Location identification support system and location identification support method

Abstract

To identify a position from information of a landscape which a person views.SOLUTION: A position identification support system generates data to identify a position. A storage device comprises: a reception section for storing visible spot character information which records character information included in a landscape and receiving an input from a user; a search key generation section for identifying a search word to search for the visible spot character information; and a screen generation section for outputting screen data to display the position. The reception section receives an input of the character information included in the landscape. The search key generation section identifies the search word to search for the visible spot character information from the received character information. The reception section searches for the visible spot character information with the use of the identified search word, so as to acquire information to narrow down a position from the received character information. The screen generation section outputs screen data to display the information to narrow down the position from the character information.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a position identification support system that generates information for identifying a position from the expression of a landscape.

Background Art

[0002] Today, by using GNSS (Global Navigation Satellite System), one can know one's own position. However, in urban areas (for example, between structural buildings), it may not be possible to receive radio waves from the required number of artificial satellites for positioning calculations, and the position may not be identified by GNSS. For this reason, there is a need to identify a position using information on the landscape visible to the user. For example, even when the informant is not familiar with the local geography, such as when away or traveling, and does not know the address or the name of the landmark, it is desired to accurately identify the position in the event of a traffic accident or an emergency.

[0003] As the background art in this technical field, there is the following prior art. Patent Document 1 (Japanese Patent Application Laid-Open No. 2001-133283) discloses a navigation device including voice recognition means for inputting voice and outputting various instruction signals, information search means for searching information data from an information recording medium based on a search instruction signal input from the voice recognition means, and voice output means for outputting the search result as voice. The information search means includes a search genre discrimination section for discriminating a signal indicating a search genre from the input search instruction signal, a search direction discrimination section for discriminating a search instruction signal indicating a search direction, a search range setting section for setting a search range, and a search section for searching the information data according to the discriminated search genre, search direction, and search range.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Traditionally, location information (address, landmark names, GPS positioning information, etc.) is entered into the system, and the corresponding location is searched using a map information system. However, if the caller or dispatcher is not familiar with the geography of the area (for example, they do not know the address or the name of a landmark), searching using landmarks becomes difficult. In this case, information about the scenery visible to the user (for example, "I can see a building with a red pointed roof" or "It's near a shop with a blue sign") is effective in identifying the location, but such information is not registered in the map information system.

[0006] Furthermore, even if the name of a landmark is known, if information indicating whether that landmark is "visible" can be used, the location can be narrowed down even further.

[0007] Furthermore, the aforementioned background technology allows navigation devices to search map data using words indicating direction, such as "left" and "right," spoken by the speaker. However, this method provides variations in how destinations are expressed when the speaker's location is known in advance, and it is not a technology that can be used when the reference location is unknown. In addition, despite the presence of numerous characters in urban areas, the use of these characters to pinpoint a location has not been considered.

[0008] Therefore, there is a need for a location identification support system that can determine a location from information about the landscape as seen by a person. Furthermore, there is a need to improve location accuracy by identifying locations not only from information prepared as three-dimensional maps such as building shapes, but also from the text that the user is seeing.

[0009] The present invention aims to realize a location identification support system that identifies a location from information about the scenery seen by a person. [Means for solving the problem]

[0010] A representative example of the invention disclosed in this application is as follows: A location identification support system that generates data for identifying a location, comprising: a computing device that performs predetermined processing; a storage device accessible by the computing device, wherein the storage device stores visible location character information, which contains character information included in the landscape; a reception unit for receiving input from a user by the computing device; a search key generation unit for the computing device to identify a search term for searching the visible location character information; and a screen generation unit for the computing device to output screen data for displaying the location, wherein the reception unit receives input of character information included in the landscape; the search key generation unit identifies a search term for searching the visible location character information from the received character information; and the reception unit searches the visible location character information using the identified search term. Then, using the reliability and contribution of the received character information, a score is calculated for the visible location character information, and the location information selected using the score is used as information to narrow down the location. The screen generation unit acquires the information and then, The aforementioned position It is characterized by outputting screen data for displaying information to narrow down the results. [Effects of the Invention]

[0011] According to one aspect of the present invention, a location can be determined from information about the landscape seen by a person. Problems, configurations, and effects other than those described above will be clarified by the following description of the embodiments. [Brief explanation of the drawing]

[0012] [Figure 1] This figure shows the solution concept using the location identification support system of this embodiment. [Figure 2] This figure shows the solution concept using the location identification support system of this embodiment. [Figure 3] This block diagram shows the logical configuration of the location identification support system in this embodiment. [Figure 4] This is a block diagram showing the physical configuration of the location identification support server in this embodiment. [Figure 5] This figure shows an example of the structure of the glossary in this embodiment. [Figure 6] This figure shows an example of the configuration of the 3D city model in this embodiment. [Figure 7A] This is a diagram showing a configuration example of visible location information (visible object) in this embodiment. [Figure 7B] This is a diagram showing a configuration example of visible location information (character information) in this embodiment. [Figure 8] This is a flowchart of the process executed by the location identification support server in this embodiment. [Figure 9] This is a sequence diagram of the process executed by the location identification support server in this embodiment. [Figure 10] This is a diagram showing an example of a search result screen displayed on the user terminal in this embodiment. [Figure 11] This is a diagram showing an example of a search result screen displayed on the user terminal in this embodiment. [Figure 12] This is a diagram showing an example of a search result screen displayed on the user terminal in this embodiment.

Embodiments for Carrying Out the Invention

[0013] First, an overview of the embodiments of the present invention will be described. The location identification support system of this embodiment searches for objects from a 3D city model representing landmarks using information on the attributes (shape, color, etc.) of landmarks (such as "a pointed roof can be seen", "near a store with a red sign", etc.). Then, areas corresponding to recognition types such as "visible" and "near" of the searched objects and the visible range of character information are superimposed and displayed on the map. When multiple keywords are input, the accuracy of location identification is improved by superimposing and displaying multiple areas on the map.

[0014] FIG. 1 and FIG. 2 are diagrams showing the solution concept by the location identification support system of this embodiment.

[0015] FIG. 1 shows a solution for providing a location identification support service to an individual. In the solution shown in FIG. 1, by inputting information about the scenery seen by the user (e.g., "near a building with a pointed roof", "a red iron tower can be seen") and character information (e.g., "East-West Mart") into the user terminal 20 connected to the location identification support server 10, the user's location is displayed on the map. For example, when browsing a map on the Internet and the user's location information cannot be obtained by GNSS, using the location identification support service of this embodiment, the user's location can be displayed on the map, and the location can be identified even when the user is unfamiliar with the local geography of the scene.

[0016] FIG. 2 shows a solution for providing a location identification support service to a person or an organization that needs to identify the location of others. In the solution shown in FIG. 2, by inputting information about the scenery seen by others (e.g., "near a building with a pointed roof", "a red iron tower can be seen") and character information (e.g., "East-West Mart") heard by the user into the user terminal 20 connected to the location identification support server 10, the location of the other person is displayed on the map. In the command rooms of the fire department and the police that receive emergency reports, the location of the reporter is narrowed down by relaying the address and the name of the landmark from the reporter to the commander. However, when the reporter is unfamiliar with the local geography of the scene, the commander listens to the information about the landmark visible to the reporter to narrow down the location. However, such a method depends on the on-site knowledge and skills of the communication commander. Therefore, with the location identification support service of this embodiment, the location of the reporter can be displayed on the map, and the location of the incident can be quickly identified for an emergency report.

[0017] FIG. 3 is a block diagram showing the logical configuration of the location identification support system of this embodiment.

[0018] The location identification support system of this embodiment is composed of a location identification support server 10 and a user terminal 20, and the location identification support server 10 and the user terminal 20 are connected via a network.

[0019] The location identification support server 10 includes a search request receiving unit 11, a search key generation unit 12, a target object search unit 13, a target area extraction unit 14, and a screen generation unit 19, and stores a term dictionary 15, a 3D city model 16, visible point information 17, and map information 18.

[0020] The search request receiving unit 11 receives the search request sent from the user terminal 20, controls the processing by each functional unit of the location identification support server 10, and returns the processing results from each functional unit to the terminal. The search key generation unit 12 generates a search query from the input content received by the search request receiving unit 11 by referring to the term dictionary 15. The target object search unit 13 searches for the object for which a search has been requested by referring to the 3D city model 16. The target area extraction unit 14 outputs information on locations where the object can be seen by referring to the visible point information 17. The screen generation unit 19 generates display data to be displayed on the user terminal 20.

[0021] The glossary 15 is a database used to classify the text entered for location identification and to identify search methods; its details are explained with reference to Figure 5. The 3D city model 16 is a database in which information on objects (e.g., buildings, roads, etc.) is recorded; its details are explained with reference to Figure 6. Visible point information 17 includes visible point information (visible objects) 17A and visible point information (text information) 17B. Visible point information (visible objects) 17A is data on objects visible at regular intervals of mesh, and visible point information (text information) 17B is information on text present in the space targeted by the 3D city model. Details of visible point information (visible objects) 17A and visible point information (text information) 17B are explained with reference to Figures 7A and 7B, respectively. Map information 18 is map information of the area that supports location identification.

[0022] The user terminal 20 is comprised of a computer having a processor (CPU), memory, auxiliary storage device, communication interface, input interface, and output interface, and provides a search request input function 21 and a screen display function 22. For example, the search request input function 21 and the screen display function 22 may be provided by a web browser executed by the user terminal 20, or by a dedicated application program executed by the user terminal 20.

[0023] Figure 4 is a block diagram showing the physical configuration of the location identification support server 10 in this embodiment.

[0024] The location identification support server 10 is composed of a computer having a processor (CPU) 1, memory 2, auxiliary storage device 3, and communication interface 4. The location identification support server 10 may also have an input interface 5 and an output interface 6.

[0025] Processor 1 is an arithmetic unit that executes programs stored in memory 2. By executing various programs, Processor 1 enables the functions of each functional unit of the location identification support server 10 (for example, the search request reception unit 11, the search key generation unit 12, the target object search unit 13, the target area extraction unit 14, the screen generation unit 19, etc.). Note that some of the processing performed by Processor 1 by executing programs may be performed by other arithmetic units (for example, hardware such as ASICs and FPGAs).

[0026] Memory 2 includes ROM, a non-volatile memory element, and RAM, a volatile memory element. ROM stores immutable programs (e.g., BIOS). RAM is a high-speed, volatile memory element such as DRAM (Dynamic Random Access Memory), and temporarily stores programs executed by processor 1 and data used during program execution.

[0027] The auxiliary storage device 3 is a high-capacity, non-volatile storage device such as a magnetic storage device (HDD) or flash memory (SSD). The auxiliary storage device 3 also stores data used by the processor 1 when executing programs (for example, a glossary 15, a 3D city model 16, visible point information 17, map information 18, etc.) and the programs executed by the processor 1. In other words, the programs are read from the auxiliary storage device 3, loaded into memory 2, and executed by the processor 1 to realize the various functions of the location identification support server 10.

[0028] Communication interface 4 is a network interface device that controls communication with other devices (e.g., user terminal 20) according to a predetermined protocol.

[0029] Input interface 5 is an interface to which input devices such as a keyboard 7 and a mouse 8 are connected and to receive input from the operator. Output interface 6 is an interface to which output devices such as a display device 9 and a printer (not shown) are connected and to output the program execution results in a format that the operator can see.

[0030] The program executed by processor 1 is provided to location tracking support server 10 via removable media (such as CD-ROM or flash memory) or a network, and stored in non-volatile auxiliary storage device 3, which is a non-temporary storage medium. For this reason, location tracking support server 10 should have an interface for reading data from removable media.

[0031] The location identification support server 10 is a computer system that operates on a single physical computer or on multiple logically or physically configured computers, and may operate on a virtual computer built on multiple physical computer resources. For example, the search request receiving unit 11, the search key generation unit 12, the target object search unit 13, the target area extraction unit 14, and the screen generation unit 19 may each operate on separate physical or logical computers, or multiple units may be combined and operate on a single physical or logical computer.

[0032] Figure 5 shows an example of the structure of the term dictionary 15. The term dictionary 15 is used to classify the text entered for location identification and to identify the search method. The term dictionary 15 contains data on terms, types, derived expressions, and search methods. The type is the classification of the term and includes attribute names, keywords, character information, and recognition types. The attribute name indicates that the term is recorded in the 3D city model 16 as an attribute of an object (shape, color, etc.). The keyword indicates that the term is recorded in the 3D city model 16 as a keyword for an object. Keywords include the type, use, and characteristics of an object. Character information is character information contained in the landscape, which is information that has been converted into text that is visible to users or informants from a point on the map, and indicates that it is recorded in the visible point information (character information) 17B. The recognition type indicates that the method of specifying the target area is determined by the word. Derived expressions are used to replace the entry in the term field of the entry if the word entered for location identification is recorded in the derived expressions. The search method is information used by the target object search unit 13 to create a search query related to the term, and it records the search conditions for the object.

[0033] Figure 6 shows an example of the configuration of a 3D city model 16. The 3D city model 16 includes data for each object, such as name, keywords, text information, and attributes (shape, color, etc.). Each data is written in the format data name=value. The value is a word registered in the term dictionary 15. The 3D city model 16 is best configured to store information hierarchically using XML or similar.

[0034] Figure 7A shows an example of the configuration of Visible Point Information (Visible Objects) 17A. Visible Point Information (Visible Objects) 17A is data of objects visible to each mesh at regular intervals, and includes location ID, latitude, longitude, viewpoint height, and visible object data. Location ID is unique identification information for the representative point of the mesh divided at regular intervals. Latitude and longitude are the positions of the representative point (e.g., the center point) within the mesh. Viewpoint height is the viewpoint height during landscape simulation from the representative point of the mesh. Visible objects are identification information for objects within the range visible from the mesh, as determined by landscape simulation from the representative point of the mesh. By using Visible Point Information (Visible Objects) 17A, it is not necessary to perform a three-dimensional simulation each time a visible area is determined, thus reducing the amount of computation and allowing for rapid acquisition of the visible area.

[0035] Figure 7B shows an example of the configuration of Visible Point Information (Text Information) 17B. Visible Point Information (Text Information) 17B records text data of characters visible from a predetermined point in the 3D city model, which are characters contained in the landscape, and includes a point ID, latitude, longitude, viewpoint height, and time-series text information. The point ID is identification information of the viewpoint position from which the text information was observed. This viewpoint position is, for example, the shooting position of an image frame taken with a 360-degree camera from a vehicle traveling on the ground, and does not necessarily coincide with the representative point of the mesh recorded in Visible Point Information (Visible Object) 17A. If the representative point of the mesh recorded in Visible Point Information (Visible Object) 17A and the viewpoint position of Visible Point Information (Text Information) 17B are different, the point ID of Visible Point Information (Visible Object) 17A and the point ID of Visible Point Information (Text Information) 17B will be different. On the other hand, even if the representative point of the mesh recorded in the visible point information (visible object) 17A and the viewpoint position of the visible point information (text information) 17B are different, if the two points are within a predetermined range of proximity (for example, 1m), the two points may be treated as the same point, and the same identification information as the location ID of the visible point information (visible object) 17A may be assigned to the location ID of the visible point information (text information) 17B.

[0036] Latitude and longitude represent the viewpoint position (the position where the image frame was taken). Viewpoint height represents the height of the viewpoint (the height at which the image frame was taken).

[0037] Textual information is text extracted from image frames captured in the space targeted by the 3D city model. This textual information can be automatically extracted using image character recognition technology, or it can be manually entered and recorded by a person viewing the images. Furthermore, if textual information is recorded on objects within the 3D city model, it can be extracted by rendering at the viewpoint position.

[0038] Text in landscapes can change over time (e.g., seasonal advertisements) or remain unchanged for extended periods (e.g., shop signs, building nameplates, road signs). Therefore, it is advisable to extract and record text information from multiple image frames taken over time. When doing so, it is important to distinguish between cases where no text information is extracted (e.g., N / A) and cases where no text information was detected from the image results for that location (e.g., NULL).

[0039] The format for recording textual information can be as shown in the diagram, by providing a column for recording textual information in chronological order, or by recording links to the textual information at each point in time in the visible location information (textual information) 17B, and keeping the textual information itself as separate data.

[0040] Figure 8 is a flowchart of the processes performed by the location identification support server 10, and Figure 9 is a sequence diagram of the processes performed by the location identification support server 10.

[0041] First, the search request receiving unit 11 determines whether there is an "end" input (101). If the user has pressed the "end" button, this process is terminated. On the other hand, if the "end" button has not been pressed, the search request receiving unit 11 determines whether there is a "search" input (102). If the user has not pressed the "search" button, the process returns to step 101. On the other hand, if the "search" button is pressed, a search request is sent from the user terminal 20 to the location identification support server 10.

[0042] The search request receiving unit 11 then receives the search request sent from the user terminal 20 (103). For example, the user enters text (keywords, attribute names, recognition types, readable characters, etc.) of information about the scenery or characters that the person is seeing into the search term input field 1011 on the search results screen displayed on the user terminal 20. For attribute names, derived expressions registered in the term dictionary 15 are used. For recognition types, words that indicate the relationship between the user and the object in question, such as visible, nearby, or in the direction. Specifically, the user may enter the scenery as a sentence, such as "I can see a red transmission tower," or as a list of words, such as "transmission tower red visible." The user may enter text using a keyboard or touch panel, or text may be entered by voice recognition of the user's speech.

[0043] Alternatively, a list of predetermined keywords and attribute names may be displayed for the user to select from. Keywords should be those registered in the 3D city model 16, and attribute names should be those registered in the terminology dictionary 15.

[0044] Furthermore, once the current location is entered, a function to draw a region indicating the "direction," as described later, becomes available. The current location can be entered in several ways: by selecting a point on the map, by entering latitude and longitude, by entering an address, or by entering the location of a nearby structure (e.g., a road kilometer post or utility pole management number).

[0045] Next, the search key generation unit 12 performs morphological analysis on the text entered by the user as a search request and extracts key information (104). For example, if the user enters "I can see a red steel tower," the words "red," "steel tower," and "visible" are extracted.

[0046] Next, the search key generation unit 12 obtains the term and recognition type of the word from the term dictionary 15 and generates an object search query (105). For example, the user's input "I can see a red transmission tower" is tagged with red: attribute name, transmission tower: keyword, and visible: recognition type, and a search method corresponding to that word is obtained. Then, a search query is generated that searches using the words tagged with the keyword and the words tagged with the attribute name (keyword = transmission tower, RGB range of red). By referring to the term dictionary 15, variations in words entered as free words can be aggregated and the search method for the 3D city model 16 (the field for searching the 3D city model 16) can be determined.

[0047] Next, the target object search unit 13 searches the 3D city model 16 using the generated object search query and obtains a list of target objects that match the search criteria (106). For example, objects that include "transmission tower" as a keyword in the 3D city model 16 and are within the red RGB range (255:0:0 to 200:50:50) are extracted.

[0048] Subsequently, the search request receiving unit 11 starts processing each object in the acquired target object list (107) and extracts target areas for each recognition type.

[0049] If the recognition type "nearby" is extracted from the text entered by the user, the method of specifying the target area is determined to be "neighborhood," and a circle centered on the target area is obtained (109). The obtained circle may be a single circle (for example, a circle with a radius of 20m) or multiple circles (for example, concentric circles with radii of 10m, 50m, and 100m).

[0050] If the recognition type = "visible" is extracted from the text entered by the user, the method of specifying the target area is determined to be "visible," and the target area extraction unit 14 obtains the visible area of ​​the object (110). For example, by referring to the visible point information 17, the identification information of the object extracted in step 106 is extracted to find the visible point IDs, and the mesh of the extracted point IDs is connected to form the visible area. Alternatively, the visible area of ​​the object may be defined as the range in which the object is not hidden by the ground or other objects through simulation in a virtual three-dimensional space. By performing a simulation in three-dimensional space each time, the visible point information 17 becomes unnecessary, and the amount of data to be prepared when the system starts up can be reduced.

[0051] If the recognition type = "Direction" is extracted from the text entered by the user, it is determined that the method of specifying the target area is "Direction," and a predetermined oval or elliptical area of ​​a specific width is obtained between the current location and the target object (111). Note that if the current location is not entered in the search request receiving unit 11, a target area based on direction cannot be obtained.

[0052] If the recognition type = "written" is extracted from the text entered by the user, the method of specifying the target area is determined to be "text information," and a query is generated to search for text information using the keyword extracted from the text entered by the user. The generated query is used to search for visible location information (text information) 17B, and the visible area of ​​the text information is obtained from the search results (112).

[0053] It is assumed that users will input text information such as "I can see the written XX," which may cause a conflict between the two recognition types: text information and visibility. In this case, it is best to prioritize the use of text information as the recognition type when searching for visible location information (text information) 17B. By using highly accurate text information to determine the visible area, rather than ambiguous information such as the shape and color of the object seen by the user, the accuracy of narrowing down the visible area can be improved.

[0054] As mentioned earlier, the textual information extracted from landscape images includes elements that change over time and elements that remain unchanged for extended periods. However, real-time updating of visible location information (textual information) 17B is difficult, and there is a possibility that it may differ from reality. To compensate for such discrepancies between the database and reality, it is advisable to calculate the reliability of the textual information and change the search method based on the reliability. The reliability should be determined by the attributes of the textual information. For example, it can be determined according to the meaning of the textual information. The string "Tozai Mart" is a store name and is often used on signs that are displayed for a long time, resulting in a high reliability value of 0.7. On the other hand, the string "Summer Campaign" is often used for short-term seasonal advertisements, resulting in a low reliability value of 0.3.

[0055] Choosing a search method based on confidence level is important. For example, for highly reliable text information, which is less likely to change, an exact match search should be used, while for less reliable text information, a fuzzy search should be used as it is more likely to change. By using a fuzzy search for less reliable text information, a search using the keyword "summer campaign" can retrieve not only "summer campaign" results but also "spring campaign" and "summer sweets." The degree of match (range of fuzzyness) in fuzzy searches can also be adjusted based on confidence level.

[0056] Furthermore, a similarity score is assigned between words. This can be done using an algorithm (e.g., word2vec) that vectorizes each word using a large corpus and calculates the similarity between words. For example, the similarity between "summer campaign" and "spring campaign" is set to 0.8, and the similarity between "summer campaign" and "summer sweets" is set to 0.6.

[0057] Next, identify candidate locations corresponding to the search results for each search keyword. Calculate a score for each candidate location obtained from the search results using word contribution and similarity. The score for each candidate location can be calculated, for example, by adding up the weighted contribution and similarity values ​​for all keywords. The keyword contribution can be calculated by the frequency with which the same text information is extracted from multiple image frames taken over time.

[0058] Specifically, if the keyword is "Tozai Mart's summer campaign," and at candidate location A, the contribution of "Tozai Mart" is 0.9 and the contribution of "summer campaign" is 0.2, the score is calculated as 0.9 + 0.2 = 1.1. At candidate location B, the frequency of occurrence of "Tozai Mart" is low and its contribution is 0.2, and a fuzzy search using "summer campaign" as the keyword yields "spring campaign" as a search result, with a contribution of 0.2 and a similarity of 0.8, the score is calculated as 0.2 + 0.2 × 0.8 = 0.36.

[0059] The area where the calculated score is greater than a predetermined threshold is defined as the visible area. The visible area may be represented on the map screen by coloring it according to its score. Alternatively, each candidate location may be ranked and displayed according to its score.

[0060] Once the process of acquiring the target area for all objects is complete (113), the screen generation unit 19 generates screen data that displays the acquired target areas overlaid on a map (114). For example, the search request receiving unit 11 acquires map data including the target object list and target areas (circles, visible range, range indicating direction) from the map information 18 and sends it to the screen generation unit 19. The screen generation unit 19 generates screen data by superimposing the target area information acquired from the search request receiving unit 11 with the map information 18. If multiple target areas have been acquired, it is advisable to display the degree of overlap between the target areas.

[0061] Note that Figure 8 includes four search methods for target areas ("neighborhood," "visible," "direction," and "text information"), but it may also process one or more of the target area specification methods.

[0062] Figure 10 shows an example of a search results screen displayed on the user terminal 20.

[0063] The search results screen shown in Figure 10 has a search term input field 1011, a search button 1012, and an exit button 1013 in the upper right, a search term display area 1020 in the middle right, a 3D city model display area 1030 in the lower right, and a map display area 1040 on the left.

[0064] The search term input field 1011 displays the words entered as a search request on the user terminal 20 via keyboard input or voice recognition. When the user operates the search button 1012, the text displayed in the search term input field 1011 is displayed in the search term display area 1020. In the search term display area 1020, the words used to search the 3D city model 16 are highlighted. To the left of the search term, a mark corresponding to the search term is displayed, which is superimposed on the map in the map display area 1040. The 3D city model display area 1030 displays an image of the city as seen from a specified point on the map, using data obtained from the 3D city model 16. The map display area 1040 displays a map with the area identified by the search superimposed on it.

[0065] When a user enters a search term and operates the search button 1012, the entered search term is sent to the location identification support server 10, a line of search conditions is added to the search term display area 1020, and the area identified by the search conditions is added to the map display area 1040. When the user operates the exit button 1013, the search term display area 1020 is cleared, the area superimposed on the map display area 1040 is removed, and only the map is displayed.

[0066] Figure 11 shows another example of the search results screen displayed on the user terminal 20, specifically the search results screen when the user has entered their current location.

[0067] The search results screen shown in Figure 11 has a search term input field 1011, a search button 1012, and an exit button 1013 in the upper right, a search term display area 1020 in the middle right, a 3D city model display area 1030 in the lower right, and a map display area 1040 on the left. The search term input field 1011, search button 1012, exit button 1013, and search term display area 1020 are the same as those shown in the search results screen in Figure 10. The 3D city model display area 1030 displays an image of the specified point on the map as seen from that point, using data obtained from the 3D city model 16, and the current location. The map display area 1040 displays a map with the area identified by the search superimposed on it, along with the current location. When the current location is entered, the area can be identified by direction, and the area related to that direction is superimposed on the map.

[0068] Figure 12 shows another example of the search results screen displayed on the user terminal 20, which is a search results screen where text information search results are superimposed.

[0069] The user entered "I can see a sign that says 'Tozai Mart'," and the visible area obtained by searching for the text information (Tozai Mart) is overlaid on the map. In the illustrated example, the convenience store adjacent to the East Church is Tozai Mart, and the area where the text on the Tozai Mart sign is legible extends in the direction of the adjacent parking lot.

[0070] As described above, the location identification support system of this embodiment can determine a location from information about the landscape seen by a person. In particular, by utilizing the developing 3D city model 16, it becomes possible to quickly determine a location using information about the landscape visible to a person. Furthermore, by determining the visible area using highly accurate textual information rather than ambiguous information such as the shape and color of objects seen by the user, the accuracy of narrowing down the visible area can be improved.

[0071] It should be noted that the present invention is not limited to the embodiments described above, but includes various modifications and equivalent configurations within the spirit of the attached claims. For example, the embodiments described above are described in detail for the purpose of clearly illustrating the present invention, and the present invention is not necessarily limited to having all the described configurations. Furthermore, some of the configurations of one embodiment may be replaced with those of another embodiment. Furthermore, configurations of other embodiments may be added to the configuration of one embodiment. Furthermore, some of the configurations of each embodiment may be added, deleted, or replaced with those of other embodiments.

[0072] Furthermore, each of the aforementioned configurations, functions, processing units, and processing means may be implemented in hardware, for example, by designing them as integrated circuits, or they may be implemented in software by having a processor interpret and execute programs that realize each function.

[0073] Information such as programs, tables, and files that implement each function can be stored in memory, hard disks, SSDs (Solid State Drives), or other storage media such as IC cards, SD cards, and DVDs.

[0074] Furthermore, the control lines and information lines shown are those deemed necessary for explanation purposes and do not necessarily represent all control lines and information lines required for implementation. In reality, it can be assumed that almost all components are interconnected. [Explanation of symbols]

[0075] 1 processor 2 memory 3 Auxiliary storage 4. Communication Interface 5 Input Interfaces 6 Output Interfaces 7 Keyboard 8 mice 9 Display device 10 Location identification support server 11 Search Request Reception Department 12 Search Key Generation Unit 13 Target Object Search Unit 14 Target area extraction unit 15 Glossary 16 3D City Models 17 Visible point information 18 Map Information 19 Screen generation section 20 User terminals 21. Search Request Input Function 22 Screen display function

Claims

1. A location identification support system that generates data for determining location, The system comprises a computing device that performs predetermined processing and a storage device that the computing device can access. The aforementioned storage device stores visible point character information, which contains character information included in the landscape. The aforementioned computing device includes a reception unit that receives input from the user, The aforementioned computing device includes a search key generation unit that identifies a search term for searching the visible location character information, The aforementioned computing device includes a screen generation unit that outputs screen data for displaying the position, The reception unit receives input of text information contained in the landscape, The search key generation unit identifies a search term for searching the visible location character information from the received character information, The aforementioned reception unit is The visible location character information is searched using the specified search term. Using the confidence and contribution of the received character information, the score of the visible location character information is calculated. The location information selected using the aforementioned score is obtained as information for narrowing down the location. The location identification support system is characterized in that the screen generation unit outputs screen data for displaying information for narrowing down the location.

2. A location identification support system according to claim 1, The aforementioned storage device stores a 3D city model including the attributes of the objects, The reception unit receives input for the landscape description, The search key generation unit identifies a search term for searching the 3D city model from the received landscape representation. The reception unit searches the 3D city model using the specified search term and obtains information to narrow down the location from the received landscape representation. The location identification support system is characterized in that the screen generation unit outputs screen data for displaying information for narrowing down the location from the text information and information for narrowing down the location from the landscape representation superimposed.

3. A location identification support system according to Claim 1, The location identification support system is characterized in that the reliability is a numerical value unique to the character information, determined according to the meaning of the character information.

4. A location identification support system according to Claim 1, The location identification support system is characterized in that the contribution is calculated based on the frequency of occurrence of the character information, which is determined from the time-series observation results of the character information.

5. A location identification support system according to Claim 1, The aforementioned visible location character information is, The observation results of the aforementioned textual information are recorded in chronological order. A location identification support system characterized by recording separately the results when the aforementioned character information was not observed and the results when the character information could not be detected by observation.

6. A location identification support system according to Claim 2, The aforementioned reception unit is Using the user input, it is determined whether to search for the visible location character information or the 3D city model. A location identification support system characterized by searching for the visible location text information when both the visible location text information and the 3D city model become search candidates.

7. A location identification support method for which a location identification support system generates data for identifying multiple locations, The location identification support system is comprised of a computer having a computing device that performs predetermined processing and a storage device accessible by the computing device. The aforementioned storage device stores visible point character information, which contains character information included in the landscape. The aforementioned location identification support method is The aforementioned computing device receives input from the user regarding textual information contained in the landscape, The arithmetic unit identifies a search term from the received character information to search for the visible location character information. The aforementioned computing device searches for the visible location character information using the specified search term, The calculation device uses the confidence level and contribution level of the received character information to calculate the score of the visible point character information. The calculation device acquires information about the position selected using the score as information for narrowing down the position. A method for assisting location identification, characterized in that the computing device generates and outputs screen data for displaying information for narrowing down the location.

Images