JP5853455B2 - Information processing apparatus and method, and program - Google Patents

Description

  The present technology relates to an information processing apparatus, method, and program, and in particular, the player wanted to play the model of the game machine model at the game store or the model provided in the island facility, but could not play the game. The present invention relates to an information processing apparatus and method, and a program, which are obtained from game information of a potential player.

  The environment in which the amusement stores are located is decreasing in the gaming population, and it is aimed at maintaining and securing fixed players who have visited the store, and expanding the number of new players who have not visited the store. In order to differentiate itself from amusement stores, there is a fierce competition for player acquisition centering on game machine replacement and events.

  As one of the efforts, (1) issue a member card or other media, (2) use the membership card when visiting the store, (3) grasp the player's trend from the usage status of the membership card, (4 ) Based on player trends (store visit data), the effectiveness of events is examined and reflected in employee services. Through this initiative, we plan to maintain fixed players and attract new players.

  However, such media efforts have progressed in issuing membership cards, but in reality, it is possible to grasp accurate player trends (visit data) based on the fact that they do not bring them in or do not insert them even if they bring them. However, the current situation is that it has not been reflected in the effectiveness of events and the services of employees.

  In order to solve this problem, there are biometrics that do not use a medium, particularly a face recognition system.

  In recent years, as the representative of applications such as mobile phones and entrance / exit gates, the spread of imaging means by cameras and the improvement of the performance of the one-to-one face authentication system have progressed, and each player is also identified in a game store. It became possible.

  This eliminates the hurdle to use the medium that was the issue of the membership card, identifies the other person, what kind of player is playing in each game machine, the camera installed in the game store and for each game machine It is possible to grasp the player's trend by using.

  Then, by grasping the trend (visit data) of the player, it is possible to reflect the effectiveness of the event for maintaining the fixed player and taking in the new player and the service of the employee.

  As such a technique, a technique for calculating an operating rate of a game machine using a member recording medium has been proposed (see Patent Document 1).

  The replacement timing of the game machine in the current game store is determined from the model of the game machine or the average operating rate of the entire island required by such technology.

JP 2004-195013 A

  However, if the replacement is determined based on the operating rate of the game machine, the replacement is determined in a state that does not take into account the potential player who is not able to play the game even if he wants to play. Although I tried, there was no player, and as a result, the operating rate of the game machine after the replacement sometimes dropped.

  This technology has been made in view of such circumstances, and in particular, in determining the operating rate of each gaming machine in a game store, the degree of attention from potential players who could not play the gaming machine that they wanted to play was calculated. In this way, it is possible to examine the replacement of the game table in consideration of the potential player.

  An information processing apparatus according to one aspect of the present technology includes a gaming table imaging unit that images a player who plays on the gaming table for each gaming table installed in a gaming store, and a corner provided with a plurality of the gaming tables, or A corner imaging unit that images a player entering or leaving the island facility unit, the game table imaging unit, a verification unit that matches a player imaged by the corner imaging unit with a registrant, and the verification unit An entrance management unit for managing the entry time for each corner for each player verified by the above, an exit management unit for managing the exit time for each corner for each player verified by the verification unit, and the gaming table. Admission is managed by the game start management unit that manages the game start time for each gaming table for each player collated by the collation unit, and the admission management unit, depending on the presence or absence of the player imaged by the imaging unit , In the verification part Based on the start time of the game managed by the game start management unit of the checked player, the player wanted to play the model of the game machine installed in the corner A potential player determination unit that determines whether or not the player is a potential player who could not play a game, and a predetermined model of a game machine installed in the game store is determined as a potential player by the potential player determination unit And a degree-of-interest calculation unit that calculates the degree of attention of the gaming machine of the predetermined model based on the information on the entry time and the exit time of the player who has been played.

  Based on the admission time and the leaving time, it is possible to further include a stay time calculation unit that calculates a stay time of the corner for each player collated by the collation unit, and the potential player determination The player has a potential for the player when the stay time of the player in the corner is longer than a predetermined time and the game start time is not registered within the stay time of the player in the corner. It can be made to determine as a player.

  The attention level calculation unit is calculated by the stay time calculation unit of a player determined as a potential player by the potential player determination unit with respect to a predetermined model of a game machine installed in the gaming store. It is possible to calculate the total stay time calculated from the information on the entrance time and the exit time as the attention level.

  The attention level calculation unit includes the entry time and the exit time of a player determined as a potential player by the potential player determination unit with respect to a predetermined model of a game machine installed in the game store. The admission calculated by the stay time calculation unit for the gaming machine operating according to the gaming machine operating information based on the information and the gaming machine operating information indicating whether or not the gaming machine is operating. The sum of the stay time calculated from the time and the information of the leaving time can be calculated as the attention level.

  It is possible to include a display unit that displays the attention level of the gaming machine that is the predetermined model calculated by the attention level calculation unit in units of the predetermined model or in units of predetermined corners. .

  An information processing method according to an aspect of the present technology is provided for each gaming machine installed in the gaming store in the gaming machine imaging unit that captures a player playing on the gaming machine for each gaming machine installed in the gaming shop. A game table imaging step for imaging a player playing a game on a game table, and a corner imaging unit for imaging a player provided with a plurality of the game tables, or a player who enters or leaves an island facility unit. A corner provided with a plurality of pedestals, or a corner imaging step for imaging a player who enters or leaves the island facility unit, the game table imaging unit, and a player imaged by the corner imaging unit as a registered person A matching step for matching the player imaged by the processing of the gaming table imaging step and the corner imaging step with a registrant in the matching unit for matching In the admission management unit that manages the admission time for each corner for each verified player, the admission management step for managing the admission time for each corner for each player collated by the process of the verification step, and the verification Exit management step for managing the exit time for each corner for each player collated by the processing of the collation step in the exit management unit for managing the exit time for each corner for each player collated by the unit; Processing of the game table imaging step in the game start management unit that manages the game start time for each game table for each player collated by the collation unit based on the presence or absence of the player imaged by the game table imaging unit The game start for managing the game start time for each gaming table for each player collated by the process of the collation step depending on the presence or absence of the player imaged by Based on the game start time managed by the game start management unit of the player verified by the verification unit, and the player managed by the verification unit. Admission is performed by the process of the admission management step in the potential player determination unit that determines whether or not the player is a potential player who has not been able to play a game, although he / she wanted to play the model of the gaming table installed in the corner. Based on the managed game start time managed by the game start management step of the player collated by the process of the collation step, the player is installed at the corner. A potential player determination step for determining whether or not the player is a potential player who has not been able to play the game, but a predetermined game table installed in the game store. Attention to calculate the degree of attention of the gaming machine as the predetermined model based on the information on the entrance time and the exit time of the player determined as the potential player by the potential player determination unit for the model Information on the entry time and the exit time of the player determined as a potential player by the processing of the potential player determination step for a predetermined model of the game machine installed in the game store in the degree calculation unit And a degree-of-attention calculation step for calculating the degree of attention of the gaming machine as the predetermined model.

  A program according to one aspect of the present technology includes a game table imaging unit that images a player who plays on the game table for each game table installed in a game store, and a corner or an island provided with a plurality of the game tables. A corner imaging unit that images a player entering or leaving a facility unit, the game table imaging unit, a verification unit that matches a player imaged by the corner imaging unit with a registrant, and a verification by the verification unit An entrance management unit for managing the entrance time for each corner for each player, an exit management unit for managing the exit time for each corner for each player collated by the collation unit, and the gaming table imaging unit The admission is managed by the admission management unit, the game start management unit managing the game start time for each gaming table for each player collated by the collation unit, depending on the presence or absence of the player imaged by By collation Based on the match start time of the game managed by the game start management unit of the player, the player wishes to play the game machine type installed at the corner. A potential player determination unit that determines whether or not a potential player has failed to play a game, and a predetermined model of a gaming table installed in the game store is determined as a potential player by the potential player determination unit. A computer that controls an information processing device including an attention level calculation unit that calculates the attention level of the gaming machine that is the predetermined model based on information on the entry time and the exit time of the player. A gaming table imaging step for imaging a player playing on the gaming table for each gaming table installed in the gaming store in the gaming table imaging unit, and a plurality of the gaming tables in the corner imaging unit are provided. A corner imaging step for imaging a player who enters or leaves a corner or island facility unit, and a player imaged in the matching table imaging step and the corner imaging step in the matching unit as a registrant. A collation step for collation, an admission management step for managing an entry time for each corner for each player collated by the process of the collation step in the admission management unit, and a process for the collation step in the exit management unit The exit management step for managing the exit time for each corner for each player collated by the above, and the presence or absence of the player imaged by the processing of the game table imaging step in the game start management unit, A game start management step for managing a game start time for each of the game machines for each of the players verified by the processing; At the game start time managed by the game start management step of the player whose entry has been managed by the process of the admission management step and who has been verified by the process of the verification step Based on the potential player determination step of determining whether or not the player is a potential player who wanted to play the model of the gaming table installed in the corner but could not play the game, The entrance time and the exit time of the player determined as a potential player by the processing of the potential player determination step for a predetermined model of the game machine installed in the game store in the attention level calculation unit. A program for executing a process including an attention level calculation step for calculating the attention level of the gaming machine as the predetermined model based on the information of the above.

  In one aspect of the present technology, a player who plays on the gaming table is imaged for each gaming table installed in a gaming store, and a corner where a plurality of the gaming tables are provided, or entry in units of island facilities, or The leaving player is imaged, the imaged player is collated with the registrant, the entry time for each corner is managed for each collated player, and the exit time for each corner for each collated player Are managed and the game start time of each game machine is managed for each verified player, and the managed game of the verified player is managed for admission according to the presence or absence of the imaged player Based on the start time of the game, it is determined whether or not the player is a potential player who wanted to play the model of the game stand installed in the corner but could not play the game. To the predetermined model of the game stand installed in the store There are, of the player that has been determined as a potential player, on the basis of the entrance time, and the information of the exit time, game machine of attention as the predetermined model is calculated.

  That is, in the information processing apparatus according to one aspect of the present technology, for each gaming table installed in a gaming store, the gaming table imaging unit that captures a player playing on the gaming table is, for example, each camera. A corner provided with a plurality of game machines or a corner image pickup unit that picks up an image of a player who enters or leaves an island facility unit is, for example, an in-store camera, the game table image pickup unit, and the corner image pickup unit. The collation unit that collates the player imaged by the registrant is, for example, a collation unit, and the admission management unit that manages the admission time for each corner for each player collated by the collation unit, For example, the exit management unit that is a corner entrance management unit and manages the exit time of each corner for each player verified by the verification unit is, for example, a corner exit management unit, and the gaming table imaging unit Imaged For example, the game start management unit that manages the game start time for each gaming table for each player collated by the collation unit according to the presence or absence of the player is a game start management unit, and the admission management unit Based on the start time of the game managed by the game start management unit of the player verified by the verification unit whose entry is managed, the player sets the model of the game machine installed at the corner A potential player determination unit that determines whether or not a potential player who was able to play a game but could not play is, for example, a potential player determination unit, and is installed in the game store. Regarding the predetermined model of the gaming machine, the attention of the gaming machine that becomes the predetermined model based on the information of the entry time and the leaving time of the player determined as the potential player by the potential player determination unit Calculate degree The that attention degree calculation unit, for example, an attention DB management unit.

  That is, for each player collated by the collation unit, the stay time based on the stay time at the corner by the corner entrance management unit and the corner exit management unit and the game start time managed by the game start management unit Is longer than the predetermined time, there is no information on the game start time within the stay time, and if the game is played on any of the game tables in the corner within the stay time, the player is regarded as a potential player, The attention level DB management unit regards the gaming bases in the corner as gaming bases that are playing, and adds the staying time cumulatively to calculate the attention level as the attention level for each gaming base. Register in DB.

  As a result, it is possible to obtain the attention level of a potential player who has a high possibility of wanting to play a game, although he / she has not actually played a game for each model of the game stand. In other words, since it is possible to grasp the trends of potential players who are not actually playing a game machine but want to play, it is necessary to make an appropriate selection when selecting a model to replace a game machine. It can be used as a reference.

  According to this technology, it is possible to calculate the degree of attention for each model of the appropriate game machine for considering the replacement of the game machine, and it is possible to select the game machine model to be replaced more appropriately. It becomes.

It is a figure showing the composition of the 1 embodiment of the surveillance system to which this art is applied. It is a figure which shows the example of installation of the camera of FIG. It is a figure which shows the example of installation of the camera of FIG. It is a figure which shows the example of installation of the camera of FIG. It is a figure which shows the example of installation of the camera of FIG. It is a figure which shows the example of installation of the camera of FIG. It is a figure which shows the example of installation of the camera of FIG. It is a figure which shows the example of installation of the entrance camera and shop camera of FIG. It is a figure explaining the structural example of the image processing unit of FIG. 1, a biometric information recognition apparatus, and a game store management apparatus. It is a flowchart explaining the face image detection process by each stand image processing unit. It is a flowchart explaining the face image detection process by an image processing unit. It is a flowchart explaining a table allocation information acquisition process. It is a figure which shows the structural example of stand allocation DB. It is a flowchart explaining a customer management DB management process. It is a flowchart explaining a customer management DB management process. It is a figure which shows the structural example of customer management DB. It is a figure which shows the structural example of attention level DB. It is a flowchart explaining attention degree display processing. And FIG. 11 is a diagram illustrating a configuration example of a personal computer.

  Embodiments of the present technology will be described below. Correspondences between the configuration requirements of the present technology and the embodiments described in the detailed description of the present invention are exemplified as follows. This description is intended to confirm that the embodiments supporting the present technology are described in the detailed description of the invention. Therefore, although there are embodiments that are described in the detailed description of the invention but are not described here as embodiments corresponding to the constituent elements of the present technology, It does not mean that the embodiment does not correspond to the configuration requirements. Conversely, even if an embodiment is described here as corresponding to a configuration requirement, that means that the embodiment does not correspond to a configuration requirement other than the configuration requirement. It's not something to do.

  In other words, the information processing apparatus according to one aspect of the present technology includes a game table imaging unit (for example, each camera 38 in FIG. 9) that images a player who plays on the game table for each game table installed in the game store. A corner provided with a plurality of the game tables, or a corner image pickup unit (for example, the in-store camera 42 in FIG. 9) that picks up an image of a player who enters or leaves an island facility, and the game table image pickup unit; A collation unit (for example, collation unit 293 in FIG. 9) that collates a player imaged by the corner imaging unit with a registrant, and manages an entry time for each corner for each player collated by the collation unit. An entrance management unit (for example, the corner entrance management unit 294a of FIG. 9) and an exit management unit (for example, the corner exit management unit of FIG. 9) that manages the exit time for each corner for each player collated by the collation unit 294b) and the above A game start management unit (for example, the game start management unit in FIG. 9) that manages the game start time for each game table for each player collated by the collation unit based on the presence or absence of the player imaged by the technical table imaging unit. 294c), and based on the game start time managed by the game start management unit of the player whose entry is managed by the admission management unit and verified by the verification unit, A potential player determination unit (for example, the potential player determination unit in FIG. 9) that determines whether or not the player is a potential player who wanted to play a model of a gaming table installed at a corner but could not play a game. 294e) and a predetermined model of the game machine installed in the game store based on the information of the entry time and the exit time of the player determined as a potential player by the potential player determination unit. , Attention degree calculation unit that calculates a game machine of attention as a serial predetermined model (e.g., attention DB management unit 294g in FIG. 9) and a.

  Based on the entrance time and the exit time, a stay time calculation unit (for example, a stay time calculation unit 294f in FIG. 9) that calculates the stay time of the corner for each player collated by the collation unit is further included. In the potential player determination unit, the stay time of the player in the corner is longer than a predetermined time, and the game start time is within the stay time of the player in the corner. When no is registered, the player can be determined as a potential player.

  A display unit (for example, the display unit 23 in FIG. 9) that displays the attention level of the gaming machine of the predetermined model calculated by the attention level calculation unit in units of the predetermined model or in units of predetermined corners. Can be included.

  An information processing method and program according to an aspect of the present technology is provided for each gaming machine installed in the gaming store in a gaming machine imaging unit that captures a player who plays in the gaming machine for each gaming machine installed in the gaming machine. A game table imaging step (for example, step S11 in FIG. 10) for imaging a player who plays on the game table, and a game that enters or leaves in units of corners or island facilities provided with a plurality of the game tables. In a corner imaging unit that images a person, a corner imaging step (for example, step S31 in FIG. 11) for imaging a corner in which a plurality of the game tables are provided, or a player who enters or leaves an island facility unit, Processing of the gaming table imaging step and corner imaging in the game table imaging unit and a matching unit that matches a player imaged by the corner imaging unit with a registrant A collation step (for example, steps S94 to S101 in FIG. 14) for collating the player imaged by the processing of the step with the registrant, and managing the entrance time for each corner for each player collated by the collation unit In the admission management unit, an admission management step (for example, steps S105 and S106 in FIG. 15) for managing the admission time for each corner for each player collated by the process of the collation step, and collation by the collation unit In the exit management unit that manages the exit time for each corner for each player, the exit management step for managing the exit time for each corner for each player collated by the process of the collation step (for example, step of FIG. 15). S107, S112) and the game collated by the collation unit based on the presence / absence of the player imaged by the game table imaging unit In the game start management unit that manages the game start time for each gaming table for each player, the presence / absence of the player imaged by the processing of the gaming table imaging step for each player verified by the processing of the verification step A game start management step (for example, step S104 in FIG. 15) for managing a game start time for each gaming table, and an entry managed by the admission management unit, and the game start of the player collated by the collation unit Based on the game start time managed by the management unit, whether the player is a potential player who wanted to play a model of the game machine installed in the corner but could not play a game In the potential player determination unit that determines whether or not the admission is managed by the process of the admission management step, the player of the player collated by the process of the collation step Based on the start time of the game managed by the process of the technique start management step, the player wishes to play the model of the game machine installed in the corner, but the potential game that could not be played A potential player determination step (for example, steps S108 to S110 in FIG. 15) for determining whether or not the player is a player, and a predetermined model of a game machine installed in the game store, the potential player determination unit Installed in the game store in the attention level calculation unit that calculates the attention level of the gaming machine of the predetermined model based on the information on the entry time and the exit time of the player determined as the player. Based on the information on the entry time and the exit time of the player determined as a potential player by the processing of the potential player determination step for a predetermined model of the game machine. Te, and an attention degree calculation step (e.g., step S111 in FIG. 15) for calculating a game machine of attention as a predetermined model.

[Configuration example of monitoring system embodiment]
FIG. 1 is a diagram illustrating a configuration example of an embodiment of a monitoring system using an information processing apparatus according to the present technology.

[Example of monitoring system configuration]
The game stores 1-1 to 1-n are so-called pachinko stores, pachislot stores, or casino stores. These amusement stores 1-1 to 1-n are affiliated stores or member stores of the biometric information management center or the third party amusement store management center, and stores that need to manage a plurality of stores in an integrated manner. It is. The game stores 1-1 to 1-n are connected by a third-party game store management bus 4 and are connected to each other through a public communication line network 5 represented by the bus and the Internet. Amusement store management information is exchanged. In the following description, when there is no particular need to distinguish each of the game stores 1-1 to 1-n, the game store 1 is simply referred to, and the other configurations are also referred to in the same manner.

  The third-party amusement store management bus 4 functions as a transmission path for distributing medium lending management information managed mainly by the medium lending management device 27 of each amusement store 1.

  The third-party amusement store management center 2 is a server used by a business operator that manages and operates the third-party amusement store management center, and the medium lending management managed by the third-party amusement store management database (DB) 3 In addition to updating the information DB based on the information supplied from each game store 1, the updated latest medium lending management information is distributed to the medium lending management device 27 of each game store 1.

  The biological information recognizing device 21 includes image data processing units 39 based on images captured by the cameras 38-1 to 38-m, the entrance cameras 41-1 to 41-p, and the in-store cameras 42-1 to 42-q. -1 to 39-m and the image processing units 40-1 to 40- (p + q), and are stored in the biological information database 22 in advance based on the facial image information supplied via the biological information bus 31. When matching with the registered face image, if it matches, the mobile terminal 20 is notified of the registered player's visit, or displayed on the display unit 23 such as an organic EL (Electro Luminescence) or LCD (Liquid Crystal Display). .

  The game store management device 24 is a so-called hall computer, and monitors the operations of the in-ball counter 251 and the out-ball counter 252 of the game table 36 via the game store management information bus 30. The game store management device 24 is configured to provide information on the game balls 36 to be paid out or the payout of medals, the number of game balls to be discharged without winning a prize, and the game machines 36-1 to 36-m. A predetermined process is executed according to the call information of the player or the monitoring situation such as the occurrence of an error, and the execution result is displayed on the display unit 25 such as an organic EL or LCD. The game store management device 24 identifies information supplied from the counter 35, the game machines 36-1 to 36-m, and the game machine peripheral terminals 37-1 to 37-m, respectively. For example, it is managed by the gaming machine management database 26 in association with the gaming machine number.

  The medium lending management device 27 manages the medium lending management information of the rented game media using the medium lending management database 29 based on the information from the payment machine 33 and the lending machine 34, and also the medium lending management database. When the medium lending management information registered in 29 is updated, the updated information is sent to the third party amusement store management center 2 via the third party amusement store management bus 4 and the public communication network 5. Further, the medium lending management device 27 acquires the medium lending management information supplied by the third party amusement store management center 2 via the third party amusement store management bus 4 and the public communication line network 5, and the medium lending management is performed. Store in the database 29.

  The lending machine 34 lends a number of game media according to the amount when the player accepts a predetermined amount by cash or a prepaid card when playing on the gaming table 36. At this time, the lending machine 34 supplies information on the number of lent gaming media to the medium lending management device 27 together with information such as the accepted cash and the remaining number of prepaid cards. Accordingly, the medium lending management device 27 registers information on the number of lent gaming media in the medium lending management database 29 together with information such as the accepted cash and the remaining number of prepaid cards.

  The checkout machine 33 sells prepaid cards with a frequency for borrowing a ball. At this time, the checkout machine 33 supplies the frequency of the prepaid card sold and the amount paid to the medium lending management device 27. Further, the settlement vending machine 33 settles and pays out cash based on the remaining number of game media lent as a frequency such as a prepaid card. At this time, the checkout machine 33 supplies the remaining number of prepaid cards and the amount of cash refunded to the medium lending management device 27.

  The counter 35 counts the number of game media acquired by the player playing on the game table 36, and outputs the counting result as a magnetic card or a receipt.

  The game machines 36-1 to 36-m execute a game when a predetermined operation is performed by the player, and pay out a game ball or a medal according to a so-called small hit or big hit.

  The game console peripheral terminals 37-1 to 37-m are so-called pedestrian machines provided corresponding to the respective game machines 36-1 to 36-m. The same as the lending machine 34) is provided. Further, the gaming machine peripheral terminal 37 acquires biological information such as a face image of the player who plays the gaming machine 36 and transmits it to the biological information recognition device 21 together with the gaming machine identification information (game machine number). FIG. 1 shows an example in which each camera 38-1 to 38-m that acquires a player's face image is provided for each gaming table 36 as a function for acquiring biological information.

  The entrance cameras 41-1 to 41-p and the in-store cameras 42-1 to 42-q are installed at entrances and predetermined places in the store of the amusement store 1, and imaged units 40-1 to 40- (P + q).

  For example, as shown in FIG. 2, each of the cameras 38-1 to 38-m is a table display lamp 61-1 to 61-4 provided on each of the game tables 36-1 to 36-4. As shown in FIG. 3, the player may be provided within the reading range δ so that the player can take an image so that a face image can be taken. It can be used as a stand ID.

  Further, each of the cameras 38-1 to 38-m is provided with convex portions 71-1 to 71-4 on the gaming machine peripheral terminals 37-1 to 37-4 as shown in FIG. As shown by the above, it may be provided so that a player's face image can be captured within the reading range θ.

  Further, each of the cameras 38-1 to 38-m may be provided in the center of the game table 36 (on the board surface of the game table 36), for example, as shown in FIG. Good. That is, as each camera 38 is installed in the installation unit 81 in FIG. 6, the player is imaged within the reading range φ as shown in FIG.

[Installation position of entrance camera and in-store camera]
The entrance cameras 41-1 to 41-p and the in-store cameras 42-1 to 42-q are installed at entrances and predetermined places in the store of the amusement store 1, and imaged units 40-1 to 40- (P + q).

  The entrance cameras 41-1 to 41-p and the in-store cameras 42-1 to 42-q are set as shown in FIG. 8, for example. FIG. 8 shows an installation example of the entrance cameras 41-1 to 41-p and the in-store cameras 42-1 to 42-q in the game store 1.

  That is, in FIG. 8, entrances 112-1 to 112-3 are provided, and the entrance cameras 41-1 to 41-3 image players who enter the store through the respective entrances and exits 112. Further, the in-store cameras 42-1 to 42-16 are provided at positions where the player can check the entrance and exit of the corners set by the island facilities 111-1 to 111-5, respectively. More specifically, the in-store cameras 42-1 to 42-4 take images of players who enter and exit the corners in the island facilities 111-1, 111-2. That is, here, the in-store cameras 42-2 and 42-3 image the players who enter the corners of the island facilities 111-1 and 111-2, and the in-store cameras 42-1 and 42-4 The player who leaves the corner in 111-1, 111-2 is imaged. Similarly, the in-store cameras 42-5 to 42-8 capture images of players who enter and exit the corners in the island facilities 111-2 and 111-3. Further, the in-store cameras 42-9 to 42-12 take pictures of players entering and exiting the corners in the island facilities 111-3 and 111-4, and the in-store cameras 42-13 to 42-16 are used for the island facilities 111-4. , 111-5, the player entering and exiting the corner is imaged. Since each of the cameras 38, the entrance camera 41, and the in-store camera 42 all have a pan / tilt / zoom function, the in-store cameras 42-1 to 42-16 are arranged as shown in FIG. All players who play on the game stand 36 can take an image with any of the in-store cameras 42-1 to 42-16.

  Furthermore, the in-store camera 42-a is provided in front of the lending machine 34, the in-store camera 42-b is provided in front of the checkout machine 33, and the in-store camera 42-c is the counter of the counter 35. It is provided in front, and a player who uses the rental machine 34, the checkout machine 33, and the counter 35 can be imaged.

  That is, as shown in FIG. 8, in the game store 1, a player who visits the store, a player who plays on the game stand 36, and a player who uses the lending machine 34, the checkout machine 33, and the counter 35. Each camera 38, the entrance camera 41, and the in-store camera 42 are installed so that almost all the actions that the player is supposed to take in the gaming store 1 can be monitored.

[Configuration example of functions realized by amusement facility]
Next, with reference to FIG. 9, the structural example of the function implement | achieved by the installation in the game store 1 is demonstrated.

  Each table image processing unit 39 includes an image acquisition unit 211, a face image detection unit 212, a feature amount extraction unit 213, a feature amount data table 214, a collation unit 215, and a transmission unit 216.

  The image acquisition unit 211 of each stand image processing unit 39 acquires an image captured by each stand camera 38 and supplies the acquired image to the face image extraction unit 212. The face image extraction unit 212 extracts a rectangular image made up of a face image from the image supplied from the image acquisition unit 211 using a pattern such as the arrangement of the parts constituting the face, and supplies the extracted rectangular image to the feature amount extraction unit 213. The feature amount extraction unit 213 extracts a feature amount for identifying the face image, and supplies the feature amount together with the face image to the collation unit 215 and the feature amount data table 214. The feature amount data table 214 stores the feature amount extracted from the face image of the immediately preceding frame in association with the frame number, and supplies it to the collation unit 215. The collation unit 215 obtains the similarity between the feature amount of the latest frame supplied from the feature amount extraction unit 213 and the feature amount obtained from the immediately preceding frame, and compares the face value of the immediately preceding frame with a predetermined threshold value. The image is compared with the face image of the current frame, and in the latest frame, a new face image is detected, the game starts, the same person exists and the game continues, immediately after the person is replaced It is determined whether the game has been started or the person has finished the game, and information on the feature amount is supplied to the transmission unit 216 together with the determination result. The transmission unit 216 transmits the face image and the collation result of the collation unit 215 to the biometric information recognition device 21. When transmitting the face image and the determination result, the transmission unit 216 transmits the face ID and the determination result to the biometric information authentication device 21 together with a camera ID for identifying which game stand 36 each camera 38 is provided on.

  The image processing unit 40 includes an image acquisition unit 231, a face image detection unit 232, and a transmission unit 233. The image acquisition unit 231 of the image processing unit 40 acquires an image captured by the entrance camera 41 or the in-store camera 42 and supplies it to the face image extraction unit 232. The face image extraction unit 232 extracts a rectangular image made up of face images from the image supplied from the image acquisition unit 231 by using a pattern such as the arrangement of parts constituting the face, and supplies the extracted image to the transmission unit 233. The transmission unit 233 transmits the face image to the biological information recognition device 21. When transmitting the face image, the transmission unit 233 transmits the face image to the biometric information authentication apparatus 21 together with a camera ID for identifying where the entrance camera 41 or the in-store camera 42 is provided.

  The amusement shop management device 24 includes a control unit 271, a table allocation DB 272, a transmission / reception unit 273, and a display unit 25.

  The control unit 271 controls the overall operation of the game store management device 24. Based on the camera ID, the table allocation DB 272 includes information indicating which game machine number of the game machine 36 is set, which corner is set by the island facility 111, and which corner is the camera that is imaging the entrance. It is an assigned database. When the base allocation DB 272 is requested from the biological information recognition device 21, the control unit 271 controls the transmission / reception unit 273 to transmit the base allocation DB 272.

  The transmission / reception unit 291 of the biometric information recognition apparatus 21 acquires the face image supplied from each of the image processing units 39 and the image processing unit 40 and various notifications, and supplies them to the notification determination unit 292. The notification determination unit 292 determines whether the notification supplied from the transmission / reception unit 291 is the absence detection, the same person detection, or the person detection, and for the absence notification, the information is stored in the DB registration update unit. 294. In addition, in the case of person detection, the notification determination unit 292 supplies person detection information to the collation unit 293.

  The collation unit 293 registers the face image information supplied by the person detection in the customer management DB 295 and collates with any person registered in the customer management DB 295 to obtain a collation result. The data is supplied to the DB registration update unit 294 together with the person ID. More specifically, the collation unit 293 includes a feature amount extraction unit 311, a similarity calculation unit 312, a similarity calculation result accumulation unit 313, a similarity calculation result totaling unit 314, and a similarity determination unit 315. The feature amount extraction unit 311 extracts various feature amounts necessary for matching the face image from the face image, and supplies the face image to the similarity calculation unit 312 together with the extracted feature amount. The similarity calculation unit 312 is based on the feature amounts of all the face images registered in the customer management DB 295 supplied from the database management unit 296 and the feature amounts supplied from the feature amount extraction unit 311. The similarity is calculated and stored in the similarity calculation result storage unit 313. The similarity calculation result totaling unit 314 includes a face image having the highest similarity among all the similarities accumulated in the similarity calculation result accumulating unit 313 and information on the degree of similarity. 315 is supplied. When the supplied highest similarity is higher than a predetermined threshold, the similarity determination unit 315 considers that the face image registered in the customer management DB 295 matches the corresponding person ID. The notification information supplied together with the information is output to the DB registration / updating unit 294. In addition, the similarity determination unit 315 considers that the supplied topmost similarity is not higher than a predetermined threshold value and does not match the face image registered in the customer management DB 295, The face image is supplied to the registration unit 301, a new person ID is set and registered in the customer management DB 295, and the notification information supplied together with the registered person ID is output to the DB registration update unit 294.

  The DB registration update unit 294 registers the customer management DB 295 and the attention level DB 302 based on information such as absence detection, same person detection, or person detection supplied from the notification determination unit 292 or the collation unit 293. More specifically, the DB registration update unit 294 includes a corner entrance management unit 294a, a corner exit management unit 294b, a game start management unit 294c, a game end management unit 294d, a potential player determination unit 294e, a stay time calculation unit 294f, and Attention level DB management unit 294g is provided. The corner entrance management unit 294a, based on the information of the person detection, based on the supplied person ID of the authenticated player, the face image captured by the in-store camera 42 at the entrance of a predetermined corner from the camera ID. Information on the time of entering a person's corner is registered in the customer management DB 295. The corner exit management unit 294b, based on the information of the person detection, based on the supplied person ID of the authenticated player, the face image captured by the in-store camera 42 at a predetermined corner exit from the camera ID. Information on the time of leaving the person's corner is registered in the customer management DB 295.

  Based on the person detection information, the game start management unit 294c captures an image from each camera 38 of the gaming machine 36 having a predetermined gaming machine number based on the supplied person ID of the authenticated player. When the detected face image is detected, the face image is considered to be in operation, and information on the time is registered in the customer management DB 295 as game start information. If the face image captured by each camera 38 of the gaming machine 36 with a predetermined gaming machine number is not detected from the supplied camera ID based on the information on the absence detection, the gaming end management unit 294d The time information is registered in the customer management DB 295 as game end information.

  The potential player determination unit 294e controls the stay time calculation unit 294f based on the information stored in the customer management DB 295 of the player of the facial image captured by the in-store camera 42 at the predetermined corner exit from the camera ID. Then, based on whether or not the corner's game table 36 is played within the stay time, the player wants to play but does not play the corner. It is determined whether or not the potential player is staying. If the player is a potential player, the attention level DB management unit 294g regards the gaming stand 36 present in the corner as the attention stand, calculates the attention degree by accumulating the staying time, and determines the degree of attention for each gaming stand 36. Register in the attention level DB 302.

  The table allocation information management unit 298 requests the game store management device 24 for information on the table allocation DB 272 at predetermined intervals, such as the morning time when the game store 1 is activated, and uses the acquired information on the table allocation DB 272 as a table. The allocation DB 297 is updated.

  The attention level display control unit 299 is registered in the attention level DB 302 when an operation unit 300 including a keyboard and operation buttons is operated and an instruction to that effect is received so as to display the attention level for a specific model of the gaming machine 36. Of the attention level information, the attention level and the number of potential players for the gaming table 36 that are requested to display the attention level are read out, and appropriate for considering replacement of the gaming table 36. The attention level is displayed on the display unit 23. At this time, the attention level display control unit 299 controls the operation rate calculation unit 299a to calculate the corresponding operation rate for the gaming machine 36 for which the attention level display is requested, and calculates the operation rate together with the attention level. It is displayed on the display unit 23.

[Face image detection processing by each stand image processing unit]
Next, the face image detection process by each stand image processing unit 39 will be described with reference to the flowchart of FIG.

  In step S <b> 11, each camera 38 captures the direction in which the player is present from the installed position, and supplies the captured image to each camera image processing unit 39. The image acquisition unit 211 of each stand image processing unit 39 acquires the supplied image and supplies it to the face image detection unit 212.

  In step S <b> 12, the face image extraction unit 212 extracts a rectangular image composed of the face image from the image supplied from the image acquisition unit 211 using a pattern such as the arrangement of the parts constituting the face, and the feature amount extraction unit 213. To supply.

  In step S13, the face image extraction unit 212 determines whether or not a face image has been extracted from the image. If the face image can be extracted in step S13, the process proceeds to step S14.

  In step S <b> 14, the feature amount extraction unit 213 extracts a feature amount for identifying the face image, and supplies the feature amount together with the face image to the matching unit 215 and the feature amount data table 214. The feature amount data table 214 stores the feature amount extracted from the face image of the immediately preceding frame in association with the frame number, and supplies it to the collation unit 215.

  In step S15, the collation unit 215 obtains the similarity between the feature amount of the latest frame supplied from the feature amount extraction unit 213 and the feature amount obtained from the immediately preceding frame.

  In step S <b> 16, the matching unit 215 determines that the calculated similarity is higher than a predetermined threshold, the face image of the previous frame matches the face image of the current frame, and When it is determined that the same player is captured, the process proceeds to step S17.

  In step S17, the collation unit 215 controls the transmission unit 216 to identify the previous player including the camera ID for identifying each camera 38 that captured the face image, information about the imaging time, and information about the face image. A notification of the same person detection indicating that the same player is imaged is transmitted to the biometric information recognition device 21.

  On the other hand, if it is determined in step S16 that the similarity is not higher than the predetermined threshold and a face image of a new player different from the player imaged in the immediately preceding frame has been captured, the process proceeds to step S18. move on.

  In step S18, the collation unit 215 controls the transmission unit 216 to perform collation of the face image including the camera ID for identifying each camera 38 that captured the face image, information on the imaging time, and information on the face image. A notification of person detection indicating that a face image that has not been detected has been detected is transmitted to the biometric information recognition device 21.

  If it is determined in step S13 that a face image could not be extracted, the process proceeds to step S19.

  In step S19, the matching unit 215 determines whether or not a face image has been detected in the immediately preceding frame based on information recorded in the feature amount data table 214. That is, when it is known that the player has played a game until just before, the process proceeds to step S20.

  In step S20, the collation unit 215 controls the transmission unit 216 to play the game of the face image that has been collated immediately before, including the camera ID for identifying each camera 38 that captured the face image and the information of the imaging time. A notification of absence detection is transmitted to the biometric information recognition device 21 to indicate that the person has finished the game and has left the game.

  If no face image is detected in the immediately preceding frame in step S19, the process in step S20 is skipped.

  With the above processing, each of the stand image processing units 39 includes the camera ID for picking up the image, the time of image pickup, and the face image as necessary according to the face image of the player picked up by each stand camera 38. The three types of notifications of the same person detection, the person detection, and the absence detection can be transmitted to the biometric information recognition device 21.

[Face image detection processing by image processing unit]
Next, face image detection processing by the image processing unit 40 will be described with reference to the flowchart of FIG.

  In step S31, the in-store camera 42 captures an entrance or exit near a corner set by the island facility 111 from an installed position, and captures an image in a direction where a player entering or leaving the corner exists. Then, the captured image is supplied to the image processing unit 40. The image acquisition unit 231 of the image processing unit 40 acquires the supplied image and supplies it to the face image extraction unit 212.

  In step S <b> 32, the face image extraction unit 232 extracts a rectangular image composed of the face image from the image supplied from the image acquisition unit 231 using a pattern such as the arrangement of the parts constituting the face, and supplies the extracted rectangular image to the transmission unit 233. To do.

  In step S33, the face image extraction unit 232 determines whether or not a face image can be extracted from the image. If the face image can be extracted in step S33, the process proceeds to step S34.

  In step S34, the transmission unit 233 detects that a face image that has not been collated is detected, including a camera ID that identifies the in-store camera 42 that captured the face image, imaging time, and face image information. The notification of person detection shown in FIG. still. If the face image cannot be extracted in step S33, the process in step S34 is skipped.

  Through the above processing, the image processing unit 40 extracts the face image of the player who enters or leaves each corner imaged by the in-store camera 42, and captures the camera ID, the imaging time, and the face image. It is possible to transmit a person detection notification including the information to the biometric information recognition device 21.

[Table allocation information acquisition processing]
Next, the base allocation information acquisition process will be described with reference to the flowchart of FIG.

  In step S61, the table allocation information management unit 298 determines whether or not the biometric information recognition apparatus 21 has been activated, and the same processing is repeated until it is deemed to have been activated. In step S61, for example, when it is confirmed that the program is activated, the process proceeds to step S62.

  In step S62, the table allocation information management unit 298 controls the transmission / reception unit 291 to request the game store management device 24 for information on the table allocation DB 272.

  In step S71, the control unit 271 of the gaming store management device 24 controls the transmission / reception unit 273 to determine whether or not table allocation information has been requested, and the same processing is repeated until requested. In step S71, when the table allocation information is requested by the process of step 62 described above, the process proceeds to step S72.

  In step S <b> 72, the control unit 271 reads information in the table allocation DB 272. The table allocation DB 272 is, for example, as shown in FIG. In the table allocation DB 272 of FIG. 13, a camera ID column, an area column, a detail column, a model column, and a corner information column are provided from the left.

  As shown in the uppermost part of FIG. 13, for example, the camera with the camera ID C1 is the in-store camera 42 provided at the entrance of the first island facility 111, which is a one-yen corner. The second row shows that the camera with the camera ID C2 is the in-store camera 42 provided at the exit of the first island facility 111, which is a one-corner corner. Further, the third row shows that the camera with the camera ID C3 is each camera 38 provided in the first unit of the XXXXXX model of the first island facility 111 having a one-yen corner. The fourth row shows that the camera with the camera ID C4 is each camera 38 provided in the second XXXXXX model of the first island facility 111 having a one-yen corner. Further, the fifth row shows that the camera with the camera ID C5 is the in-store camera 42 provided at the entrance of the second island facility 111 having a four-circle corner. The sixth row shows that the camera with the camera ID C6 is the in-store camera 42 provided at the exit of the second island facility 111 having a four-corner corner. Further, the seventh row shows that the camera with the camera ID C7 is each camera 38 provided in the third unit of YYYYY of the second island facility 111 having a four-circle corner.

  As described above, the information of the position is registered in association with the camera ID based on the information in the table allocation DB 272, so that the captured image is picked up by each camera 38, the entrance camera 41, or the in-store camera 42 at which position. It is possible to identify whether the image is a recorded image.

  In step S <b> 73, the control unit 271 controls the transmission / reception unit 273 to transmit the read information of the table allocation DB 272 to the biological information recognition apparatus 21.

  In step S63, the table allocation information management unit 298 of the biological information recognition apparatus 21 controls the transmission / reception unit 291 to receive and acquire information of the table allocation DB 272 transmitted by the process of step S73.

  In step S64, the table allocation information management unit 298 updates the table allocation DB 297 with the acquired information of the table allocation DB 272.

  Through the above processing, the biometric information recognition device 21 acquires the information in the table allocation DB 297 from the amusement shop management device 24 that originally manages the information each time it is activated, and the same information as the latest table allocation DB 272 is obtained. It becomes possible to do. It should be noted that the information in the table allocation DB 272 is not frequently updated, so there is no need to update it every time it is started. For example, once a week, once a month, or each camera 38 It may be set only when the arrangement of the entrance camera 41 and the in-store camera 42 is changed.

[Customer management database management processing]
Next, customer management DB management processing by the biological information recognition apparatus 21 will be described with reference to the flowcharts of FIGS.

  In step S91, the notification determination unit 292 controls the transmission / reception unit 291 to determine whether a person detection notification has been transmitted from each of the image processing units 39 or the image processing unit 40. In step S91, for example, when a person detection notification is transmitted from each of the image processing units 39 or the image processing unit 40 by the process of step S18 of FIG. 10 or the process of step S34 of FIG. Advances to step S92.

  In step S <b> 92, the notification determination unit 292 acquires information about the camera ID, the imaging time, and the face image included in the transmitted person detection notification, and supplies the information to the feature amount extraction unit 311 of the matching unit 293. To do.

  In step S93, the feature amount extraction unit 311 extracts the feature amount from the face image attached to the supplied person detection notification, and supplies the feature amount together with the person detection information to the similarity calculation unit 312.

  In step S94, the similarity calculation unit 312 controls the database management unit 296 to set an unprocessed face image as a processing target face image among the player's face images registered in the customer management DB 295. Read out.

  In step S <b> 95, the similarity calculation unit 312 calculates the similarity using the feature amount of the processing target face image and the feature amount supplied from the feature amount extraction unit 311.

  In step S96, the similarity calculation unit 312 stores the calculated similarity information in the similarity calculation result storage unit 313 in association with the processing target face image, that is, the person ID for identifying the processing target face image.

  In step S97, the similarity calculation unit 312 controls the database management unit 296 to determine whether or not there is an unprocessed face image among the player face images registered in the customer management DB 295. . If there is an unprocessed face image in step S97, the process returns to step S94. That is, the processes in steps S94 to S97 are repeated until the similarity with the face images of all the players registered in the customer management DB 295 is obtained. If it is determined in step S97 that there is no unprocessed face image and the similarity to the face images of all the players registered in the customer management DB 295 is obtained, the process proceeds to step S98.

  In step S <b> 98, the similarity calculation result totaling unit 314 obtains ranks for all the similarities stored in the similarity calculation result storage unit 313 according to the similarity value and supplies the ranks to the similarity determination unit 315. .

  In step S99, the similarity determination unit 315 determines whether or not the obtained highest similarity is higher than a predetermined threshold value and matches the player's face image registered in the customer management DB 295. . In step S99, for example, when it is determined that the highest similarity is not higher than the predetermined threshold value and does not match the face image of the player registered in the customer management DB 295, the process proceeds to step S100.

  In step S <b> 100, the similarity determination unit 315 supplies the face image supplied as person detection to the registration unit 301. For example, as illustrated in FIG. 16, the registration unit 301 issues a new person ID, registers the new person ID in the customer management DB 295, and supplies information on the registered new person ID to the similarity determination unit 315. Here, a person ID is newly set and only the face image is registered. In FIG. 16, a person ID field, a face image field, a time field, and an area movement history field are provided from the left.

  That is, in the uppermost stage, a player whose person ID is P1 is captured by the in-store camera 42 at the entrance of the first island facility 111 at 10:00 on October 1, 2010, and enters the first island facility. It is shown. In the second row, the player with the person ID P1 is captured by the in-store camera 42 at the exit of the first island facility 111 at 10:06 on October 1, 2010, and exits from the first island facility 111. It is shown that Further, in the third row, the player with the person ID P1 is captured by the in-store camera 42 at the entrance of the second island facility 111 at 10:30 on October 1, 2010 and enters the second island facility 111. It is shown that In the fourth row, the player with the person ID P1 is captured by each camera 38 of the gaming table 36 with the unit number 001 at 10:50 on October 1, 2010, and the unit number is 001. It is shown that the game is started on the game table 36. In the fifth row, the player with the person ID P1 is not picked up by each camera 38 of the game table 36 with the machine number 001 at 11:55 on October 1, 2010, and the machine number is 001. It is shown that the game has been completed on the game table 36.

  In the sixth row, the player with the person ID P2 is picked up by each camera 38 of the game table 36 with the table number 002 at 10:55 on October 1, 2010, and the player number is 002. It is shown that the game is started on the game table 36.

  Further, in the seventh row, the player with the person ID P3 is picked up by each camera 38 of the gaming machine 36 with the machine number 003 at 11:00 on October 1, 2010, and the gaming machine 36 with the machine number 003. It is shown that the game has started.

  In the eighth row, the player with the person ID P4 is captured by the respective cameras 38 of the gaming table 36 having the unit number 004 at 12:00 on October 1, 2010, and the gaming table 36 having the unit number 004 is obtained. It is shown that the game has started.

  In step S99, when the highest similarity exceeds a predetermined threshold, the process of step S100 is skipped. That is, in this case, since registration has already been performed in the customer management DB 295, registration processing is skipped.

  In step S101, the similarity determination unit 315 determines that the player of the face image to be processed is the player of the face image with the person ID having the highest similarity, or a face image with a new person ID set. The DB registration update unit 294 is notified that the player is a player.

  In step S102 (FIG. 15), the DB registration / updating unit 294 accesses the table allocation DB 297 and identifies the corresponding position based on the camera ID included in the person detection.

  In step S <b> 103, the game start management unit 294 c determines whether the camera that captures the face image included in the person detection specified from the camera ID is any one camera 38 of the game table 36.

  In step S103, when the camera that has captured the face image included in the person detection identified from the camera ID is any one of the cameras 38 in the game table 36, the game table 36 indicates that the face image has been captured. Assuming that the game has started, the process proceeds to step S104.

  In step S104, the game start management unit 294c registers, in the customer management DB 295, information including time information, a game machine number, and a game start in association with the person ID included in the person detection.

  In step S103, when the position is not the gaming table 36, the process of step S104 is skipped.

  In step S105, the corner entrance management unit 294a determines whether or not the camera that captures the face image included in the person detection specified by the camera ID is the entrance of a predetermined corner specified by any of the island facilities 111. Determine.

  In step S105, when the camera that captures the face image included in the person detection specified from the camera ID is the in-store camera 42 that captures the entrance of a predetermined corner made of any of the island facilities 111, the process is as follows. The process proceeds to S106.

  In step S106, the corner entrance management unit 294a, for example, as shown in the uppermost row of FIG. 16, the corner entrance management unit 294a associates the time information with a person ID included in the new person detection, and a predetermined information. Information including entering the corner and entering is registered in the customer management DB 295.

  In step S105, if the camera that captures the face image included in the person detection specified from the camera ID is not the in-store camera 42 that captures the entrance of a predetermined corner made of any of the island facilities 111, step S106. Is skipped.

  In step S107, the corner exit management unit 294b determines whether the camera that captures the face image included in the person detection specified by the camera ID is an exit of a predetermined corner specified by any of the island facilities 111. Determine.

  In step S107, when the camera that captured the face image included in the new person detection specified by the camera ID is an exit of a predetermined corner specified by any of the island facilities 111, the process proceeds to step S108. .

  In step S108, the potential player determination unit 294e causes the player with the person ID included in the person detection to play at the corner of the camera ID that is the exit of the predetermined corner specified by any of the island facilities 111. It is determined whether or not. In step S108, when a game is played in the corner, the process proceeds to step S112.

  If it is determined in step S108 that no game is played, the process proceeds to step S109.

  In step S109, the potential player determination unit 294e controls the stay time calculation unit 294f to access the customer management DB 295, and calculates the stay time from the difference between the entrance time to the corner and the exit time. . Then, the potential player determination unit 294e determines whether or not the calculated stay time is longer than a predetermined time. Here, the predetermined time is, for example, the time required for a normal person to pass by walking the corner. In other words, if the player specified by the person ID is only to go to another corner to go to another corner, the player will not stay in that corner for more than the time required for passage. Therefore, it is determined whether or not it has just passed. In step S109, for example, if it is a predetermined time or more, the process proceeds to step S110.

  In step S110, the potential player determination unit 294e indicates that the player identified by the person ID is interested in the corner game table 36, but the game table 36 that the player wants to play is not empty. Consider a potential player who has been in a long stay. Therefore, in step S111, the attention level DB management unit 294g accesses the customer management DB 295, and among the gaming tables 36 existing in the corresponding corner, the gaming table 36 that is currently playing is regarded as the attention table. That is, the attention level DB management unit 294g has a game table that has game start time information but no game end time information from the area movement history column of the customer management DB 295. 36 is regarded as a game table 36 that is currently being played, that is, an attention table. Then, the attention level DB management unit 294g accesses the attention level DB 302, and uses the point and number information corresponding to the staying time of the player regarded as a potential player as a gaming table regarded as the attention platform of the corresponding corner. The game table number identifying 36 is added to the information on the degree of attention and the number of players.

  In other words, if a player stays in the same corner for a longer time than the predetermined time without playing the corner where the game machine is provided, the reason for staying in that corner was that he wanted to play the game. Therefore, it is considered that the game stand 36 of which the player is interested is not vacant and the game cannot be performed, and the corresponding player is regarded as a potential player. Then, the game stand existing in the corner where the potential player has passed is set as the watch stand, and the points corresponding to the staying time are accumulated in the watch degree DB 302 as the watch degree. The attention level DB 302 is, for example, as shown in FIG. The attention level 302 in FIG. 17 is provided with a date column, a stand number column, an attention level column, and a number of people column from the left. In FIG. 17, as of January 1, 2011, in the gaming machine 36 with the machine number 001, the attention degree is 154, and the number of potential players is 51. On the same day, in the gaming machine 36 with the machine number 002, the degree of attention is 841 and the number of potential players is 180. Further, on the same day, in the gaming machine 36 having the machine numbers 003 and 004, the attention degrees are 256 and 372, respectively, and the number of potential players is 39 and 119, respectively. Here, when the staying time is X minutes, the attention level may be obtained by cumulatively adding X itself, or by cumulatively adding a point X × A (A is a coefficient) multiplied by a coefficient A It may be. That is, since the degree of attention is digitized by the degree of attention added in proportion to the staying time, it can be used as an index of the ability to attract customers of the game stand 36 that does not appear in the operation rate. .

  In step S112, the corner exit management unit 294b exits from the time information and a predetermined corner in association with the person ID included in the person detection, for example, as shown in the second row of FIG. Is registered in the customer management DB 295, and the process returns to step S91 (FIG. 14).

  In step S107, if it is not a predetermined corner exit, the processing in steps S108 to S111 is skipped.

  On the other hand, if it is not person detection in step S91 (FIG. 14), the process proceeds to step S113.

  In step S113, the DB registration update unit 294 determines whether the absence detection has been notified. In step S113, for example, when the absence detection is notified by the process of step S20 of FIG. 10, the process proceeds to step S114.

  In step S114, the DB registration update unit 294 accesses the table allocation DB 297 and identifies the corresponding position based on the camera ID included in the new person detection.

  In step S115, the game end management unit 294d registers, in the customer management DB 295, information including time information, a game machine number, and a game end in association with the person ID included in the absence detection. That is, when the absence detection is performed, the face image cannot be acquired and the player does not exist, so it is considered that the player has left.

  In step S113, if the absence is not detected, the process returns to step S91.

  With the above processing, the customer management DB 295 as shown in FIG. 16 and the attention level DB 302 as shown in FIG. 17 are sequentially accumulated according to the latest information. It is possible to accumulatively register information indicating which corner has entered and exited, which game table 36 has been played from when, and the attention level by potential players on each game table 36.

[Attention level display processing]
Next, attention level display processing in the game shop management device 24 will be described with reference to the flowchart of FIG.

  In step S161, the attention level display control unit 299 determines whether or not the display of the attention level of the gaming table is requested in the corner unit or the game model unit that identifies the corner by operating the operation unit 300. The same processing is repeated until requested. In step S161, for example, when display of the attention level is requested, the process proceeds to step S162.

  In step S <b> 162, the attention level display control unit 299 displays an image requesting input of information specifying the corner or the model of the gaming machine 36 specifying the corner on the display unit 23.

  In step S163, the attention level display control unit 299 determines whether there is input of information that specifies a corner or a model of the gaming machine 36 that specifies the corner, and repeats the same processing until it is input. In step S163, for example, when the operation unit 300 is operated to input information on a corner or the type of the gaming machine 36 that identifies the corner, the process proceeds to step S164.

  In step S164, the attention level display control unit 299 identifies the gaming machine 36 belonging to the specified corner based on the input corner or information on the model of the gaming machine 36 that identifies the corner.

  In step S165, the attention level display control unit 299 accesses the attention level DB 302, and of the attention level and the number of potential players, the attention level of the gaming table 36 belonging to the identified corner and the potential player's number. Extract information about the number of people.

  In step S166, the degree-of-attention display control unit 299 controls the operation rate calculation unit 299a to use the game start time and game end time of the game table 36 belonging to the specified corner, to the designated corner. The operating rate of all the game machines 36 to which it belongs is calculated.

  In step S167, the attention level display control unit 299 displays the read attention level, the number of potential players, and the calculated operation rate information on the display unit 23.

  With the above processing, the attention level for each gaming table, the number of potential players, and the information on the operating rate are displayed. Therefore, the operating rate and the operating rate that are information of the gaming table 36 actually played are displayed. Since it is possible to display and compare the attention level that does not appear at the same time, it is possible to appropriately select a replacement model of the game table 36. That is, for example, if the occupancy rate is slightly lower and the model has a high degree of attention, it is considered that the game store has enough power to attract customers, even if the profits from games are not sufficient. Since there is a possibility that profits can be obtained with other models, it is possible to determine that such models should not be replaced. On the other hand, if the occupancy rate is moderate, but it is a model with low attention, a player who has a popular model in the vicinity and cannot play the popular model is not interested, but the game he wants to play Since it is not possible to play on the table, there is a possibility that the game is only being played, so it can be determined that the model is selected as a replacement target model.

  In addition, in the above, the example which calculates | requires an attention degree based on the stay time of a potential player in the corner where the game machine was provided in the game store has been described, but for example, the game machine installed in the game store is If we consider it as a plurality of spatially distributed resources, the attention level can be defined as follows. That is, for each resource, the retention time of a predetermined resource use desireer (corresponding to a potential player) staying in the vicinity of the predetermined resource being used by another resource user without using the predetermined resource Cumulative accumulation is possible, and the accumulated accumulation time can be considered as the attention level. Here, staying in the vicinity of a predetermined resource being used by another resource user means, for example, that the resource is not used and, for example, a survey is performed more than a predetermined frequency or a cost higher than a predetermined cost is applied. It may be considered that the act of investigating is staying in the vicinity area. That is, the attention level is expressed by integrating the staying time in which a potential player waits for a state where a player can play in the vicinity of the game stand. In this case, the attention level indicates the degree of interest in the game table. Therefore, even when the target corresponding to the gaming table is regarded as a plurality of spatially distributed resources described above, the degree of attention is the target corresponding to the gaming table being played by other players, that is, Any information may be used as long as it indicates the degree of interest of the user with respect to the resource being used by another resource user. As long as the degree of attention is obtained as an indication of the degree of interest of the user with respect to the target as described above, the target may be a resource other than the above-described resources or a game table.

  By the way, the series of processes described above can be executed by hardware, but can also be executed by software. When a series of processing is executed by software, a program constituting the software may execute various functions by installing a computer incorporated in dedicated hardware or various programs. For example, it is installed from a recording medium in a general-purpose personal computer or the like.

  FIG. 19 shows a configuration example of a general-purpose personal computer. This personal computer incorporates a CPU (Central Processing Unit) 1001. An input / output interface 1005 is connected to the CPU 1001 via the bus 1004. A ROM (Read Only Memory) 1002 and a RAM (Random Access Memory) 1003 are connected to the bus 1004.

  The input / output interface 1005 includes an input unit 1006 including an input device such as a keyboard and a mouse for a user to input an operation command, an output unit 1007 for outputting a processing operation screen and an image of a processing result to a display device, a program and various data. A storage unit 1008 including a hard disk drive for storing data, a LAN (Local Area Network) adapter, and the like, and a communication unit 1009 for performing communication processing via a network represented by the Internet are connected. Also, a magnetic disk (including a flexible disk), an optical disk (including a CD-ROM (Compact Disc-Read Only Memory), a DVD (Digital Versatile Disc)), a magneto-optical disk (including an MD (Mini Disc)), or a semiconductor A drive 1010 for reading / writing data from / to a removable medium 1011 such as a memory is connected.

  The CPU 1001 is read from a program stored in the ROM 1002 or a removable medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, installed in the storage unit 1008, and loaded from the storage unit 1008 to the RAM 1003. Various processes are executed according to the program. The RAM 1003 also appropriately stores data necessary for the CPU 1001 to execute various processes.

  In this specification, the step of describing the program recorded on the recording medium is not limited to the processing performed in time series in the order described, but of course, it is not necessarily performed in time series. Or the process performed separately is included.

  Further, in this specification, the system represents the entire apparatus constituted by a plurality of apparatuses.

1, 1-1 to 1-n amusement store 2 third-party amusement store management center 3 third-party amusement store management database 4 third-party amusement store management bus 5 public communication line network 21 biometric information recognition device 22 biometric information database 24 Amusement store management device 26 Amusement table management database 27 Medium lending management device 29 Medium lending management database 30 Amusement store management information bus 31 Biological information bus 33 Settlement vending machine 34 Lending machine 35 Counter 36, 36-1 to 36-m 37,37-1 thru | or 37-m Game stand peripheral terminal 38,38-1 thru | or 38-m each stand camera 39,39-1 thru | or 39-m each stand image processing unit 40,40-1 thru | or 40- (p + q) Image processing unit 41, 41-1 to 41-p Entrance camera 42, 42-1 to 42-q In-store camera

Claims (6)

A game table imaging unit that captures an image of a player who plays on the game table for each game table installed in a game store , and a corner that has a plurality of the game tables, or a game that enters or leaves in units of island facilities A collation unit that collates a player imaged by a corner imaging unit that images a person with a registrant,
An admission management unit that manages the admission time of each corner for each player collated by the collation unit;
An exit management unit that manages an exit time for each corner for each player verified by the verification unit;
A game start management unit for managing the game start time for each gaming table for each player collated by the collation unit, depending on the presence or absence of the player imaged by the gaming table imaging unit;
Based on the entrance time and the exit time, a stay time calculation unit that calculates a stay time of the corner for each player collated by the collation unit;
Based on the start time of the game managed by the game start management unit of the player verified by the verification unit whose entrance is managed by the entrance management unit, the player is installed in the corner. A potential player determination unit that determines whether or not the player is a potential player who has not been able to play a game but wished to play the type of the game machine,
Based on the information on the entry time and the exit time of the player determined as a potential player by the potential player determination unit for the predetermined model of the game machine installed in the game store, the predetermined game machine and the attention level calculation unit for calculating the gaming table of attention as a model only contains,
The potential player determination unit, when the stay time of the player in the corner is longer than a predetermined time, and when the game start time is not registered within the stay time of the player in the corner, Determine a player as a potential player,
The degree-of-attention calculation unit obtains a predetermined model of a game machine installed in the game store from information on the entrance time and the exit time of the player determined as a potential player by the potential player determination unit. An information processing apparatus that calculates a sum of points obtained by multiplying a given stay time by a coefficient as a degree of attention . The degree-of-attention calculation unit is information on the entry time and the exit time of a player determined as a potential player by the potential player determination unit for a predetermined model of a game machine installed in the game store. And the entrance time calculated by the stay time calculation unit for the gaming machine operating according to the gaming machine operating information based on the gaming machine operating information indicating whether or not the gaming machine is operating. The information processing apparatus according to claim 1 , wherein a sum of points obtained by multiplying a stay time obtained from the information of the departure time by a coefficient is calculated as a degree of attention. A display unit that displays the degree of attention of the gaming table as the predetermined model calculated by the attention level calculation unit and the number of staying players in units of the predetermined model or in units of predetermined corners. The information processing apparatus according to claim 1 or 2 . The information processing apparatus according to any one of claims 1 to 3, further comprising the game table imaging unit and the corner imaging unit. Yu TECHNICAL stand imaging unit, and a gaming table imaging step for imaging a player for the game in the gaming table for each installed gaming stand in game arcade,
Co over Na imaging unit, and a corner imaging step of the amusement machine has corners provided in a plurality, or to image the player to entrance or exit island equipment units,
A matching step collating unit, to match the registrant the processing of the gaming table imaging step, and the player captured by the process of the corner imaging step,
Input field management unit, and the admission management step of managing the admission time for each of the corner for each player who is verified by the processing of the verification step,
Withdrawal lot management unit, and exit management step of managing the exit time for each of the corner for each player who is verified by the processing of the verification step,
A stay time calculating unit that calculates a stay time of the corner for each player collated by the collating unit based on the entrance time and the exit time;
Yu TECHNICAL start management unit, the presence or absence of the player captured by the process of the amusement machine imaging step, game start managing a game start time of each of the amusement machines each player who is verified by the processing of the matching step Administrative steps;
Latent standing player determination unit, admission by the process of the entrance management step is managed, the player's that have been collated by the process of matching step, the start time of the game, which is managed by the processing of the game start managing step A potential player determination step of determining whether or not the player is a potential player who wanted to play a model of a gaming table installed in the corner but could not play a game; and ,
Attention degree calculation part, for a given model of the amusement machine installed in the game arcade, the potential player in the process of the determination step of the determined player as potential player, the entry time and the exit time based on the information, it sees contains an attention degree calculation step of calculating a game machine of attention as a predetermined model,
In the potential player determination step, when the stay time of the player in the corner is longer than a predetermined time and a game start time is not registered within the stay time of the player in the corner, Determine a player as a potential player,
Information on the entry time and the exit time of the player determined as a potential player in the potential player determination step for a predetermined model of the game machine installed in the game store in the attention level calculation step. An information processing method for calculating a sum of points obtained by multiplying a required stay time by a coefficient as a degree of attention . A game table imaging unit that captures an image of a player who plays on the game table for each game table installed in a game store, and a corner that has a plurality of the game tables, or a game that enters or leaves in units of island facilities A collation unit that collates a player imaged by a corner imaging unit that images a person with a registrant,
An admission management unit that manages the admission time of each corner for each player collated by the collation unit;
An exit management unit that manages an exit time for each corner for each player verified by the verification unit;
A game start management unit for managing the game start time for each gaming table for each player collated by the collation unit, depending on the presence or absence of the player imaged by the gaming table imaging unit;
Based on the entrance time and the exit time, a stay time calculation unit that calculates a stay time of the corner for each player collated by the collation unit;
Based on the start time of the game managed by the game start management unit of the player verified by the verification unit whose entrance is managed by the entrance management unit, the player is installed in the corner. A potential player determination unit that determines whether or not the player is a potential player who has not been able to play a game but wished to play the type of the game machine,
Based on the information on the entry time and the exit time of the player determined as a potential player by the potential player determination unit for the predetermined model of the game machine installed in the game store, the predetermined game machine cause the computer to function as the attention degree calculating unit that calculates a gaming table of attention as a model,
The potential player determination unit, when the stay time of the player in the corner is longer than a predetermined time, and when the game start time is not registered within the stay time of the player in the corner, Determine a player as a potential player,
The degree-of-attention calculation unit obtains a predetermined model of a game machine installed in the game store from information on the entrance time and the exit time of the player determined as a potential player by the potential player determination unit. A program that calculates the sum of points obtained by multiplying a given stay time by a coefficient as the degree of attention.

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