JP6876445B2 - Data compressors, control methods, programs and storage media - Google Patents

Description

The present invention relates to a technique for compressing data.

Conventionally, a technique for efficiently processing or storing a large amount of measurement data has been known. For example, Patent Document 1 discloses a technique for shortening the processing time of three-dimensional CG display of point cloud data output by a laser scanner mounted on a moving body. Further, Patent Document 2 discloses a technique for compressing three-dimensional data.

Japanese Unexamined Patent Publication No. 2015-158772 Japanese Unexamined Patent Publication No. 2016-115332

When saving the output of a measuring device such as a laser scanner mounted on a moving body, the amount of data becomes enormous, so it is preferable to compress and save the data. On the other hand, for measurement data used for control that requires high accuracy such as automatic operation, it is not preferable that the reproducibility (that is, accuracy) is lowered by compression.

The present invention has been made, for example, in order to solve the above-mentioned problems, and an object of the present invention is to provide a data compression device capable of suitably compressing measurement data.

The invention according to claim 1 is a data compression device.
Point cloud data that has a light emitting unit that emits light and a light receiving unit that receives the light, and is output by a measuring device that includes a feature in the measurement range, and can specify the light receiving level at which the light receiving unit receives the light. The acquisition unit that acquires the measurement data that is
A compression unit for compressing the measurement data is provided.
Based on the light receiving level , the compression unit lowers the compression rate of the first measurement data corresponding to a specific feature in the measurement data to be lower than the compression rate of the second measurement data other than the first measurement data. It is characterized by doing.

The invention according to claim 7 is a control method executed by a data compression device.
Point cloud data that has a light emitting unit that emits light and a light receiving unit that receives the light, and is output by a measuring device that includes a feature in the measurement range, and can specify the light receiving level at which the light receiving unit receives the light. The acquisition process to acquire the measurement data, which is
It has a compression step of compressing the measurement data.
In the compression step, the compression rate of the first measurement data corresponding to a specific feature in the measurement data is lower than the compression rate of the second measurement data other than the first measurement data based on the light receiving level. It is characterized by doing.

The invention according to claim 8 is a program executed by a computer.
Point cloud data that has a light emitting unit that emits light and a light receiving unit that receives the light, and is output by a measuring device that includes a feature in the measurement range, and can specify the light receiving level at which the light receiving unit receives the light. The acquisition unit that acquires the measurement data that is
The computer is made to function as a compression unit for compressing the measurement data.
Based on the light receiving level , the compression unit lowers the compression rate of the first measurement data corresponding to a specific feature in the measurement data to be lower than the compression rate of the second measurement data other than the first measurement data. It is characterized by doing.

This is a schematic configuration of a data compression system. The block configuration of the in-vehicle device is shown. An example of the data structure of the compression rate determination table is shown. It is a flowchart about the generation of compression point cloud data. It is a figure which showed the ray of the pulse laser emitted by a rider. The outline of the data compression system according to the modification is shown.

According to a preferred embodiment of the present invention, the data compression device includes an acquisition unit for acquiring measurement data output by the measurement device including the feature in the measurement range, and a compression unit for compressing the measurement data. The compression unit makes the compression rate of the first measurement data corresponding to a specific feature of the measurement data lower than the compression rate of the second measurement data other than the first measurement data.

The data compression device includes an acquisition unit and a compression unit. The acquisition unit acquires the measurement data output by the measurement device that includes the feature in the measurement range. Here, "feature" refers to all objects on the ground regardless of whether they are natural or artificial, and includes flat objects such as white lines painted on the road. The compression unit compresses the measurement data acquired by the acquisition unit. Here, the compression unit lowers the compression rate of the first measurement data corresponding to a specific feature among the measurement data acquired by the acquisition unit to be lower than the compression rate of the second measurement data other than the first measurement data. To do. By doing so, the data compression device reduces the amount of data as a whole while suppressing the deterioration of the accuracy of the measurement data corresponding to a specific feature that requires high-precision measurement data due to compression. The measurement data can be preferably compressed as described above.

In one aspect of the data compression device, the specific feature is a feature to be detected in automatic operation. For features to be detected in automatic operation, high-precision measurement data is required, so it is preferable to prioritize accuracy (reproducibility) over compression rate. Therefore, according to this aspect, the data compression device can suitably compress the measurement data as a whole without deteriorating the accuracy of the measurement data of the feature to be detected in the automatic operation.

In another aspect of the data compression device, the compression unit compresses the first measurement data by lossless compression or does not compress the first measurement data. As a result, the data compression device can surely suppress the deterioration of the accuracy of the measurement data corresponding to the specific feature due to the compression.

In another aspect of the data compression device, the measuring device has an emission unit that emits light while changing the emission direction and a light receiving unit that receives the light, and the compression unit has the light receiving unit. The first measurement data is identified based on the light receiving level at which light is received. In general, the reflectance of light differs depending on the feature. Therefore, in this aspect, the data compression device determines whether or not the feature irradiated with the light is a specific feature by referring to the light receiving level received by the measuring device. As a result, the data compression device can suitably identify the first measurement data from the measurement data acquired by the acquisition unit.

In another aspect of the data compression device, for each feature, setting information in which information on the compression rate is associated with information on the reflectance of the feature or the light receiving level of the light reflected by the feature is stored. The compression unit refers to the setting information, identifies the measurement data for each feature from the light receiving level at which the light receiving unit receives the light, and identifies each of the identified measurement data. Determine the compression ratio. According to this aspect, the data compression device can refer to the setting information and compress the measurement data at a compression rate suitable for each feature.

In another aspect of the data compression device, the compression unit identifies the first measurement data based on the color information of each position indicated by the measurement data. Also in this aspect, the data compression device can suitably identify the first measurement data from the measurement data acquired by the acquisition unit based on the color of each object.

According to another preferred embodiment of the present invention, the control method executed by the data compression device is the acquisition step of acquiring the measurement data output by the measurement device including the feature in the measurement range, and the measurement data. It has a compression step of compressing, and the compression step compresses the compression rate of the first measurement data corresponding to a specific feature among the measurement data, and compresses the second measurement data other than the first measurement data. Lower than the rate. By executing this control method, the data compression device suppresses the deterioration of the accuracy of the measurement data corresponding to a specific feature that requires high-precision measurement data due to compression, and reduces the total amount of data. The measurement data can be preferably compressed so as to be reduced.

According to another preferred embodiment of the present invention, a computer-executed program, an acquisition unit that acquires measurement data output by a measurement device that includes a feature in the measurement range, and compression that compresses the measurement data. The computer is made to function as a unit, and the compression unit sets the compression rate of the first measurement data corresponding to a specific feature among the measurement data from the compression rate of the second measurement data other than the first measurement data. Also lower. By executing this program, the computer should reduce the amount of data as a whole while suppressing the deterioration of the accuracy of the measurement data corresponding to a specific feature that requires high-precision measurement data due to compression. The measurement data can be appropriately compressed. Preferably, the program is stored in a storage medium.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

[Overview of data compression system]
FIG. 1 is a schematic configuration of a data compression system according to this embodiment. The data compression system includes a vehicle traveling on the road and an in-vehicle device 1 moving together with the vehicle.

The vehicle-mounted device 1 has a lidar (Light Detection and Ranking) 30 installed in the vehicle. Then, the vehicle-mounted device 1 compresses and stores the point cloud data related to the features around the vehicle (including the sign 50 in FIG. 1) output by the rider 30. The in-vehicle device 1 is an example of the "data compression device" in the present invention.

The rider 30 measures the distance to an object existing in the outside world discretely by emitting a pulsed laser with respect to a predetermined angle range in the horizontal direction and the vertical direction, and a three-dimensional point indicating the position of the object. Generate groups data. In this case, the rider 30 has an exit unit that emits a pulsed laser while changing the irradiation direction, a light receiving unit that receives reflected light (scattered light) of the irradiated pulse laser, and a point group based on a light receiving signal output by the light receiving unit. It has an output unit that outputs data. The point cloud data is generated based on the irradiation direction corresponding to the pulsed laser received by the light receiving unit and the response delay time of the pulsed laser specified based on the above-mentioned received signal. In this embodiment, the point cloud data includes the position information of each point with respect to the vehicle (that is, relative three-dimensional coordinate data) and the level of the light receiving signal corresponding to each point (also referred to as "light receiving level"). .) And can be identified. The rider 30 is an example of the “measurement device” in the present invention, and the point cloud data is an example of the “measurement data” in the present invention. Instead of scanning in both the horizontal direction and the vertical direction, the rider 30 may incline the emission direction of the pulse laser from the horizontal direction so that the scanning surface is oblique to the horizontal direction.

FIG. 2 is a block diagram showing a functional configuration of the vehicle-mounted device 1. The on-board unit 1 mainly includes a communication unit 11, a storage unit 12, a sensor unit 13, an input unit 14, a control unit 15, and an output unit 16. Each of these elements is connected to each other via a bus line.

The communication unit 11 performs data communication with another device based on the control of the control unit 15. The storage unit 12 stores a program executed by the control unit 15 and information necessary for the control unit 15 to execute a predetermined process. Further, the storage unit 12 stores the compression rate determination table 20 that defines the compression rate of the point cloud data to be applied to each feature, and the compression point cloud data 21 that is the point cloud data after the compression process. The compression rate determination table 20 is referred to by the control unit 15 when compressing the point cloud data generated by the rider 30. The compression rate determination table 20 is an example of "setting information" in the present invention.

The sensor unit 13 is composed of an internal sensor for detecting the state of the vehicle and an external sensor for recognizing the surrounding environment of the vehicle. In addition to the rider 30 described above, the sensor unit 13 includes a camera 31 for photographing the scenery outside the vehicle and a GPS receiver. 32, a gyro sensor 33, a speed sensor 34, and the like are included. The outputs of the GPS receiver 32, the gyro sensor 33, the speed sensor 34, and the like are used to identify, for example, the current position and traveling direction of the vehicle.

The input unit 14 is a button, a touch panel, a remote controller, a voice input device, etc. for the user to operate, and the output unit 16 is, for example, a display, a speaker, or the like that outputs under the control of the control unit 15.

The control unit 15 includes a CPU that executes a program and the like, and controls the entire vehicle-mounted device 1. In this embodiment, the control unit 15 compresses the point cloud data output by the rider 30 with reference to the compression rate determination table 20, and stores it in the storage unit 12 as the compression point cloud data 21. The control unit 15 is an example of a “acquisition unit”, a “compression unit” in the present invention, and a computer that executes a program in the present invention.

[Compression rate determination table]
FIG. 3 shows an example of the data structure of the compression ratio determination table 20. The compression rate determination table 20 shown in FIG. 3 has items of "feature type", "compression rate", "reflectance", and "RGB". In FIG. 3, "A" to "H" and "a" to "z" represent predetermined numerical values, respectively.

Here, the "feature type" indicates the type of the feature represented by the point cloud data. The feature type may represent any feature such as a white line, a road sign, a utility pole, a building shown in FIG. 3, a road marking, a traffic light, and a signboard.

"Compression rate" indicates the compression rate applied to the point cloud data representing the corresponding feature type. In the example of FIG. 3, there are two stages of compression rates, "high" and "low", and the storage unit 12 has a known data compression algorithm that realizes each of the "high" and "low" compression rates. It is remembered. Here, for example, when the compression rate is "high", a data compression algorithm of lossy compression is used, and when the compression rate is "low", reversible compression or similar high reproducibility is obtained. A data compression algorithm is used. When the compression rate is "low", the control unit 15 may not perform data compression of the corresponding point cloud data. That is, in this case, the control unit 15 compresses the corresponding point cloud data with the lowest compression rate.

Further, in the example of FIG. 3, the compression rate is set to "low" for white lines and road signs that are likely to be detected in automatic driving, and there is a possibility that they will be detected in automatic driving of buildings and the like. For low point cloud data, the compression ratio is set to "high". In this way, the point cloud data of the features to be detected in the automatic operation has a low compression rate in order to suppress deterioration due to compression, and the point cloud data of other features has a high compression rate. To reduce the amount of data. The control unit 15 may compress the point group data representing the features not registered in the compression rate determination table 20 by the data compression algorithm corresponding to the compression rate of "high". Compression may be performed by a data compression algorithm having a compression ratio intermediate between "high" and "low". The information recorded in the item "compression rate" is an example of "information about the compression rate" in the present invention. The “detection target” referred to here refers to point cloud data of a feature that is likely to be used by a control unit that automatically drives a vehicle. That is, in this embodiment, it is point cloud data such as white lines and road signs.

"Reflectance" indicates a range of general reflectance for a pulsed laser of a feature defined in "Feature type". In general, the reflectance of a feature is proportional to the light receiving level of the pulsed laser reflected by the feature. Therefore, the control unit 15 uses the light receiving level information included in the point group data to determine the ground irradiated with the pulse laser. It is possible to estimate the reflectance of an object. Therefore, in this embodiment, the control unit 15 corresponds to the corresponding feature based on the reflectance estimated from the light receiving level included in the point cloud data and the range of the reflectance recorded in the item of "reflectance". Identify the type.

“RGB” indicates the RGB color information of the feature defined in the “feature type”. In the example of FIG. 3, the possible range of each of the assumed R, G, and B colors is recorded for each feature type. By referring to the item of "RGB", the control unit 15 can specify the feature defined in the compression rate determination table 20 based on the RGB value of each pixel of the image captured by the camera 31. .. In this case, first, the control unit 15 identifies the pixels of the captured image of the camera 31 to which each point of the point cloud data output by the rider 30 corresponds. For example, the control unit 15 stores in advance a correspondence table between the two-dimensional coordinate system of the captured image of the camera 31 and the three-dimensional coordinate system of the point cloud data output by the rider 30, and refers to the table. In, the pixels of the image corresponding to each point of the point cloud data are specified. Then, the control unit 15 specifies the corresponding feature type based on the RGB value of the specified pixel and the respective value ranges of R, G, and B recorded in the item of "RGB".

The control unit 15 is limited to the case where the corresponding feature type cannot be specified only by the item of "reflectance" (for example, when the reflectance estimated from the light receiving level belongs to the range of the reflectance of a plurality of feature types). By referring to the item of "RGB", the corresponding feature type may be specified.

[Processing flow]
FIG. 4 is an example of a flowchart relating to the generation of the compression point cloud data 21 executed by the control unit 15 in this embodiment. The control unit 15 repeatedly executes the processing of the flowchart shown in FIG. 4 every time, for example, the rider 30 outputs the point cloud data obtained by one scan.

First, the control unit 15 acquires the point cloud data output by the rider 30 (step S101). Here, for example, the rider 30 emits a pulsed laser with respect to a predetermined angle range in the horizontal direction and the vertical direction, and the control unit 15 emits 3 of each point of the object irradiated with the pulsed laser emitted by the rider 30. The lidar 30 receives point group data capable of specifying the three-dimensional coordinates and the light receiving level of the pulsed laser reflected at each point.

Next, the control unit 15 identifies the point cloud data for each feature (step S102). For example, the control unit 15 divides each point of the point cloud data existing in the predetermined angle ranges in the horizontal direction and the vertical direction obtained in step S101 for each feature based on the difference in the light receiving level. In this case, the control unit 15 may identify the point cloud data for each feature based on, for example, a known three-dimensional segmentation algorithm.

After that, the control unit 15 refers to the compression rate determination table 20 to specify the compression rate to be applied to the features indicated by the point cloud data identified for each feature (step S103). For example, the control unit 15 estimates the reflectance of each object based on the average of the light receiving levels of each point of the point cloud data identified for each feature in step S102, and determines the feature type corresponding to the estimated reflectance. , It is specified by referring to the compression ratio determination table 20. Further, instead of or in addition to this, the control unit 15 identifies the pixels of the captured image of the camera 31 corresponding to the point cloud data identified for each feature in step S102, and the RGB values of the specified pixels. The feature type corresponding to is specified by referring to the compression ratio determination table 20.

Next, the control unit 15 compresses the point cloud data based on the compression rate specified in step S103 (step S104). In this case, for example, the control unit 15 determines the data compression algorithm to be applied from the compression rate specified in step S103, and corresponds to the data compression algorithm for each of the point cloud data identified for each feature in step S102. To apply. As a result, the control unit 15 performs highly reproducible compression (including the case where compression is not performed) without deteriorating the accuracy of features that require high-precision data, and requires high-precision data. For features that do not, the amount of data is suitably reduced by compressing with a high compression rate.

Then, the control unit 15 stores the point cloud data compressed in step S104 as the compressed point cloud data 21 in the storage unit 12 (step S105). After that, the compressed point cloud data 21 stored in the storage unit 12 is supplied to a server device that manages map data used for, for example, automatic operation, and is used for updating the map data.

The control unit 15 obtains the point cloud data before or after compression based on the position of the vehicle, the traveling direction, the installation angle of the rider 30 with respect to the vehicle, and the like from the relative three-dimensional coordinates with respect to the vehicle. It may be converted into absolute three-dimensional coordinates based on latitude, longitude, altitude, etc. In this case, for example, the control unit 15 specifies the position and traveling direction of the vehicle based on the output of the sensor unit 30 when the point cloud data is acquired in step S101, and the rider 30 stored in advance in the storage unit 12 By reading out the installation angle information, the above-mentioned coordinate conversion process is performed. As a result, the control unit 15 can store the compressed point cloud data 21 represented by the general-purpose absolute coordinate system. Instead of this, the control unit 15 uses the compressed point cloud data and information on the vehicle position, the traveling direction, and the installation angle of the rider 30 so that the above-mentioned coordinate conversion process can be executed later. It may be associated and stored as the compressed point cloud data 21.

[Concrete example]
Next, a specific example of utilizing the compression rate determination table 20 shown in FIG. 3 will be described. FIG. 5 is a diagram showing a light beam of a pulsed laser emitted by the rider 30. In the example of FIG. 5, the rider 30 emits a pulse laser with a predetermined angular resolution determined by the pulse period for a predetermined angular range (about 210 ° in this example) including the front direction of the vehicle. doing. The rider 30 emits a pulse laser for a predetermined angle range not only in the horizontal direction but also in the vertical direction, or the scanning surface is tilted with respect to the horizontal direction, so that the rider 30 is directed with respect to the road surface. However, it shall irradiate a pulse laser.

In this case, the pulsed laser emitted by the rider 30 irradiates various objects including the white lines 51a to 51c, the road sign 52, the utility pole 53, and the building 54, and the reflected light is received by the rider 30. In this case, the control unit 15 receives the point cloud data generated based on the received signal of the reflected light from the rider 30 (see step S101 in FIG. 4), and identifies the point cloud data for each feature (see step S102). ). Then, the control unit 15 refers to the compression rate determination table 20 and specifies the compression rate of the point cloud data divided for each feature (see step S103). Specifically, the control unit 15 highly reproduces the point cloud data based on the pulse laser reflected by the white lines 51a to 51c and the road sign 52, which are features that should be detected with high accuracy during automatic driving or the like. Set the compression ratio to "low" to maintain the property. On the other hand, the control unit 15 sets the compression ratio to "high" for the utility pole 53 and the building 54, which are less likely to be detected with high accuracy, to reduce the amount of data.

As described above, the in-vehicle device 1 according to the present embodiment acquires the point cloud data output by the rider 30 including the feature in the measurement range, compresses the point cloud data, and stores it as the compressed point cloud data 21. To do. At this time, the in-vehicle device 1 refers to the compression rate determination table 20, and among the point cloud data output by the rider 30, compresses the point cloud data corresponding to a specific feature and compresses the other point cloud data. Lower than the rate. As a result, the on-board unit 1 is suitable for reducing the amount of data as a whole while suppressing deterioration of the point cloud data corresponding to a specific feature that requires highly accurate measurement data due to compression. The point cloud data can be compressed.

[Modification example]
Next, a modification suitable for the embodiment will be described. The following modifications may be applied to the above-described embodiment in any combination.

(Modification example 1)
The data structure of the compression ratio determination table 20 shown in FIG. 3 is an example, and the data structure to which the present invention can be applied is not limited to the structure shown in FIG.

For example, the compression rate determination table 20 may record only the records corresponding to the features whose "compression rate" should be "low". In this case, the utility pole and building records of FIG. 3 are not recorded in the compression rate determination table 20, and the item of "compression rate" is omitted. In the second example, the "compression rate" in FIG. 3 is not limited to the two stages of "high" and "low", and may have three or more stages. Even in this case, it is preferable that the feature related to the automatic operation is set so as not to perform the compressibility or compression that can be realized by lossless compression. In the third example, a specific compression rate may be specified by a numerical value for the “compression rate” in FIG. In this case, for example, the control unit 15 executes the point cloud data compression process by a data compression algorithm that can specify the compression rate.

In the fourth example, in the compression rate determination table 20, instead of or in addition to the item of "reflectance", the "light receiving level" that defines the range of the light receiving level received by the light receiving portion of the rider 30 is displayed. It may have an item. In this case, the control unit 15 sets the light receiving level of each point of the point cloud data output by the rider 30 and the item of "light receiving level" in the compression rate determination table 20 without converting the reflectance and the light receiving level. By comparing, it is possible to identify the target feature type.

(Modification 2)
The processing of the flowchart of FIG. 4 may be executed by a server device capable of data communication with the vehicle-mounted device 1. FIG. 6 shows an outline of the data compression system according to this modified example.

The data compression system shown in FIG. 6 includes a server device 4 that performs data communication with the vehicle-mounted device 1. Although only one on-board unit 1 is shown in FIG. 6, a plurality of on-board units 1 actually perform data communication with the server device 4. The server device 4 includes a compression rate determination table 20 and compression point cloud data 21. Then, the server device 4 receives the point cloud data output by the rider 30 from the vehicle-mounted device 1. In this case, the server device 4 executes steps S102 to S105 of the flowchart of FIG. 4 by referring to the compression rate determination table 20, and stores the compressed point cloud data as the compressed point cloud data 21.

In this case, the server device 4 further receives information such as the position of the vehicle, the traveling direction, and the installation angle of the rider 30 from the in-vehicle device 1, and based on these information, the point cloud data before or after compression is obtained. , The point cloud data represented by the absolute three-dimensional coordinates may be stored as the compressed point cloud data 21 by converting the relative three-dimensional coordinates with respect to the vehicle into the absolute three-dimensional coordinates. Instead, the server device 4 may receive the point cloud data converted into absolute three-dimensional coordinates from the vehicle-mounted device 1.

In another example, the processing of the flowchart of FIG. 4 may be executed by a control unit (ECU: Electronic Control Unit) of the vehicle instead of the vehicle-mounted device 1. In this case, the vehicle control unit electrically connects to various sensors including the rider 30 and executes the flowchart of FIG. 4 by referring to the compression rate determination table 20 stored in the predetermined storage unit. Then, the vehicle control unit generates the compression point cloud data 21 and stores it in the storage unit.

(Modification example 3)
The vehicle-mounted device 1 may compress and store the three-dimensional data generated based on the output of the camera 31 instead of storing the compressed point cloud data 21 in which the output of the rider 30 is compressed.

In this case, for example, the camera 31 is a three-dimensional measurement camera having a plurality of image pickup elements, and the control unit 15 generates three-dimensional data having RGB values based on the output of the camera 31. Then, the control unit 15 identifies the generated three-dimensional data for each feature by referring to the item of "RGB" in the compression rate determination table 20, and compresses each of the identified three-dimensional data with a different compression rate. .. Then, the control unit 15 stores the compressed three-dimensional data in the storage unit 12. As described above, even when the in-vehicle device 1 targets the three-dimensional data obtained from the output of the external sensor other than the rider 30, the compression processing is preferably performed by making the compression ratio different for each corresponding feature. It can be performed.

1 In-vehicle device 4 Server device 11 Communication unit 12 Storage unit 13 Sensor unit 14 Input unit 15 Control unit 16 Output unit 20 Compression rate determination table 21 Compression point cloud data

Claims (9)

Point cloud data that has a light emitting unit that emits light and a light receiving unit that receives the light, and is output by a measuring device that includes a feature in the measurement range, and can specify the light receiving level at which the light receiving unit receives the light. The acquisition unit that acquires the measurement data that is
A compression unit for compressing the measurement data is provided.
Based on the light receiving level , the compression unit lowers the compression rate of the first measurement data corresponding to a specific feature in the measurement data to be lower than the compression rate of the second measurement data other than the first measurement data. Data compression device. The data compression device according to claim 1, wherein the specific feature is a feature to be detected in automatic operation. The data compression device according to claim 1 or 2, wherein the compression unit compresses the first measurement data by lossless compression or does not perform compression. The emitting unit emits light while changing the emitting direction.
The data compression device according to any one of claims 1 to 3, wherein the compression unit identifies the first measurement data based on the light receiving level. Each feature is provided with a storage unit that stores setting information that associates information on the compression ratio with information on the reflectance of the feature or the light reception level of the light reflected by the feature.
The data compression device according to claim 4, wherein the compression unit refers to the setting information, identifies measurement data for each feature from the light receiving level, and determines the compression rate of each of the identified measurement data. .. The data compression device according to any one of claims 1 to 5, wherein the compression unit identifies the first measurement data based on the color information of each position indicated by the measurement data. It is a control method executed by the data compression device.
Point cloud data that has a light emitting unit that emits light and a light receiving unit that receives the light, and is output by a measuring device that includes a feature in the measurement range, and can specify the light receiving level at which the light receiving unit receives the light. The acquisition process to acquire the measurement data, which is
It has a compression step of compressing the measurement data.
In the compression step, the compression rate of the first measurement data corresponding to a specific feature in the measurement data is lower than the compression rate of the second measurement data other than the first measurement data based on the light receiving level. Control method to do. A program that a computer runs
Point cloud data that has a light emitting unit that emits light and a light receiving unit that receives the light, and is output by a measuring device that includes a feature in the measurement range, and can specify the light receiving level at which the light receiving unit receives the light. The acquisition unit that acquires the measurement data that is
The computer is made to function as a compression unit for compressing the measurement data.
Based on the light receiving level , the compression unit lowers the compression rate of the first measurement data corresponding to a specific feature in the measurement data to be lower than the compression rate of the second measurement data other than the first measurement data. Program to do. A storage medium that stores the program according to claim 8.

Images