and the hand scanner  15  may read information for identifying a commodity from another code other than a barcode, e.g., a two-dimensional code. 
     The cash processing machine  16  receives and dispenses cash. The cash processing machine  16  includes a bill insertion port  161 , a bill discharging port  162 , a coin insertion port  163 , and a coin discharging port  164 . The cash processing machine  16  receives bills inserted via the bill insertion port  161 . The cash processing machine  16  discharges bills as change from the bill discharging port  162 . The cash processing machine  16  receives coins inserted via the coin insertion port  163 . The cash processing machine  16  discharges coins as change from the coin discharging port  164 . 
     The speaker  17  outputs warning or alert sounds, voice messages, or the like. 
     A camera  80  is provided above the main body  101 . The camera  80  images a customer who is operating the checkout terminal  10 . As illustrated in  FIG.  2   , the display of the touch panel  11 , the card insertion port of the card reader  12 , the receipt dispensing port of the printer  13 , the reading window of the scanner  14 , and the bill insertion port  161 , the bill discharging port  162 , the coin insertion port  163 , and the coin discharging port  164  of the cash processing machine  16  are disposed along one surface (hereinafter referred to as front surface) of the main body  101 . Accordingly, the customer stands to face the front surface of the main body  101  and operates the checkout terminal  10 . The camera  80  images substantially the whole body of the customer from above. Therefore, the head, the face, both the shoulders, both the arms, the chest, the abdomen, and the like of the customer are imaged by the camera  80 . 
     As illustrated in  FIG.  3   , the checkout terminal  10  includes a control circuit  18  including a processor  181 , a main memory  182 , an auxiliary storage device  183 , a clock  184 , a network interface (I/F)  185 , a monitoring device interface (I/F)  186 , a device interface (I/F)  187 , and a system transmission line  188 . The system transmission line  188  includes an address bus, a data bus, a control signal line, and the like. 
     The processor  181 , the main memory  182 , the auxiliary storage device  183 , the clock  184 , the network interface  185 , the monitoring device interface  186 , and the device interface  187  are connected to each other by the system transmission line  188  such that data signals are exchanged therebetween. In the checkout terminal  10 , the touch panel  11 , the card reader  12 , the printer  13 , the scanner  14 , the hand scanner  15 , the cash processing machine  16 , and the speaker  17  explained above are connected to the device interface  187 . Devices that can be connected to the checkout terminal  10  are not limited to the devices shown in  FIG.  3   . Any device may be added to the checkout terminal  10  or one or more of the devices shown in  FIG.  3    may be omitted. 
     The processor  181  controls the other components of the checkout terminal  10  in order to perform various functions thereof according to an operating system and one or more application programs. The processor  181  is, for example, a CPU (Central Processing Unit). 
     The main memory  182  includes a nonvolatile memory region and a volatile memory region. The nonvolatile memory region of the main memory  182  stores the operating system and/or the application programs. In the nonvolatile and/or volatile memory region, data necessary for the processor  181  to execute processing for controlling the components of the checkout terminal  10  is stored. The volatile memory region is used as a work area where data is temporarily stored by the processor  181 . The nonvolatile memory region is, for example, a ROM (Read Only Memory). The volatile memory region is, for example, a RAM (Random Access Memory). 
     The auxiliary storage device  183  is, for example, an EEPROM (Electric Erasable Programmable Read-Only Memory), a HDD (Hard Disk Drive), or an SSD (Solid State Drive). The auxiliary storage device  183  stores data used by the processor  181  in performing various kinds of processing, data generated by the processor  181 , and the like. The auxiliary storage device  183  can store the application programs. 
     The clock  184  is a clock circuit that maintains a date and time. The processor  181  acquires, as present date and time, the date and the time from the clock  184 . 
     The network interface  185  performs data communication with the store server  20  and the attendant terminal  40  connected via the communication network  30 . 
     The monitoring device interface  186  is connected to the monitoring device  50  via the signal cable  60 . The monitoring device interface  186  performs data communication with the monitoring device  50 . 
       FIG.  4    is a hardware block diagram of the monitoring device  50 . The monitoring device  50  includes a processor  51 , a main memory  52 , an auxiliary storage device  53 , a camera interface (I/F)  54 , a checkout terminal interface (I/F)  55 , an attendant terminal interface (I/F)  56 , and a system transmission line  57 . The system transmission line  57  includes an address bus, a data bus, a control signal line, and the like. 
     The processor  51 , the main memory  52 , the auxiliary storage device  53 , the camera interface  54 , the checkout terminal interface  55 , and the attendant terminal interface  56  are connected to each other by the system transmission line  57  such that data signals are exchanged therebetween. 
     The processor  51  controls the other components of the monitoring device  50  in order to perform various functions thereof according to an operating system and one or more application programs. The processor  51  is, for example, a CPU. 
     The main memory  52  includes a nonvolatile memory region and a volatile memory region. The nonvolatile memory region of the main memory  52  stores the operating system and/or the application programs. In the nonvolatile and/or volatile memory region, data necessary for the processor  51  to execute processing for controlling the components of the monitoring device  50  is stored. The volatile memory region is used as a work area where data is temporarily stored by the processor  51 . The nonvolatile memory region is, for example, a ROM. The volatile memory region is, for example, a RAM. 
     The auxiliary storage device  53  is, for example, an EEPROM, a HDD, or an SSD. The auxiliary storage device  53  stores data used by the processor  51  in performing various kinds of processing, data generated by the processor  51 , and the like. The auxiliary storage device  53  can store the application programs. 
     The camera interface  54  is connected to the camera  80  attached to the checkout terminal  10  corresponding to the monitoring device  50 . The camera interface  54  outputs a control signal for controlling the camera  80  to the camera  80 . The camera  80  performs an imaging operation according to the control signal. The camera interface  54  takes in image the data captured by the camera  80 . The camera interface  54  may be a network interface connected to the camera  80  via a wired or wireless network. 
     The checkout terminal interface  55  is connected to the checkout terminal  10  via the signal cable  60 . The checkout terminal interface  55  performs data communication with the checkout terminal  10 . The checkout terminal interface  55  may be a network interface connected to the checkout terminal  10  via a wired or wireless network. 
     The attendant terminal interface  56  is connected to the attendant terminal  40  via the signal cable  70 . The attendant terminal interface  56  performs data communication with the attendant terminal  40 . The attendant terminal interface  56  may be a network interface connected to the attendant terminal  40  via a wired or wireless network. Two or more of the camera interface  54 , the checkout terminal interface  55 , and the attendant terminal interface  56  may be integrated into one or more interfaces. 
     The monitoring device  50  having such a configuration uses a part of the volatile memory region in the main memory  52  as a region of a first memory  521  and a second memory  522 . Uses of the first memory  521  and the second memory  522  are explained below. 
     In the monitoring device  50 , as illustrated in FIG.  5 , the processor  51  operates as an image acquiring unit  511 , a customer detecting unit  512 , a score calculating unit  513 , a storing unit  514 , and an output unit  515  to perform various functions of the monitoring device  50 . 
     The image acquiring unit  511  performs a function of sequentially acquiring, for each of frames, image data captured by the camera  80  connected via the camera interface  54 . 
     The customer detecting unit  512  performs a function of detecting a customer who is performing checkout processing using the checkout terminal  10 . The customer detecting unit  512  detects the customer based on, for example, an image captured by the camera  80  and acquired by the image acquiring unit  511 . The customer detecting unit  512  detects the customer by, for example, extracting skeleton information of the customer from the captured image using a skeleton estimation technique that utilizes artificial intelligence (AI). 
     The score calculating unit  513  performs a function of calculating a posture score of the customer. The score calculating unit  513  calculates the posture score based on, for example, the skeleton information of the customer extracted by the skeleton estimation technique in the customer detecting unit  512 . For example, the score calculating unit  513  scores parts of a body forming a skeleton and calculates the posture score. The parts of the body include the right eye, the left eye, the right ear, the left ear, the nose, the mouth, the neck, the right shoulder, the left shoulder, the right elbow, the left elbow, the right wrist, the left wrist, the right waist, the left waist, the right knee, the left knee, the right ankle, and the left ankle. The score calculating unit  513  sets, for example, a total number of parts that have been successfully extracted from the captured image as the posture score. The score calculating unit  513  may weight on some particular parts such as the eyes and the nose in specifying the customer and calculate the posture score. If a line segment, which is the axis of the body, connecting the middle point between the right shoulder and the left shoulder and the middle point between the right waist and the left waist tilts to the near side when viewed from above, that is, if the customer is looking down, since the parts of the face are not shown in the captured image, the score calculating unit  513  may sets the posture score to decrease. 
     The storing unit  514  performs a function of, for example, if the skeleton information of the customer is extracted from the captured image using the skeleton estimation technique by the customer detecting unit  512 , storing the skeleton information in the first memory  521 . The first memory  521  is capable of storing a predetermined number of pieces of skeleton information in time series. If the predetermined number of pieces of skeleton information are already stored in the first memory  521 , the storing unit  514  stores in the first memory  521  new skeleton information after deleting the oldest skeleton information. 
     The storing unit  514  also performs a function of storing in the second memory  522  a maximum value of the posture score calculated in the score calculating unit  513  together with data of the captured image for each frame corresponding to the posture score. If the posture score is the maximum value, it can be considered that a large number of pieces of information that can specify the customer detected by the customer detecting unit  512  are included in the captured image corresponding to the posture score. That is, the data of the captured image corresponding to the posture score having the maximum value can be information representing the features of the customer. Thus, the score calculating unit  513  and the storing unit  514  can acquire the information representing the features of the customer. 
     The output unit  515  performs a function of, if the customer is no longer detected by the customer detecting unit  512  before the checkout processing in the checkout terminal  10  ends, outputting an alert signal. The alert signal includes the data of the captured image, which is the information stored in the second memory  522 , that is, the information representing the features of the customer. For example, the alert signal is output to the attendant terminal  40  via the signal cable  70 . 
     All of the functions of the image acquiring unit  511 , the customer detecting unit  512 , the score calculating unit  513 , the storing unit  514 , and the output unit  515  are performed as information processing executed by the processor  51  according to a customer monitoring program. 
     The customer monitoring program is a type of the application programs stored in the main memory  52  or the auxiliary storage device  53 . A method of installing the customer monitoring program in the main memory  52  or the auxiliary storage device  53  is not particularly limited. The customer monitoring program can be installed in the main memory  52  or the auxiliary storage device  53  from a non-transitory computer readable recording medium or via a network. A form of the recording medium may be any form as long as the recording medium can store programs like a CD-ROM or a memory card and can be read by the monitoring device  50 . 
       FIG.  6    is a flowchart of the information processing executed by the processor  51  of the monitoring device  50  according to the customer monitoring program. A main procedure performed by the monitoring device  50  is explained below with reference to  FIG.  6   . The procedure explained below is an example. The procedure can be changed as appropriate if the same effects can be achieved. 
     As illustrated in  FIG.  6   , in ACT  1 , the processor  51  waits for a checkout start command. If the start key displayed on the checkout start screen of the checkout terminal  10  corresponding to the monitoring device  50  is touched, the checkout start command is transmitted from the checkout terminal  10  to the monitoring device  50  via the signal cable  60 . That is, if a customer coming to the checkout area stands in the front of the checkout terminal  10  not in use and touches the start key displayed on the touch panel  11 , the checkout start command is input to the monitoring device  50  connected to the checkout terminal  10 . 
     If the checkout start command is received via the checkout terminal interface  55  in ACT  1 , the processor  51  proceeds to ACT  2 . In ACT  2 , the processor  51  initializes the first memory  521  and the second memory  522 . The data stored in the first memory  521  and the second memory  522  are cleared by the initialization. 
     If finishing initializing the first memory  521  and the second memory  522 , the processor  51  proceeds to ACT  3 . In ACT  3 , the processor  51  outputs a start signal to the camera  80  connected to the camera interface  54 . The camera  80  starts an imaging action according to the start signal. As explained above, the camera  80  is installed at a position where the camera  80  is capable of imaging the customer standing in the front of the checkout terminal  10  from above. Therefore, it is highly likely that the hair, the face, the clothes, and the like of the customer who has touched the start key are shown in the image captured by the camera  80 . 
     In ACT  4 , the processor  51  acquires, as the image acquiring unit  511 , a captured image of each frame from the camera  80  via the camera interface  54 . The processor  51  executes processing in ACT  5  and subsequent acts based on the captured image. 
     In ACT  5 , the processor  51  executes skeleton estimation processing on the captured image. If the customer is shown in the captured image, the skeleton information of the customer is extracted by the skeleton estimation processing. That is, if the skeleton information is extracted, it is determined that the customer is standing in the front of the checkout terminal  10 . 
     In ACT  6 , the processor  51  checks whether the customer is detected, that is, whether the skeleton information is successfully extracted from the captured image. If the skeleton information is not successfully extracted from the captured image in ACT  6 , the processor  51  proceeds to ACT  7 . In ACT  7 , the processor  51  checks whether data is stored in the second memory  522 . Immediately after the second memory  522  is initialized in ACT  2 , data is not stored in the second memory  522 . In that case, the processor  51  returns to ACT  4 . The processor  51  acquires the next captured image from the camera  80  and executes the processing in ACT  5  and subsequent acts in the same manner as explained above. 
     If the skeleton information is successfully extracted from the captured image in ACT  6 , the processor  51  proceeds to ACT  8 . In ACT  8 , the processor  51  stores, as the storing unit  514 , the skeleton information in the first memory  521 . In ACT  9 , the processor  51  checks whether another kind of skeleton information is already stored in the first memory  521 . Immediately after the first memory  521  is initialized in ACT  2 , another kind of skeleton information is not stored in the first memory  521 . In that case, the processor  51  proceeds to ACT  15 . Processing in ACT  15  is explained below. 
     If another kind of skeleton information is already stored in the first memory  521  in ACT  9 , the processor  51  proceeds to ACT  10 . In ACT  10 , the processor  51  executes same-customer determination processing. Specifically, the processor  51  determines whether the customer shown in the captured image from which the skeleton information is extracted in ACT  5  is the same as the customer shown in the captured image stored in the memory  521  from which the skeleton information is extracted. For example, if a plurality of pieces of skeleton information are stored in the first memory  521 , the processor  51  estimates, with extrapolation, present skeleton information from the plurality of pieces of skeleton information. The processor  51  performs matching of the estimated skeleton information and the skeleton information extracted in ACT  5 . As a result, if a similarity degree of the skeleton information is equal to or larger than a predetermined value, the processor  51  determines that the same customer is shown. If the similarity degree of the skeleton information is smaller than the predetermined value, the processor  51  determines that the same customer is not shown. 
     Usually, a customer who performs registration and checkout processing and payment for the purchased commodities using the checkout terminal  10  places the purchased commodities on the first commodity placing table  102  and stands in front of the checkout terminal  10 . The customer touches the start key displayed on the checkout start screen. Then, the screen of the touch panel  11  shifts from the checkout start screen to the registration details screen. Therefore, the customer starts registration processing for the purchased commodities. Specifically, the customer repeats a series of actions including: taking one of the purchased commodities from the first commodity placing table  102 , causing the scanner  14  or the hand scanner  15  to read the barcode attached to the purchased commodity, and placing the purchased commodity on the second commodity placing table  103 . Therefore, it is assumed that the customer keeps standing in the front of the checkout terminal  10  while the customer performs the registration processing for the purchased commodities. During that period, the customer is imaged by the camera  80 . Accordingly, usually, it is determined in ACT  11  that the same customer is shown. However, it is also possible that, because of an unintended movement or the like of the customer or another customer in the checkout area, the processor  51  temporarily determines that the same customer is not shown. If it is determined by the processor  51  that the same customer is not shown, the processor  51  proceeds to ACT  15 . Processing in ACT  15  is explained below. 
     If determining in ACT  11  that the same customer is shown, the processor  51  proceeds to ACT  12 . In ACT  12 , the processor  51  calculates, as the score calculating unit  513 , a posture score from the skeleton information extracted in ACT  5 . In ACT  13 , the processor  51  checks whether the calculated posture score is a maximum value up to that point. 
     In ACT  14  explained below, the processor  51  stores in the second memory  522  the maximum value of the posture score. Therefore, in ACT  13 , if the posture score is not stored in the second memory  522  or if the posture score calculated in ACT  12  is larger than the posture score stored in the second memory  522 , the processor  51  determines that the posture score having the maximum value is calculated. If the posture score stored in the second memory  522  is smaller than or equal to the posture score calculated in ACT  12 , the processor  51  determines that the posture score not having the maximum value is calculated. If the posture score not having the maximum value is calculated, the processor  51  proceeds to ACT  15 . Processing in ACT  15  is explained below. 
     If the posture score having the maximum value is calculated in ACT  13 , the processor  51  proceeds to ACT  14 . In ACT  14 , as the storing unit  514 , the processor  51  stores in the second memory  522  the image data acquired in ACT  4  and the posture score calculated in ACT  12  in correlation with each other. Thereafter, the processor  51  proceeds to ACT  15 . 
     In this way, if the processor  51  stores in the second memory  522  the image data and the posture score having the maximum value at that point in time in ACT  14 , if the processor  51  determines in ACT  11 , with the same-customer determination processing, that the same customer is not shown, or if another kind of skeleton information is not stored in the first memory  521  in ACT  9 , the processor  51  proceeds to ACT  15 . 
     In ACT  15 , the processor  51  determines whether a checkout end command is received. If the checkout screen is displayed by the checkout terminal  10  corresponding to the monitoring device  50 , the checkout end command is transmitted from the checkout terminal  10  to the monitoring device  50  via the signal cable  60 . That is, if the customer who finished the registration processing for the purchased commodities touches the payment key displayed on the registration details screen, the screen of the touch panel  11  shifts from the registration details screen to the payment method selection screen. Therefore, the customer touches a key corresponding to a desired payment method. Then, the screen of the touch panel  11  shifts to a checkout screen corresponding to the payment method and the checkout end command is input to the monitoring device  50 . 
     If the checkout end command is not received in ACT  15 , that is, if the customer continues the registration processing for the purchased commodities, the processor  51  returns to ACT  4 . The processor  51  acquires the next captured image from the camera  80  and executes the processing in ACT  5  and subsequent acts in the same manner as explained above. That is, every time the processor  51  acquires a captured image in which the hair, the face, the clothes, and the like of the customer continuing the registration processing for the purchased commodities are highly likely to be shown, the processor  51  executes the skeleton estimation processing in ACT  5 , the skeleton information storage processing in ACT  8 , the same-customer determination processing in ACT  10 , the posture score calculation processing in ACT  12 , and the second memory update processing in ACT  14 . 
     If the checkout end command is received in ACT  15 , the processor  51  proceeds to ACT  17 . In ACT  17 , the processor  51  outputs a stop signal to the camera  80  connected to the camera interface  54 . The camera  80  stops the imaging operation according to the stop signal. Then, the processor  51  ends the procedure illustrated in the flowchart of  FIG.  6   . Thereafter, the processor  51  waits for the next checkout start command in ACT  1  again. 
     If the customer performs registration and checkout processing and payment for the purchased commodities by himself or herself using the checkout terminal  10  in this way, usually, the customer keeps standing in the front of the checkout terminal  10  until the checkout processing ends. Therefore, since the skeleton information of the customer is continuously extracted from the image of each frame captured by the camera  80 , the processor  51  repeatedly executes the processing in ACT  8  to ACT  14  on the captured image. As a result, a captured image in which the posture score is the maximum value is stored in the second memory  522 . 
     If the customer performs operation for paying a price of the purchased commodities on the checkout terminal  10  and the checkout processing ends, the processor  51  ends the information processing shown in  FIG.  6   . The processor  51  clears the second memory  522  according to a touch on the start key by the next customer. Therefore, the image information of the customer who has ended the checkout processing does not remain in the second memory  522 . 
     On the other hand, if the customer went away from the front of the checkout terminal  10  before the checkout processing has ended, the skeleton information cannot be extracted from the captured image in the skeleton estimation processing in ACT  5 . If the skeleton information cannot be extracted from the captured image in a state in which the captured image in which the posture score is the maximum value is stored in the second memory  522 , the processor  51  proceeds to ACT  16 . In ACT  16 , the processor  51  outputs an alert with as the output unit  515 . Specifically, the processor  51  outputs an alert signal to the attendant terminal  40  via the attendant terminal interface  56 . The alert signal includes the data of the captured image in the frame unit stored in the second memory  522 . 
     The processor  51  that has output the alert proceeds to ACT  17  explained above. That is, the processor  51  outputs a stop signal to the camera  80  connected to the camera interface  54  and ends the information processing shown in  FIG.  6   . 
     In this way, if the customer goes away from the front of the checkout terminal  10  before the checkout processing ends, the alert signal is output from the monitoring device  50  to the attendant terminal  40 . In the attendant terminal  40 , an alert screen  90  (see  FIG.  7   ) is displayed on the display device according to the alert signal. 
       FIG.  7    is an example of the alert screen  90 . As illustrated in  FIG.  7   , on the alert screen  90 , a captured image is displayed in an image region  92  together with an alert message  91 . The alert message  91  notifies the attendant that the customer went away without completing the checkout processing with the checkout terminal  10  corresponding to the monitoring device  50 , which is the alert signal transmission source. The captured image is received together with the alert signal, that is, the captured image in which the posture score is the largest. On the alert screen  90 , a checkbox  93  that is checked if information of the alert screen  90  is to be transferred to a person in charge of security other than the attendant and an OK button  94  are also displayed. A layout, an image, text, and the like of the alert screen  90  are not limited to those illustrated in  FIG.  7   . 
     The attendant who checks the alert screen  90  can learn that a customer performing checkout processing using the checkout terminal  10  of No.  3  left the checkout terminal  10  without completing the checkout processing. At this time, an image showing features such as the head, the face, and the clothes of the customer is displayed in the image region  92 . Therefore, the attendant can easily specify, from the image, who is an alert notification target customer. 
     For example, the attendant who specifies the alert notification target customer touches the OK button  94 . Then, the alert screen  90  is erased. For example, the attendant who does not successfully specify the alert notification target customer checks the checkbox  93  and then touches the OK button  94 . Then, content of the alert screen  90  is transferred from the attendant terminal  40  to a predetermined terminal operated by the person in charge of security. As a result, the image showing the features of the customer who left the checkout area without completing checkout processing is displayed and stored in the predetermined terminal. 
     As explained in detail above, according to the first embodiment, even if there are a plurality of customers who are about to go away from the checkout area when the alert is notified from the attendant terminal  40 , the attendant can easily specify an alert target customer. As a result, it is possible to prevent, at a high probability, the customer from going away from the checkout area without completing checkout processing. 
     Additionally, the monitoring device  50  stores, in the second memory  522 , only a frame image in which a posture score is the largest. Therefore, it is unnecessary to store a plurality of image data having large data sizes, which reduces a storage requirement for the monitoring device  50 . 
     Second Embodiment 
     A second embodiment is explained with reference to  FIGS.  8  to  10   . 
     In the second embodiment, as in the first embodiment, the monitoring devices  50  connected to the corresponding checkout terminals  10  in the checkout system  100  operate as customer monitoring devices. Accordingly,  FIGS.  1  to  3    are applicable to the second embodiment as well, and the explanations for  FIGS.  1  to  3    are omitted.  FIGS.  8  to  10    correspond to  FIGS.  4  to  6    in the first embodiment. Therefore, the same components as the first embodiment are denoted by the same reference numerals and signs and the detailed explanations of the components are omitted. 
     The monitoring device  50  is partly different from the monitoring device  50  in the first embodiment in its configuration and functions. Therefore, in the following explanation, a monitoring device according to the second embodiment is referred to as a monitoring device  501 . 
       FIG.  8    is a hardware block diagram of the monitoring device  501 . Like the monitoring device  50 , the monitoring device  501  includes the processor  51 , the main memory  52 , the auxiliary storage device  53 , the camera interface (I/F)  54 , the checkout terminal interface (I/F)  55 , the attendant terminal interface (I/F)  56 , and the system transmission line  57 . 
     However, the monitoring device  501  uses a part of the volatile memory region in the main memory  52  as a region of a memory  523  for a detection completion flag “F” and a third memory  524 . The memory  523  for the detection completion flag F and the third memory  524  are explained below. 
     In the monitoring device  501 , as illustrated in  FIG.  9   , the processor  51  operates as an image acquiring unit  581 , a customer detecting unit  582 , a storing unit  583 , and an output unit  584 . 
     Like the image acquiring unit  511  of the monitoring device  50 , the image acquiring unit  581  performs the function of sequentially acquiring, for each of frames, image data captured by the camera  80  connected via the camera interface  54 . 
     Like the customer detecting unit  512  of the monitoring device  50 , the customer detecting unit  582  performs the function of detecting a customer who is performing checkout processing using the checkout terminal  10 . The customer detecting unit  582  detects the customer based on, for example, an image captured by the camera  80  and acquired by the image acquiring unit  581 . However, since the monitoring device  501  does not have the function of the score calculating unit  513 , the customer detecting unit  582  does not need to use the skeleton estimation technique. For example, the customer detecting unit  582  can detect, from the captured image, as the customer, an object belonging to a person category using an object detection technique in which deep learning is used, such as single-shot detector (SSD). 
     The storing unit  583  performs a function of storing in the memory  523  the detection completion flag F, which is one-bit data of “0” or “1”. The storing unit  583  also performs a function of storing in the third memory  524  data of a captured image in which the customer was detected first by the customer detecting unit  582 . 
     As explained below, in the second embodiment as well, if a checkout start command is received from the checkout terminal  10 , the processor  51  outputs a start signal to the camera  80 . The customer touches the start key displayed on the checkout start screen displayed on the touch panel  11  of the checkout terminal  10 , whereby the checkout start command is transmitted from the checkout terminal  10  to the monitoring device  501 . Therefore, it is highly likely that the customer facing the touch panel  11  is shown in an image captured by the camera  80  at that timing. That is, since the camera  80  is disposed above the checkout terminal  10 , it is highly likely that not only the clothes of the customer but also the face of the customer is shown. Since all of purchased commodities of the customer are placed on the first commodity placing table  102 , the purchased commodities should be shown in the captured image. Therefore, the data of the captured image stored in the third memory  524 , that is, the captured image in which the customer was detected first by the customer detecting unit  582  can be considered as information representing features of the customer. In other words, the storing unit  583  can acquire the information representing the features of the customer. 
     Like the output unit  515  of the monitoring device  50 , the output unit  584  performs the function of outputting an alert signal if the customer is no longer detected by the customer detecting unit  582  before checkout processing ends. The alert signal includes the data of the captured image, which is the information stored in the third memory  524 , that is, the information representing the features of the customer. For example, the alert signal is output to the attendant terminal  40  via the signal cable  70 . 
     All of the functions of the image acquiring unit  581 , the customer detecting unit  582 , the storing unit  583 , and the output unit  584  explained above are performed by the processor  51  according to a customer monitoring program. 
       FIG.  10    is a flowchart of the information processing executed by the processor  51  of the monitoring device  501  according to the customer monitoring program. A main procedure performed by the monitoring device  501  is explained below with reference to  FIG.  10   . The procedure explained below is an example. The procedure can be changed as appropriate if the same effects can be achieved. 
     As illustrated in  FIG.  10   , in ACT  21 , the processor  51  waits for a checkout start command. If the start key displayed on the checkout start screen of the checkout terminal  10  corresponding to the monitoring device  501  is touched, whereby the checkout start command is received via the checkout terminal interface  55 , the processor  51  proceeds to ACT  22 . In ACT  22 , the processor  51  sets the detection completion flag F stored in the memory  523  to “0” as the storing unit  583 . In ACT  23 , the processor  51  initializes the third memory  524 . The data stored in the third memory  524  is cleared by the initialization. 
     If finishing initializing the third memory  524 , the processor  51  proceeds to ACT  24 . In ACT  24 , the processor  51  outputs a start signal to the camera  80  connected to the camera interface  54 . The camera  80  starts an imaging operation according to the start signal. 
     In ACT  25 , the processor  51  acquires a captured image of each frame from the camera  80  via the camera interface  54  as the image acquiring unit  581 . The processor  51  executes processing in ACT  26  and subsequent acts based on the captured image. 
     In ACT  26 , the processor  51  performs object detection processing to detect an object belonging to a person category from the captured image. 
     In ACT  27 , the processor  51  checks whether an object belonging to the person category is successfully detected from the captured image. If an object belonging to the person category is not successfully detected from the captured image in ACT  27 , the processor  51  proceeds to ACT  28 . In ACT  28 , the processor  51  checks whether data is stored in the third memory  524 . No data is stored in the third memory  524  immediately after the third memory  524  is initialized in ACT  23 . In that case, the processor  51  returns to ACT  25 . The processor  51  acquires the next captured image from the camera  80  and executes the processing in ACT  26  and subsequent acts in the same manner as explained above. 
     If an object belonging to the person category is successfully detected from the captured image in ACT  27 , the processor  51  proceeds to ACT  29 . In ACT  29 , the processor  51  checks the detection completion flag F of the memory  523 . If the detection completion flag F is “0”, the processor  51  proceeds to ACT  30 . In ACT  30 , as the storing unit  583 , the processor  51  stores in the third memory  524  data of the captured image acquired in ACT  25 . In ACT  31 , the processor  51  rewrites the detection completion flag F of the memory  523  from “0” to “1” as the storing unit  583 . Thereafter, the processor  51  proceeds to ACT  32 . 
     In ACT  32 , the processor  51  checks whether a checkout end command is received. If the checkout end command is not received, that is, if the customer continues the registration processing for the purchased commodities, the processor  51  returns to ACT  25 . The processor  51  acquires the next captured image from the camera  80  and executes the processing in ACT  26  and subsequent acts. However, in this case, since the detection completion flag F is “1” in ACT  29 , the processor  51  skips the processing in ACT  30  and ACT  31 . 
     If receiving the checkout end command in ACT  32 , the processor  51  proceeds to ACT  34 . In ACT  34 , the processor  51  outputs a stop signal to the camera  80  connected to the camera interface  54 . The camera  80  stops the imaging operation according to the stop signal. Then, the processor  51  ends the information processing indicated by the flowchart of  FIG.  10   . Thereafter, in ACT  21 , the processor  51  waits for the next checkout start command again. 
     If the customer performs registration and checkout processing and payment for the purchased commodities by himself or herself using the checkout terminal  10  in this way, usually, the customer keeps standing in the front of the checkout terminal  10  until the checkout processing ends. Therefore, since an object belonging to the person category is continuously detected from an image of each frame captured by the camera  80 , the processor  51  repeatedly executes the processing in ACT  29  and subsequent acts on the captured image. As a result, a captured image in which the person, who is the customer, was detected first is stored in the third memory  524 . 
     If the customer performs operation for paying a price of the purchased commodities on the checkout terminal  10  and the checkout processing ends, the processor  51  ends the information processing shown in  FIG.  10   . The processor  51  clears the third memory  524  according to a touch operation on the start key by the next customer. Therefore, the image information of the customer who ended the checkout processing does not remain in the third memory  524 . 
     On the other hand, if the customer went away from the front of the checkout terminal  10  before the checkout processing ends, any customer cannot be detected from the captured image in the detection processing in ACT  26 . If the customer is no longer detected after the captured image in which the customer was detected first is stored in the third memory  524 , the processor  51  proceeds to ACT  33 . In ACT  33 , the processor  51  outputs an alert as the output unit  584 . Specifically, the processor  51  outputs an alert signal to the attendant terminal  40  via the attendant terminal interface  56 . The alert signal includes the data of the captured image stored in the third memory  524 . 
     The processor  51  that has output the alert proceeds to ACT  34  explained above. That is, the processor  51  outputs a stop signal to the camera  80  connected to the camera interface  54  and ends the information processing shown in  FIG.  10   . 
     In this way, if the customer goes away from the front of the checkout terminal  10  before the checkout processing ends, the alert signal is output from the monitoring device  50  to the attendant terminal  40 . In the attendant terminal  40 , an alert screen is displayed on the display device according to the alert signal. The alert screen is, for example, a screen having the same layout as the alert screen  90  in the first embodiment. Therefore, a captured image at a point in time when the customer who went away from the checkout terminal  10  touched the start key displayed on the checkout start screen is displayed on the alert screen. 
     It is highly likely that not only the clothes of the customer but also the face of the customer is shown in the captured image. Therefore, the attendant can easily specify, from the image, who is an alert notification target customer. 
     As explained above in detail, in the second embodiment, as in the first embodiment, it is possible to prevent, at a high probability, the customer from going away from the checkout area without completing checkout. 
     Moreover, in the second embodiment, the skeleton estimation processing and the calculation processing for the posture score are unnecessary. Therefore, a processing load on the processor  51  can be reduced. 
     Third Embodiment 
     A third embodiment is explained with reference to  FIGS.  11  to  13   . 
     In the third embodiment, as in the first and second embodiments, the monitoring devices  50  connected to the corresponding checkout terminals  10  in the checkout system  100  operates as customer monitoring devices. Accordingly,  FIGS.  1  to  3    are applicable to the third embodiment as well, and the explanations for  FIGS.  1  to  3    are omitted.  FIGS.  11  to  13    correspond to  FIGS.  4  to  6    in the first embodiment. Therefore, the same components as the first embodiment are denoted by the same reference numerals and signs and detailed explanations of the components are omitted. 
     The monitoring device  50  is partly different from the monitoring device  50  in the first and second embodiments in its configuration and functions. Therefore, in the following explanation, a monitoring device according to the third embodiment is referred to as a monitoring device  502 . 
       FIG.  11    is a hardware block diagram of the monitoring device  502 . Like the monitoring device  50  and the monitoring device  501 , the monitoring device  502  includes the processor  51 , the main memory  52 , the auxiliary storage device  53 , the camera interface (I/F)  54 , the checkout terminal interface (I/F)  55 , the attendant terminal interface (I/F)  56 , and the system transmission line  57 . 
     However, the monitoring device  502  uses a part of the volatile memory region in the main memory  52  as a region of a fourth memory  525 . The fourth memory  525  is explained below. 
     In the monitoring device  502 , as illustrated in  FIG.  12   , the processor  51  operates as an image acquiring unit  591 , a customer detecting unit  592 , a list acquiring unit  593 , a storing unit  594 , and an output unit  595 . 
     Like the image acquiring unit  511  of the monitoring device  50 , the image acquiring unit  591  performs the function of sequentially acquiring, for each of frames, image data captured by the camera  80  connected via the camera interface  54 . 
     Like the customer detecting unit  512  of the monitoring device  50 , the customer detecting unit  592  performs the function of detecting a customer who is performing checkout processing using the checkout terminal  10 . The customer detecting unit  592  detects the customer based on, for example, an image captured by the camera  80  and acquired by the image acquiring unit  591 . However, since the monitoring device  502  does not have the function of the score calculating unit  513 , the customer detecting unit  592  does not need to use the skeleton estimation technique. For example, the customer detecting unit  592  can detect, from the captured image, as the customer, an object belonging to a person category using an object detection technique in which deep learning is used, such as SSD. 
     The list acquiring unit  593  performs a function of acquiring a list of commodities registered as information concerning a transaction performed by the checkout terminal  10 . In the checkout terminal  10 , for example, if information for identifying a commodity is read by the scanner  14  or the hand scanner  15 , purchased commodity data including a commodity name and a price of the commodity is registered in a transaction memory. According to this registration processing, commodity names, prices, and the like of purchased commodities by the customer are sequentially stored in the transaction memory. The list acquiring unit  593  acquires, as list data of the purchased commodities, the data stored in the transaction memory of the checkout terminal  10 . 
     The storing unit  594  performs a function of storing in the fourth memory  525  the list data of the purchased commodities acquired by the list acquiring unit  593 . 
     The list data of the purchased commodities indicates a list of commodities purchased by the customer who performs checkout processing using the checkout terminal  10 . Therefore, the list data can be used as information representing features of the customer. Thus, the list acquiring unit  593  can acquire the information representing the features of the customer. 
     Like the output unit  515  of the monitoring device  50 , the output unit  595  performs the function of outputting an alert signal if the customer is no longer detected by the customer detecting unit  592  before checkout processing ends. The alert signal includes the list data of the purchased commodities, which is the information stored in the fourth memory  525 , that is, the information representing the features of the customer. For example, the alert signal is output to the attendant terminal  40  via the signal cable  70 . 
     All of the functions of the image acquiring unit  591 , the customer detecting unit  592 , the list acquiring unit  593 , the storing unit  594 , and the output unit  595  explained above are performed by the processor  51  according to a customer monitoring program. 
       FIG.  13    is a flowchart of the information processing executed by the processor  51  of the monitoring device  502  according to the customer monitoring program. A main procedure performed by the monitoring device  502  is explained below with reference to  FIG.  13   . The procedure explained below is an example. The procedure can be changed as appropriate if the same effects can be achieved. 
     As illustrated in  FIG.  13   , in ACT  41 , the processor  51  waits for a checkout start command. In the checkout terminal  10  corresponding to the monitoring device  502 , if the start key displayed on the checkout start screen is touched, whereby a checkout start command is received via the checkout terminal interface  55 , the processor  51  proceeds to ACT  42 . In ACT  42 , the processor  51  initializes the fourth memory  525 . The data stored in the fourth memory  525  is cleared by the initialization. 
     If finishing initializing the fourth memory  525 , the processor  51  proceeds to ACT  43 . In ACT  43 , the processor  51  outputs a start signal to the camera  80  connected to the camera interface  54 . The camera  80  starts an imaging operation according to the start signal. 
     In ACT  44 , the processor  51  acquires a captured image of each frame from the camera  80  via the camera interface  54  as the image acquiring unit  591 . The processor  51  executes processing in ACT  45  and subsequent acts based on the captured image in the frame unit. 
     In ACT  45 , the processor  51  performs object detection processing to detect an object belonging to a person category from the captured image. 
     In ACT  46 , the processor  51  checks whether an object belonging to the person category is successfully detected from the captured image. If an object belonging to the person category is not successfully detected from the captured image in ACT  46 , the processor  51  proceeds to ACT  47 . In ACT  47 , the processor  51  checks whether data is stored in the fourth memory  525 . No data is stored in the fourth memory  525  immediately after the fourth memory  525  is initialized in ACT  42 . In that case, the processor  51  returns to ACT  44 . The processor  51  acquires the next captured image from the camera  80  and executes the processing in ACT  45  and subsequent acts in the same manner as explained above. 
     If an object belonging to the person category is successfully detected from the captured image in ACT  46 , the processor  51  proceeds to ACT  48 . In ACT  48 , the processor  51  issues a request command for list data from the checkout terminal interface  55  as the list acquiring unit  593 . The request command is received by the checkout terminal  10  connected via the signal cable  60 . The processor  181  of the checkout terminal  10  that has received the request command transmits, as a response to the request, list data of purchased commodities stored in the transaction memory to the monitoring device  502 , which is the request command transmission source. If any one of payment methods is selected on the payment method selection screen, the processor  181  issues a checkout end command. 
     The processor  51  of the monitoring device  502  that has transmitted the request command waits for the list data to be received in ACT  49  or the checkout end command to be received in ACT  50 . If the list data is received in the waiting state in ACT  49  and ACT  50 , the processor  51  proceeds to ACT  51 . In ACT  51 , as the storing unit  594 , the processor  51  stores in the fourth memory  525  the list data. 
     Thereafter, the processor  51  returns to ACT  44 . The processor  51  acquires the next captured image from the camera  80  and executes the processing in ACT  45  and subsequent acts. 
     If the checkout end command is received in the waiting state in ACT  49  and ACT  50 , the processor  51  proceeds to ACT  53 . In ACT  53 , the processor  51  outputs a stop signal to the camera  80  connected to the camera interface  54 . The camera  80  stops the imaging operation according to the stop signal. Then, the processor  51  ends the procedure illustrated in the flowchart of  FIG.  13   . Thereafter, in ACT  41 , the processor  51  waits for the next checkout start command again. 
     If the customer performs registration and checkout processing for the purchased commodities by himself or herself using the checkout terminal  10  in this way, usually, the customer keeps standing in the front of the checkout terminal  10  until the checkout processing ends. Therefore, since an object belonging to the person category is continuously detected from an image of each from captured by the camera  80 , the processor  51  repeatedly executes the processing in ACT  48  and subsequent acts on the captured image. As a result, list data of the purchased commodities registered using the checkout terminal  10  by the customer is stored in the fourth memory  525 . 
     If the customer performs operation for paying a price of the purchased commodities on the checkout terminal  10  and the checkout processing ends, the processor  51  ends the information processing shown in  FIG.  13   . The processor  51  clears the fourth memory  525  according to a touch operation on the start key by the next customer. Therefore, the list data of the customer who has ended the checkout processing does not remain in the fourth memory  525 . 
     On the other hand, if the customer goes away from the front of the checkout terminal  10  before the checkout processing ends, any customer cannot be detected from the captured image in the detection processing in ACT  45 . If the customer is no longer detected from the captured image in a state in which the list data of the purchased commodities is stored in the fourth memory  525 , the processor  51  proceeds to ACT  52 . In ACT  52 , the processor  51  outputs an alert as the output unit  595 . Specifically, the processor  51  outputs an alert signal to the attendant terminal  40  via the attendant terminal interface  56 . The alert signal includes the list data of the purchased commodities stored in the fourth memory  525 . 
     The processor  51  that has output the alert proceeds to ACT  53  explained above. That is, the processor  51  outputs a stop signal to the camera  80  connected to the camera interface  54  and ends the information processing shown in  FIG.  13   . 
     In this way, if the customer goes away from the front of the checkout terminal  10  before the checkout processing ends, the alert signal is output from the monitoring device  50  to the attendant terminal  40 . In the attendant terminal  40 , an alert screen is displayed on the display device according to the alert signal. The alert screen is, for example, a screen having the same layout as the alert screen  90  in the first embodiment. On the alert screen  90 , the list data of the purchased commodities is displayed in a region where the captured image is displayed. Therefore, the attendant can easily specify, from the list of the purchased commodities, who is the alert notification target customer. 
     As explained in detail above, in the third embodiment, as in the second embodiment, it is possible to prevent, at a high probability, the customer from going away from the checkout area without completing checkout processing. 
     Moreover, in the third embodiment, a memory for storing an image captured by the camera  80  until the checkout processing ends is unnecessary. Therefore, a required memory capacity can be reduced. 
     Modifications 
     The monitoring device  50  may not be provided to correspond to one checkout terminal  10 . For example, one monitoring device  50  is allocated to two checkout terminals  10 . The monitoring device  50  acquires image data from the cameras  80  connected to the checkout terminals  10  and executes the information processing shown in  FIG.  6 ,  10   , or  13  in parallel. Consequently, the number of monitoring devices  50  can be reduced compared with the number of checkout terminals  10 . Therefore, there is an advantage that system cost can be reduced. 
     The checkout terminal  10  monitored by the monitoring device  50  is not limited to the checkout terminal  10  in the checkout system  100  of a self-service type. For example, there is a checkout system of a semi-self-service type in which a registration machine that performs registration processing for purchased commodities and a checkout machine that performs checkout processing for the purchased commodities are separated, a store clerk operates the registration machine, and a customer operates the checkout machine. The monitoring device  50 ,  501 , or  502  can be applied to the checkout machine of such a checkout system as well. Consequently, it is possible to easily specify a person about to go away without completing checkout processing by the checkout machine. 
     The camera  80  may not be provided in each of the checkout terminals  10 . For example, a plurality of customers who operate checkout terminals  10  may be simultaneously imaged by the camera  80  attached on the ceiling and the like of the checkout area. In the third embodiment, since the monitoring device can detect the customer, the camera  80  may be omitted. For example, the customer may be detected using a human sensor. 
     The embodiments are explained using an example in which one customer is imaged by the camera  80 . However, a group of two or more customers stand in front of the checkout terminal  10  and perform checkout processing. In such a case, the monitoring device  50  calculates posture scores from an image in which those customers are detected and store image data of a maximum posture score in the second memory  522  for each customer. The monitoring device  501  and the monitoring device  502  can advance the subsequent processing by detecting at least one person. 
     The same-customer determination processing in ACT  10  in the first embodiment is not limited to the method of estimating skeleton information. For example, a captured image of each frame may be input to a CNN (Convolutional Neural Network) to calculate a feature vector of a customer and it may be determined, from distance information between the feature vector calculated this time and a feature vector of an immediately preceding customer, whether the customers are the same customer. 
     In the first embodiment, the data of the captured image in which the posture score is the maximum value is stored in the second memory  522 . Concerning this point, data of a plurality of captured images in which posture scores are equal to or larger than a predetermined threshold may be stored in the second memory  522  and the plurality of image data may be transmitted at the time of an alert notification. Consequently, although the memory capacity of the monitoring device  50  increases, it is possible to more accurately specify a customer who goes away without completing checkout processing. 
     In the first embodiment, timing for initializing the first memory  521  and the second memory  522  is not limited to the timing of ACT  2 . For example, the first memory  521  and the second memory  522  may be initialized after the processing in ACT  17 . This point is the same in the second or third embodiment. 
     A notification destination of the alert is not limited to the attendant terminal  40 . For example, the image data or the list data may be transmitted to an information terminal such as a smartphone or a tablet terminal carried by a store clerk together with the alert signal. 
     Timing when the checkout end command is output is not limited to the timing when the checkout screen is displayed. For example, the checkout end command may be output at timing when the checkout screen is displayed and a purchase receipt is dispensed. 
     While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel embodiments described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the embodiments described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the inventions.