RELATIONSHIP ANALYSIS METHOD, RELATIONSHIP ANALYSIS PROGRAM, AND RELATIONSHIP ANALYSIS APPARATUS

• US 20100262281A1
• Filed: 02/26/2010
• Published: 10/14/2010
• Est. Priority Date: 03/03/2009
• Status: Abandoned Application

• Current Assignee: Hitachi, Ltd., Japan Tobacco Inc.
• Original Assignee: Hitachi, Ltd., Japan Tobacco Inc.
• Inventors: SUZUKI, Yasuhiro, Maki, Hideyuki, Yuyama, Shigeo, Sayama, Chiharu, Watanabe, Hiroshi
• Application Number:
  US12/713,455
• Publication Number:
  US 20100262281A1
• Time in Patent Office: Days
• US Class Current: 700/236
• CPC Class Codes: G06F 3/013 Eye tracking input arrangements G06F3/015 takes precedence
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

To obtain a high accuracy marketing analysis result, while reducing an effect of a low accuracy visual line detection processing, a storage unit of a visual line analysis apparatus stores therein, for each commodity, a basic zone including the commodity and an extended zone at least a portion of which, is overlapped with the basic zone. The basic zone and the extended zone are stored in association with each other. An attention degree calculation part of the visual line analysis apparatus compares positional information on a visual line data detected by the visual line detection part and positional information on each zone defined in a zone definition data to calculate an attention degree for each zone, aggregates attention degrees in each zone for each commodity corresponding to the each zone, calculates an attention degree data for each commodity, and stores the calculated data in the storage unit.

Claims

1. A relationship analysis method, performed by a relationship analysis apparatus that analyzes a relationship between a visual line data on a visual line of a user to a commodity and an action data on an action of the user of purchasing the commodity,

wherein the relationship analysis apparatus comprising a storage part, a visual line detection part, an attention degree calculation part, an action processing unit, and an analysis processing unit,

wherein the storage part stores therein a zone definition data for identifying a commodity to which a visual line is directed, based on positional information on each commodity arranged in a commodity display part;

the zone definition data includes, for each commodity, a basic zone including a commodity and an extended zone at least a portion of which is overlapped with the basic zone; and

the storage part stores therein the basic zone and the extended zone in association with each other,

wherein the visual line detection part detects the visual line data to each commodity arranged in the commodity display part,

wherein the attention degree calculation part compares, for each zone, positional information on the visual line data detected by the visual line detection part end positional information on each zone defined in a zone definition data, calculates an attention degree for each zone based on the compared result, aggregates attention degrees in each zone for each commodity corresponding to the each zone to calculate an attention degree data for each commodity, and stores the calculated data in the storage unit,

wherein the action processing unit receives an input of the action data with respect to each commodity arranged in the commodity display part and stores the received data in the storage unit, and

wherein the analysis processing unit joins the attention degree data for each commodity and the action data for each commodity stored in the storage unit, calculates a correlative relationship between the both data, and outputs the calculated result.

2. The relationship analysis method according to claim 1,

wherein the visual line detection part detects the visual line data by detecting eye parts from a user'"'"'s facial image taken by a camera set up in the commodity display part.

3. The relationship analysis method according to claim 2,

wherein, if the analysis processing unit performs a join of the attention degree data and the action data, the analysis processing unit joins the attention degree data and the action data having the date and time same as the attention degree data.

4. The relationship analysis method according to claim 2,

wherein, if the analysis processing unit performs a join of the attention degree data and the action data, the analysis processing unit joins the attention degree data having a given date and time and the action data having the given date and time with a prescribed margin.

5. The relationship analysis method according to claim 2,

wherein the relationship analysis apparatus is configured as an automatic vending machine having a means of purchasing each commodity arranged in the commodity display part, and

wherein the action processing unit receives an input of a purchase history data of each commodity as the action data with respect to each commodity.

6. The relationship analysis method according to claim 5,

wherein, if the analysis processing unit performs a join of the attention degree data and the action data, the analysis processing unit joins the attention degree data of a given user who is in front of the automatic vending machine at a given time and the action data of the given user.

7. The relationship analysis method according to claim 6,

wherein the relationship analysis apparatus stores at least one of an external zone including a basic zone for a given commodity and an internal zone included in the basic zone for the given commodity, both as the extended zones in the zone definition data, in the storage unit.

8. The relationship analysis method according to claim 7,

wherein the relationship analysis apparatus associates a weight with each of a plurality of zones which is associated with a given commodity in the zone definition data and stores the associated weight and zone in the storage unit, and

wherein, if the attention degree calculation part aggregates attention degrees in each zone for each commodity to calculate an attention degree data for each commodity, the attention degree calculation part calculates the attention degree data for each commodity using a weighting processing in which the attention degree of each zone is multiplied by the weight stored in the storage unit.

9. A relationship analysis program that causes the relationship analysis apparatus as a computer to execute the relationship analysis method according to claim 1.

10. A relationship analysis program that causes the relationship analysis apparatus as a computer to execute the relationship analysis method according to claim 2.

11. A relationship analysis program that causes the relationship analysis apparatus as a computer to execute the relationship analysis method according to claim 3.

12. A relationship analysis program that causes the relationship analysis apparatus as a computer to execute the relationship analysis method according to claim 4.

13. A relationship analysis program that causes the relationship analysis apparatus as a computer to execute the relationship analysis method according to claim 5.

14. A relationship analysis program that causes the relationship analysis apparatus as a computer to execute the relationship analysis method according to claim 6.

15. A relationship analysis program that causes the relationship analysis apparatus as a computer to execute the relationship analysis method according to claim 7.

16. A relationship analysis program that causes the relationship analysis apparatus as a computer to execute the relationship analysis method according to claim 8.

17. A relationship analysis apparatus that analyzes a relationship between a visual line data on a visual line of a user to a commodity and an action data on an action of the user of purchasing the commodity,

wherein the relationship analysis apparatus comprising a storage part, a visual line detection part, an attention degree calculation part, an action processing unit, and an analysis processing unit,

wherein the storage part stores therein a zone definition data for identifying a commodity to which a visual line is directed, based on positional information on each commodity arranged in a commodity display part;

the zone definition data includes, for each commodity, a basic zone including a commodity and an extended zone at least a portion of which is overlapped with the basic zone; and

the storage part stores therein the basic zone and the extended zone in association with each other,

wherein the visual line detection part detects the visual line data to each commodity arranged in the commodity display part,

wherein the attention degree calculation part compares, for each zone, positional information on the visual line data detected by the visual line detection part and positional information on each zone defined in a zone definition data, calculates an attention degree for each zone based on the compared result, aggregates attention degrees in each zone for each commodity corresponding to the each zone to calculate an attention degree data for each commodity, and stores the calculated data in the storage unit,

wherein the action processing unit receives an input of the action data with respect to each commodity arranged in the commodity display part and stores the received data in the storage unit, and

wherein the analysis processing unit joins the attention degree data for each commodity and the action data for each commodity stored in the storage unit, calculates a correlative relationship between the both data, and outputs the calculated result.