Information processing method and information processing device

Abstract

To provide a technique which can combine adjacent road graphs in high accuracy.SOLUTION: An information processing method for combining a first road graph corresponding to a first region, with a second road graph corresponding to a second region which partially overlaps with the first region, includes: a selection step of selecting any one edge from the plurality of edges which overlap with each other in the first road graph and the second road graph, maintaining the selected edge and deleting the edge which was not selected; and a merge step of determining whether or not to merge a first node, about the first node connected to the deleted edge, selecting a second node to be merged when merging it, and merging the first node to the second node.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an information processing method and an information processing device. [Background technology]

[0002] The map tiling system disclosed in Patent Document 1 divides an area into sub-areas, uses names for roads or railway lines so as not to be affected by the boundaries of the divided sub-areas, and generates the final map. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2012-168961 A Summary of the Invention [Problem to be solved by the invention]

[0004] One aspect of the present disclosure aims to provide a technology that can combine adjacent road graphs with high accuracy. [Means for solving the problem]

[0005] One aspect of the present disclosure is an information processing method for combining a first road graph corresponding to a first area and a second road graph corresponding to a second area that partially overlaps with the first area, comprising: a selection step for selecting one edge from a plurality of overlapping edges in the first road graph and the second road graph, maintaining the selected edge and deleting the unselected edges; and a merging step for determining whether or not to merge a first node connected to the deleted edge, and if so, selecting a second node to be merged, and merging the first node with the second node. Effect of the Invention

[0006] According to aspects of the present disclosure, adjacent road graphs can be combined with high accuracy. [Brief description of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram for explaining a road graph creation device (information processing device). [Diagram 2] 11A and 11B are diagrams for explaining a selection process for selecting edges to be maintained when combining road graphs. [Diagram 3] 11A and 11B are diagrams for explaining a merge process when combining road graphs. [Figure 4] 11A and 11B are diagrams for explaining a specific example of merging processing. [Diagram 5] FIG. 13 is a diagram for explaining a process for executing a combination process of road graphs in parallel. [Figure 6] 11A and 11B are diagrams for explaining an example of a process for executing a combination process of road graphs in parallel; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] Road graphs are created based on images of roads taken from satellite images or aerial photographs. There is a demand to create road graphs covering a wide area of ​​several hundred kilometers or more, but due to computational constraints, it is necessary to create road graphs from small images and combine these multiple road graphs to create a road graph covering a wide area. Therefore, it is required to perform the process of combining road graphs accurately and efficiently.

[0009] (Overall composition) 1(A) is a diagram showing the configuration of a road graph creation device (information processing device) 100 in one embodiment. The road graph creation device 100 includes a processor 110 and a memory 120. The memory 120 non-temporarily stores computer programs for causing the processor 110 to function as an image input unit 111, an ROI input unit 112, an ROI division unit 113, an image extraction unit 114, a road graph extraction unit 115, and a combination unit 116. The combination unit 116 has a selection unit 117 and a merging unit 118 as sub-functional units.

[0010] Fig. 1(B) is a diagram for explaining the process of creating a road graph from road images such as satellite images, aerial images, etc. An overview of each functional unit of the road graph creation device 100 will be explained with reference to Fig. 1(B).

[0011] The image input unit 111 acquires a road image and stores it in the memory 120. The ROI input unit 112 accepts input of a region of interest (ROI) for creating a road graph, and passes it to the ROI division unit 113. The ROI division unit 113 divides the region of interest into a plurality of sub-regions. The division is performed so that each sub-region partially overlaps with an adjacent sub-region. In one example, the sub-regions are all the same shape and size, and in another example, the sub-regions have different shapes or sizes. The image extraction unit 114 divides the road image acquired by the image input unit 111 into a plurality of divided road images (hereinafter also simply referred to as divided images) according to the sub-regions obtained by the ROI division unit 113. Note that a plurality of road images may be input, and a plurality of road images may be used to generate one divided road image.

[0012] The road graph extraction unit 115 extracts a road graph from each divided image. The road graph can be extracted using a known technique such as Sat2Graph (https: / / arxiv.org / abs / 2007.09547), which uses graph tensor encoding to infer a road graph from an image. The road graph extraction process can be executed in parallel for each divided image, and is therefore scalable. The road graph is composed of multiple road edges (hereinafter also simply referred to as edges) and multiple road nodes (hereinafter also simply referred to as nodes). An edge is a line segment corresponding to multiple points corresponding to a road. A node is an end point of an edge, and one node is connected to one or more edges.

[0013] The combining unit 116 combines multiple divided road graphs to create a road graph corresponding to the entire ROI. The combining process by the combining unit 116 can be considered as post-processing of the road graph extraction process. The combining process is performed using the selecting unit 117 and the merging unit 118. When combining adjacent road graphs, the selecting unit 117 decides which edge to select as the edge to be maintained from among the overlapping edges between the road graphs. The merging unit 118 merges the adjacent road graphs using the edges selected by the selecting unit. The details of the combining unit 116 (the selecting unit 117 and the merging unit 118) will be explained in detail later.

[0014] The important points in the merging process of divided road maps are to accurately merge two adjacent divided road graphs and to ensure scalability of the merging process of the entire road graph. To improve the merging accuracy, it is necessary to appropriately select and merge overlapping edges and nodes in adjacent divided road graphs. Also, to ensure scalability of the entire merging process, it is necessary to make it possible to execute merging processes for multiple areas in parallel. This embodiment improves these two points.

[0015] (Combining adjacent road maps) First, the process of combining two adjacent divided road graphs will be described with reference to Figures 2 and 3. Figure 2(A) is a flowchart of the selection process performed by the selection unit 117. The selection unit 117 executes the selection process on two adjacent divided road graphs.

[0016] Here, as shown in Fig. 2(B), an example will be explained in which processing is performed on the first divided road graph T1 and the second divided road graph T2. Hereinafter, the divided road graph T1 and the divided road graph T2 will be simply referred to as graph T1 and graph T2. In the area where graphs T1 and T2 overlap, graph T1 has edges E1-1 to E1-3, and graph T2 has edges E2-1 to E2-4.

[0017] In step S201, the selection unit 117 extracts multiple overlapping edges in the overlapping area of ​​the graph T1 and the graph T2. In the example of Fig. 2B, edges E1-1 and E2-1 overlap, edges 1-2 and 2-2 overlap, and edges 1-3 and 2-3 overlap. The selection unit 117 adds a buffer of a predetermined size (e.g., 5 meters) to each edge, and determines that two buffered edges overlap in any of the following cases: -Multi line intersection If it is a multipoint intersection In the case of a line intersection whose length is more than half the length of the shorter of the two edges

[0018] In step S202, the selection unit 117 assigns a score to edges determined to overlap (hereinafter also referred to as overlapping edges) and temporarily stores them in memory. At this time, the selection unit 117 assigns a score to each of the overlapping edges. The score is a function of the distance between the center of the region in the road graph and the edge and the edge length, and the closer the distance from the center of the region, the higher the score is calculated, and the longer the edge length, the higher the score is calculated. The reason for calculating the score in this way is that edges closer to the center of the region are less affected by image distortion and are more reliable, and longer edges are more reliable. Edges determined not to overlap are stored in memory as retained edges (edges that remain in the output connection graph).

[0019] In step 203, the selection unit 117 regroups the scored edges (in other words, the edges that are determined to overlap).

[0020] In step S204, the selection unit 117 keeps the edge with the highest score for each group and deletes the other edges.

[0021] FIG. 2(C) is a diagram showing an example of the result of the selection process for the edges shown in FIG. 2(B). Here, edge E1-1 is selected from overlapping edges E1-1 and E2-1. Similarly, edge 1-2 is selected from edges E1-2 and E2-2, and edge E2-3 is selected from edges E1-3 and E2-3. That is, edges E1-1, E1-2, and E2-3 are selected as overlapping edges to be kept by the selection process, and edges E2-1, E2-2, and E1-3 are deleted. Edge E2-4 is also determined not to be an overlapping edge, and is therefore an edge to be kept.

[0022] 3 is a flowchart showing the merging process by the merging unit 118. The merging process is executed on the results of the selection process.

[0023] First, let us explain the "degree of node." The "degree of a node" is defined as the number of edges connected to that node. For example, in FIG. 2(B), three nodes E1-1, E1-2, and E1-3 are connected to node N1, so the degree of node N1 is "3." Similarly, in FIG. 2(B), the degree of node N2 is "4." In FIG. 2(C), edge E1-3 has been deleted, so the degree of node N1 has changed to "2," and edges E2-1 and E2-2 have been deleted, so the degree of node N2 has changed to "2."

[0024] 3 is roughly divided into a loop process L1 including steps S301 to S307, and a loop process L2 including steps S308 to S310. Loop process L1 is performed on all nodes, and is a process for determining whether each node is to be a target for merge process (edge ​​reconnection). Loop process L2 is a process for actually merging nodes.

[0025] The node selected as the processing target in the loop process L1 is referred to as node n. In step S301, the merging unit 118 judges whether or not node n was connected to an edge deleted in the selection process. If the judgment is negative, node n is not the target of the merging process, and the loop process L1 moves to processing the next node. If the judgment is positive, the process proceeds to step S302.

[0026] In step S302, the merge unit 118 calculates the degree (k 0 ) is calculated.

[0027] In step S303, the merge unit 118 selects the node (referred to as node n') closest to node n.

[0028] In step S304, the merge unit 118 determines whether the distance between nodes n and n' is less than a threshold. If the distance is equal to or greater than the threshold, node n is not subject to the merge process, and the loop process L1 moves to the process of the next node. If the distance is less than the threshold, the process proceeds to step S305.

[0029] In step S305, the merge unit 118 determines whether the nodes n and n' are connected. If the node n is connected to the nearest node n', the node n is not subject to the merge process, and the loop process L1 moves to the process of the next node. If the node is connected, the process proceeds to step S306.

[0030] In step S306, the merging unit 118 determines whether or not the degree of node n approaches the node degree before the selection process by merging nodes n and n'. In detail, the merging unit 118 determines whether or not the following conditional expression is satisfied. ABS(k 0 -k 1 ) < ABS(k 0 -k 2 )

[0031] where ABS is a function that returns the absolute value, and k 0is the degree of node n before the selection process, and k 1 teeth The degree of node n after the selection process, k 2 is the degree of node n when nodes n and n' are merged.

[0032] If the above conditional expression is not satisfied, node n is not a target for merging, and loop process L1 moves to processing of the next node. If the above conditional expression is satisfied, the process proceeds to step S307.

[0033] In step S307, the merging unit 118 stores the node n as a merging candidate in memory. At this time, the merging unit 118 stores the node n' as a merging destination of the node n in association with the node n.

[0034] The loop process L1 is executed for all the nodes.

[0035] Here, a specific description will be given with reference to Figures 2(B) and 2(C). It is assumed that the distance between nodes N1 and N2 is less than the threshold value in step S304.

[0036] Node N2 is connected to edges E2-1 and E2-2 that were deleted in the selection process, and the distance to the nearest node N2 is less than the threshold, so the degree of node N2 changes from "2" to "4" due to the merger, approaching the degree of node N before the selection process of "4." Therefore, node N2 is determined to be merged with node N1.

[0037] Node N1 is connected to edges E2-1 and E2-2 that were deleted in the selection process, and the distance to the nearest node N2 is less than the threshold. However, the degree of node N2 changes from "2" to "4" by merging with node N1, and does not approach the degree "3" before the selection process. Therefore, node N1 is not determined as a node to be merged with other nodes.

[0038] The loop process L2 is executed for each merge candidate node stored in step S307. Hereinafter, the candidate node to be processed in the loop process is referred to as node m.

[0039] In step S308, it is determined whether there is another candidate node m' adjacent to the candidate node m. The distance threshold for this proximity determination may be the same as the threshold in step S304, or it may be different. There may be a plurality of candidate nodes m'. If the candidate node m is adjacent to the other candidate node m', the process proceeds to step S309, and if not, the process proceeds to step S310.

[0040] In step S309, the merging unit 118 determines the merge destination node position based on the candidate node m and the candidate node m' in order to merge the candidate node m and the adjacent candidate node m' into the same node. Examples of the merge destination node position are the position of the candidate node m, the position of the candidate node m', the average position (centre of gravity) of the candidate node m and the candidate node m', and the weighted average position of the candidate node m and the candidate node m'. Note that the weight in the weighted average can be determined based on the scores of the edges connected to the node, and can be, for example, a value according to the sum or average of the scores of the edges connected to the node.

[0041] Even if there is no other candidate node adjacent to candidate node m, the position of the merge destination node of candidate node m may be determined as described above based on candidate node m and its merge destination node (nodes n and n' in step S307). Also, even if there is another candidate node adjacent to candidate node m, the position of the merge destination node may be determined in the same manner as described above, taking into account the merge destination node of the candidate node.

[0042] In step S310, the merging unit 118 merges the merge candidate node with the merge destination node. As an example, the merging unit 118 connects an edge that was connected to the merge candidate node to the merge destination node, and deletes the merge candidate node.

[0043] If the determination in step S308 is affirmative, the merging unit 118 merges the candidate nodes m and m' with the merge destination node. The merging unit 118 may also create a new node having the merge destination node position determined in step S309 and merge the nodes m and m' into the new node. Alternatively, the merging unit 118 may change the position of the merge destination node of either the nodes m or m' and merge the other node into the node after the change in position.

[0044] The loop process L2 is repeated until there is no unprocessed candidate node m.

[0045] Here, a specific explanation will be given with reference to Fig. 4. Fig. 4(A) is the same as Fig. 2(B).

[0046] Fig. 4(B) is a diagram after nodes N2 and N1 in Fig. 4(A) are merged with N2 as the merge destination node. Edges E2-3 and E2-4 connected to node N2 before processing are changed to edges E2-3' and E2-4' connected to node N1. Edges E1-1 and E1-2 connected to node N1 before processing are not changed.

[0047] FIG. 4(C) is a diagram of FIG. 4(A) after merging nodes N2 and N1 with a new node N3 as the merge destination node. Here, the position of node N3 is the average position of nodes N1 and N2, but it may be another position. Edges E1-1 and E1-2 connected to node N1 before processing are changed to edges E1-1' and E1-1' connected to node N3. Similarly, edges E2-3 and E2-4 connected to node N2 before processing are changed to edges E2-3' and E2-4' connected to node N3.

[0048] (Parallel processing of road map merging) A method of performing the above-mentioned adjacent road map combining process in parallel over the entire ROI region will be described with reference to Figures 5 and 6. The adjacent road map combining process can also be called a post-processing after the road graph extraction.

[0049] FIG. 5A is a flowchart of the combining process (post-processing) performed by the combining unit 116.

[0050] In step S501, the combining unit 116 acquires a plurality of divided road graphs extracted by the road graph extraction unit 115. In one embodiment, as shown in Fig. 5(B), the divided road graph has a rectangular shape, and the rectangular divided road graphs are arranged in the horizontal and vertical directions. Note that the vertical and horizontal directions are used for convenience of explanation, and these two directions may be any directions, and do not have to be perpendicular to each other.

[0051] In step S502, the combining unit 116 divides the divided road graphs into groups and assigns a label to each divided road graph in the group. In one embodiment, the combining unit 116 divides the divided road graphs into groups so that each group contains nine divided road graphs (3×3), as shown in FIG. 5(B). The combining unit 116 also assigns labels to the divided road graphs belonging to each group based on their positions within the group. That is, the divided road graphs are assigned labels according to their relative positions within the group. In FIG. 5(B), the labels are numbers from "1" to "9", but they do not need to be numbers as long as they can be distinguished. Labels and label assignments can also be called classes and class classification, respectively.

[0052] In step S503, the combining unit 116 selects one label from the multiple labels. In step S504, the combining unit 116 executes a selection process by the selection unit 117 and a merging process by the merging unit 118 on the divided road graph having the selected label and its neighboring divided road graphs, thereby combining the divided road graphs. The combining unit 116 executes the combining process (selection process and merging process) in parallel for each group. Since the divided road graphs to be processed in the combining process differ between groups, the combining process (selection process and merging process) can be executed in parallel for each group.

[0053] In step S505, it is determined whether all the divided road graphs have been combined, and if there are any uncombined divided road graphs remaining, the process proceeds to step S503 to select another label and repeat the process. When all the divided road graphs have been combined, the process ends.

[0054] The parallel execution of the joining process will be specifically described with reference to Fig. 6. Fig. 6(A) shows a specific example of the loop process of steps S503 to S505 in the flowchart of Fig. 5(A). .

[0055] In step S601, the combining unit 116 selects an arbitrary label from among the nine labels of a 3×3 matrix. Here, it is assumed that the label "1" located in the corner of the nine labels is selected.

[0056] In step S602, the combining unit 116 executes combining processing (selection processing and merging processing) for the nine divided road graphs, that is, the divided road graph with the selected label "1" and its eight neighboring road graphs. Since there are a total of 12 overlapping areas in the nine divided road graphs, the combining processing for these 12 overlapping areas (boundary areas) is performed sequentially. The combining unit 116 also executes the combining processing for each group in parallel.

[0057] In Fig. 6(B), the divided road graphs referenced in each of the merging processes executed in parallel are indicated by bold rectangles. As shown in the figure, each merging process processes different divided road graphs, so each merging process can be executed simultaneously in parallel.

[0058] In Fig. 6(C), the overlapping area (boundary area) that is merged by the merging process with the label "1" at its center is shown in bold. As described above, the overlapping areas inside the nine divided road graphs with the label "1" at their center are merged.

[0059] In step S603, the combining unit 116 selects a label different from the label "1" selected in step S601. The label selected here may be any label that is in a different position horizontally and vertically from the label selected in step S601. Here, it is assumed that the label "9" diagonally opposite the label "1" is selected.

[0060] In step S604, the combining unit 116 executes the combining process (selection process and merging process) in parallel for the nine divided road graphs, that is, the selected divided road graph with label "9" and its eight neighboring road graphs. Note that the combining process may be omitted for the overlapping areas for which the combining process was performed in step S602.

[0061] Fig. 6(D) shows the divided road graphs to be processed in each of the merging processes executed in parallel as bold rectangles 620. Fig. 6(E) also shows in bold the overlapping area (boundary area) to be merged by the merging process with label "9" at its center.

[0062] As can be seen from Figures 6(C) and 6(E), by performing a merging process on the labels "1" and "9" (or the two diagonally opposite divided road graphs in a 3x3 divided road graph), the entire divided road graph will be merged.

[0063] In the above explanation, the merging process is performed on the labels "1" and "9", but the entire merging process can be performed by performing the merging process on two labels, namely, the label "1" and one of the labels "5", "6", "8", or "9". In other words, it is sufficient to perform the merging process on two labels, namely, one of the nine labels in the 3x3 divided road graph and another label that is in a different position both vertically and horizontally from the one label.

[0064] (Modification 1 of the joining process) In addition, although the entire interior of the nine divided road graphs is the target of the merging process, it is also possible to only target the overlapping area between the selected label and its four neighboring divided road graphs. In this case, by selecting the labels "1", "3", "5", "7", and "9" and performing the merging process five times, the entire graph will be merged.

[0065] (Modification 2 of the joining process) More generally, the size of a group may be any size, for example 2x2, or 4x4 or more. Also, the vertical and horizontal sizes of a group may be different, i.e., the size of a group may be pxq (p≧2, q≧2).

[0066] The combining unit 116 may combine multiple road graphs that are aligned in the first direction and the second direction and partially overlap with adjacent regions by parallel execution as follows. The combining unit 116 divides the multiple road graphs into a first group in a mutually exclusive and exhaustive (MECE) manner (see region 610 in FIG. 6B). Here, each group has the same shape including a p×q (p≧2, q≧2) road graph. Then, the combining unit 116 performs a combining process to combine the multiple road graphs in the first group. Here, the combining process is performed in parallel on a group-by-group basis. Next, the combining unit 116 divides the multiple road graphs into a second group in a mutually exclusive and exhaustive (MECE) manner (see region 620 in FIG. 6D). Compared to the first grouping, the second grouping has different group boundary positions in the first direction and the second direction. Then, the combining unit 116 performs a combining process to combine the multiple road graphs in the second group. In general, multiple road graphs can be combined as a whole by performing a combining process on two groups in this way. The process can be executed in parallel.

[0067] (Effects of the embodiment) According to the above embodiment, a road graph can be created from road images of a wide area by executing the road graph extraction process and the merging process in parallel. Because parallel processing is possible, it is possible to create a road graph of a wider area by investing computational resources without increasing the overall processing time. Furthermore, according to the selection process and merging process of the above embodiment, it is possible to quickly and accurately merge two road graphs.

[0068] (Other embodiments) The above-described embodiment is merely an example, and the present disclosure can be modified and implemented as appropriate without departing from the spirit and scope of the present disclosure.

[0069] The present disclosure can also be realized by supplying a computer program implementing the functions described in the above embodiments to a computer, and having one or more processors of the computer read and execute the program. Such a computer program may be provided to the computer by a non-transitory computer-readable storage medium connectable to the system bus of the computer, or may be provided to the computer via a network. Non-transitory computer-readable storage media include, for example, any type of disk, such as a magnetic disk (floppy disk, hard disk drive (HDD), etc.), an optical disk (CD-ROM, DVD disk, Blu-ray disk, etc.), a read-only memory (ROM), a random access memory (RAM), an EPROM, an EEPROM, a magnetic card, a flash memory, an optical card, and any type of medium suitable for storing electronic instructions. [Explanation of symbols]

[0070] 100: Road graph creation device (information processing device) 110: Processor 111: Image input unit 112: ROI input unit 113: ROI division unit 114: Image extraction unit 115: Road graph extraction unit 116: Combination unit 117: Selection section 118: Merge section

Claims

1. 1. An information processing method for combining a first road graph corresponding to a first region and a second road graph corresponding to a second region partially overlapping the first region, comprising: a selection step of selecting one edge from among a plurality of overlapping edges in the first road graph and the second road graph, keeping the selected edge and deleting the unselected edges; a merging step of determining whether or not to merge a first node connected to the deleted edge, and if so, selecting a second node to be merged, and merging the first node into the second node; 13. An information processing method comprising:

2. The merging step includes: selecting a node closest to the first node as the second node; merging the first node and the second node if a predetermined condition is met; Including, The predetermined condition is: the distance between the first node and the second node is less than a threshold; The first node and the second node are not connected, and a difference between the number of edges connected to the first node after the merging and the number of edges connected to the first node before the selection step is smaller than a difference between the number of edges connected to the first node before the merging and the number of edges connected to the first node before the selection step; The condition is, 2. The information processing method according to claim 1,

3. 3. The information processing method according to claim 2, characterized in that, in the merging step, a position of a node after merging the first node and the second node is at least one of a position of the first node, a position of the second node, an average position of the position of the first node and the position of the second node, and a weighted average position of the position of the first node and the position of the second node using weights based on scores of edges connected to the nodes.

4. The selecting step includes a step of calculating scores of the plurality of edges, and a step of selecting an edge having the highest score from the plurality of edges, The score is calculated to be higher the closer the distance between the edge and the center of the road graph to which the edge belongs, and the longer the length of the edge, the higher the score is calculated.

2. The information processing method according to claim 1, further comprising:

5. An information processing device including a processor and a storage device, The storage device, when executed by the processor, a selection step of selecting one edge from among a plurality of overlapping edges in a first road graph corresponding to a first region and a second road graph corresponding to a second region partially overlapping the first region, maintaining the selected edge and deleting the unselected edges; a merging step of determining whether or not to merge a first node connected to the deleted edge, and if so, selecting a second node to be merged, and merging the first node into the second node; 4. An information processing apparatus comprising:

Images