WO2022180669A1

WO2022180669A1 - Information processing device, control method, program, and storage medium

Info

Publication number: WO2022180669A1
Application number: PCT/JP2021/006797
Authority: WO
Inventors: 健志幸田; 到竹村
Original assignee: パイオニア株式会社; パイオニアスマートセンシングイノベーションズ株式会社
Priority date: 2021-02-24
Filing date: 2021-02-24
Publication date: 2022-09-01

Abstract

A controller 13 of an information processing device 1 acquires measurement data from a writer 3, which is a measurement device. The controller 13 detects, in a frame, a region of interest that is measurement data for each measurement period from the writer 3. The controller 13 uses different compression modes to respectively compress first data D1, which is measurement data not belonging to the region of interest, and second data D2, which is measurement data belonging to the region of interest. The controller 13 transmits, to a data collection device 4, upload information Iu that includes the compressed first data D1 and second data D2.

Description

Information processing device, control method, program and storage medium

This disclosure relates to processing of measured data.

Conventionally, there has been known a laser radar device that irradiates a space to be detected with a pulse of laser light and detects an object in the space to be detected based on the level of the reflected light. For example, in Patent Document 1, by appropriately controlling the emission direction (scanning direction) of light pulses that are repeatedly emitted, the surrounding space is scanned, and by observing the return light, information about objects existing in the surroundings is obtained. A lidar is disclosed that generates point cloud data representing information such as distance, reflectance, and the like.

JP 2018-009831 A

When uploading point cloud data generated by a measurement device such as a lidar according to a predetermined scanning cycle and collecting and managing it by a server device, the volume of generated point cloud data is large, so communication load and processing load on the server device. etc. become excessively large. Therefore, it is necessary to reduce the overall data volume while suppressing a substantial decrease in the amount of information to be transmitted.

The present disclosure has been made in order to solve the above-described problems, and its main purpose is to provide an information processing device that can suitably reduce the amount of data to be uploaded.

The claimed invention is
Acquisition means for acquiring measurement data by the measuring device;
detection means for detecting a region of interest in a frame that is the measurement data for each measurement cycle by the measurement device;
compression means for compressing the first data, which is the measurement data that does not belong to the region of interest, and the second data, which is the measurement data that belongs to the region of interest, in different compression modes;
transmission means for transmitting the compressed first data and the second data to a data collection device;
It is an information processing device having

In addition, the invention described in the claims,
A computer-implemented control method comprising:
Acquiring measurement data from a measuring device,
detecting a region of interest in a frame that is the measurement data for each measurement cycle by the measurement device;
Compressing first data, which is the measurement data that does not belong to the region of interest, and second data, which is the measurement data that belongs to the region of interest, in different compression modes;
transmitting the compressed first data and second data to a data collection device;
control method.

In addition, the invention described in the claims,
Acquiring measurement data from a measuring device,
detecting a region of interest in a frame that is the measurement data for each measurement cycle by the measurement device;
Compressing first data, which is the measurement data that does not belong to the region of interest, and second data, which is the measurement data that belongs to the region of interest, in different compression modes;
A program that causes a computer to execute a process of transmitting the compressed first data and second data to a data collection device.

1 is a schematic configuration diagram of a data collection system; FIG. 1 is a block configuration diagram of an information processing device; FIG. 4 is a functional block diagram of a data processing unit; FIG. It is a figure which shows the measurement range of a rider. It is an example of the flowchart which shows the processing procedure of an information processing apparatus.

According to a preferred embodiment of the present invention, the information processing apparatus includes acquisition means for acquiring measurement data by a measurement device, and detection means for detecting a region of interest in a frame that is the measurement data for each measurement cycle by the measurement device. and compression means for compressing the first data, which is the measurement data that does not belong to the region of interest, and the second data, which is the measurement data that belongs to the region of interest, in different compression modes; and transmitting means for transmitting the data and the second data to a data collection device. According to this aspect, the information processing device changes the compression mode of the measurement data based on whether it belongs to the region of interest or not, thereby preventing the loss of highly important information and reducing the amount of data to be transmitted to the data collection device. can be effectively reduced.

In one aspect of the information processing apparatus, the compression means lossy-compresses the first data and losslessly-compresses the second data. According to this aspect, the information processing device can suitably reduce the amount of data to be transmitted to the data collection device while preventing the loss of the measurement data of the region of interest.

In another aspect of the information processing apparatus, the information processing apparatus further includes metadata adding means for adding metadata relating to detection of the region of interest to the compressed second data. According to this aspect, it is possible to suitably add useful information as metadata when using the second data after compression.

In another aspect of the information processing apparatus, the detection means determines detection conditions for the region of interest based on an application to be applied. According to this aspect, it is possible to set an important region as the region of interest for each application and accurately determine the compression aspect of the measurement data for each position to be measured.

In another aspect of the information processing device, the measurement device generates the measurement data including luminance information, and the detection means detects the region of interest based on the luminance. According to this aspect, the information processing device can suitably set the region of interest according to the brightness.

In another aspect of the information processing apparatus, the detection means detects a dynamic object in the frame and sets the region of interest based on the detection result of the dynamic object. According to this aspect, the information processing apparatus can preferably set the region of interest based on the detection result of the dynamic object.

In another aspect of the information processing apparatus, the measurement data includes luminance information and reflection intensity information, and the compressing means converts at least one of the first data and the second data into the luminance information and the reflection intensity information. The intensity information is compressed by different compression modes. Thereby, the information processing apparatus can appropriately change the compression mode of the luminance information and the reflection intensity information according to their importance.

According to another preferred embodiment of the present invention, there is provided a control method executed by a computer, in which measurement data obtained by a measuring device is acquired, and a region of interest is detected in a frame of the measurement data for each measurement cycle of the measuring device. The first data that is the measurement data that is detected and does not belong to the region of interest and the second data that is the measurement data that belongs to the region of interest are compressed in different compression modes, and the compressed first data and The second data is transmitted to a data collection device. By executing this control method, the computer can efficiently reduce the amount of data transmitted to the data collection device while preventing the loss of highly important information.

According to another preferred embodiment of the present invention, measurement data by a measuring device is acquired, a region of interest is detected in a frame that is the measurement data for each measurement cycle by the measuring device, and the region of interest that does not belong to the region of interest is detected. compressing the first data, which is measurement data, and the second data, which is the measurement data belonging to the region of interest, in different compression modes; and transmitting the compressed first data and second data to a data collection device It is a program that causes a computer to execute the process of sending. By executing this program, the computer can efficiently reduce the amount of data transmitted to the data collection device while preventing the loss of highly important information. Preferably, the program is stored in a storage medium.

Preferred embodiments of the present invention will be described below with reference to the drawings.

(1) Overview of Data Collection System FIG. 1 shows a schematic configuration of a data collection system according to this embodiment. The data collection system includes an information processing device 1 that processes data generated by a sensor group 2, and a data collection device 4 that is a server device that collects and manages data.

The information processing device 1 is electrically connected to the sensor group 2 and processes data output by various sensors included in the sensor group 2 . The sensor group 2 includes at least a lidar (Lidar: Light Detection and Ranging, or Laser Illuminated Detection and Ranging) 3 . Then, the information processing device 1 generates upload information “Iu” based on the data generated by the rider 3 and transmits the generated upload information Iu to the data collection device 4 . In this case, the information processing device 1 compresses the data for each measurement direction generated by the rider 3 by applying either reversible compression or irreversible compression according to the classification result of the data. As a result, the information processing device 1 generates the upload information Iu with a suitably reduced data amount.

The information processing device 1 may be an electronic control device of a measuring unit fixedly installed on a road or a parking lot, or may be a navigation device mounted on a moving body such as a vehicle or a ship. It may be an electronic control unit built in a moving body. Further, the information processing device 1 may be configured integrally with the rider 3 as an electronic control device for the rider 3 .

The lidar 3 discretely measures the distance to an object in the external world by emitting a pulsed laser while changing the angle within a predetermined angular range in the horizontal and vertical directions. In this case, the lidar 3 includes an irradiation unit that irradiates laser light while changing the irradiation direction (that is, the measurement direction), a light receiving unit that receives reflected light (scattered light) of the irradiated laser light, and light receiving output from the light receiving unit. and an output for outputting data based on the signal. The data measured by the lidar 3 for each irradiation direction in which the pulse laser is irradiated (the direction in which measurement is performed by the pulse laser and is also referred to as a “measurement point”) is the irradiation direction corresponding to the laser light received by the light receiving unit. and the response delay time of the laser beam specified based on the light receiving signal. Then, in one measurement (scanning) cycle, the lidar 3 converts the data corresponding to each measurement point in the measurement (scanning) range of the lidar 3 (that is, the irradiation range of the pulse laser) into one frame of point cloud data. Generate. Note that the point cloud data for each frame can be regarded as image data when each measurement point is a pixel position and the data for each measurement point is pixel data.

The rider 3 is an example of a "measurement device" in the present invention. Note that the lidar 3 is not limited to the above-described scan type lidar, and may be a flash type lidar that generates three-dimensional data by diffusing laser light into the field of view of a two-dimensional array sensor.

In addition to the rider 3, the sensor group 2 may include various external sensors and/or internal sensors. For example, the sensor group 2 may include a GNSS (Global Navigation Satellite System) receiver, an autonomous positioning device, etc. required for generating position information when provided in a mobile object.

The data collection device 4 is a device that collects measurement data from a rider, receives upload information Iu from the information processing device 1, and stores the received upload information Iu. Although only one set of the information processing device 1 and the sensor group 2 is illustrated in FIG. 1, there may be a plurality of sets of the information processing device 1 and the sensor group 2 instead. In this case, the data collection device 4 receives the upload information Iu from each information processing device 1 .

Here, a supplementary explanation will be given of the point cloud data of the rider 3 included in the upload information Iu. The point cloud data is included in the upload information Iu after being compressed by the information processing apparatus 1 . The point cloud data includes, for example, measurement position information, reflection intensity information, distance information, and noise floor information for each measurement point. The measurement position information is identification information (ID) that identifies a target measurement point (scanning point). The reflection intensity information is information on the reflection intensity of the irradiated laser beam (that is, the received light intensity of the reflected light). Specifically, the reflection intensity information represents the peak received light intensity of the reflected light of the irradiated laser beam. Note that the reflection intensity information may be information representing the reflectance of the irradiated object estimated from the measured reflection intensity. The distance information is information representing the distance to the object to be irradiated. The distance is calculated based on the time-of-flight specified by the light reception timing of the peak of the reflected light of the irradiated laser light. Note that the reflection intensity information and the distance information may be information representing a set of reflection intensity and distance corresponding to a plurality of peaks of reflected light. The noise floor information is information regarding the noise floor of the reflection intensity. Noise floor information represents, for example, the mean, variance, or/and other statistics of reflected intensities that are considered noise. The noise floor information is generated, for example, based on the reflection intensity that is not used for distance calculation (that is, other than the peak) among the reflection intensities in the reflected light receiving period, or the reflection intensity in the non-receiving period. Note that instead of the rider 3 generating these various types of information (measured position information, reflection intensity information, distance information, noise floor information, etc.), the information processing apparatus 1 generates these various types of information from the raw data of the rider 3. may

(2) Configuration of Information Processing Apparatus FIG. 2 is a block diagram showing an example of the hardware configuration of the information processing apparatus 1. As shown in FIG. The information processing device 1 mainly has an interface 11 , a memory 12 and a controller 13 . These elements are interconnected via bus lines.

The interface 11 performs interface operations related to data transfer between the information processing device 1 and an external device. In this embodiment, the interface 11 acquires output data from the sensor group 2 such as the rider 3 and supplies it to the controller 13 . The interface 11 also transmits the upload information Iu generated by the controller 13 to the data collection device 4 under the control of the controller 13 . In addition, when the information processing device 1 is mounted on a mobile object such as a vehicle, the interface 11 transmits a signal related to control of the mobile object generated by the controller 13 to an electronic control unit (ECU: Electronic Control Unit) of the mobile object. ). The interface 11 may be a wireless interface such as a network adapter for wireless communication, or a hardware interface for connecting with an external device via a cable or the like. Also, the interface 11 may perform interface operations with various peripheral devices such as an input device, a display device, and a sound output device.

The memory 12 is composed of various volatile and nonvolatile memories such as RAM (Random Access Memory), ROM (Read Only Memory), hard disk drive, and flash memory. The memory 12 stores a program for the controller 13 to execute predetermined processing. Note that the program executed by the controller 13 may be stored in a storage medium other than the memory 12 .

In addition, the memory 12 stores various information related to data compression processing executed by the controller 13 . For example, memory 12 has region of interest information I1. The region-of-interest information I1 is information about a region of interest (also referred to as a “region of interest”) within a frame of point cloud data. For example, the region-of-interest information I1 includes information about detection conditions for the region-of-interest for each application. The condition for detecting the region of interest depends on the application to be executed, and may be a condition based on brightness or a condition regarding the presence or absence of a dynamic object. A method of detecting the region of interest based on the region of interest information I1 will be described later.

The controller 13 includes one or more processors such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), and a TPU (Tensor Processing Unit), and controls the information processing apparatus 1 as a whole. In this case, the controller 13 executes various processes described later by executing programs stored in the memory 12 or the like.

The controller 13 also functionally has a data processing unit 14 and an upload unit 15 . The data processing unit 14 executes processing related to compression of point cloud data generated by the rider 3 . The upload unit 15 transmits the upload information Iu including the compressed data of the point cloud data generated by the data processing unit 14 to the data collection device 4 via the interface 11 . In this case, for example, the upload unit 15 transmits the compressed data of the point cloud data generated by the data processing unit 14 to the data collection device 4 in one or more measurement cycles (scanning cycles).

The controller 13 functions as "acquisition means", "detection means", "compression means", "transmission means", and a computer that executes programs.

It should be noted that the processing executed by the controller 13 is not limited to being realized by program-based software, and may be realized by any combination of hardware, firmware, and software. Also, the processing executed by the controller 13 may be implemented using a user-programmable integrated circuit such as an FPGA (Field-Programmable Gate Array) or a microcomputer. In this case, this integrated circuit may be used to implement the program executed by the controller 13 in this embodiment.

(3) Data Compression Process Next, the point cloud data compression process by the data processing unit 14 of the information processing apparatus 1 will be described. Schematically, the data processing unit 14 compresses the data of the measurement points belonging to the region of interest among the frames of the point cloud data obtained by the measurement for one cycle by lossless compression, and compresses the data of the measurement points not belonging to the region of interest. is compressed by lossy compression. As a result, the data processing unit 14 generates compressed data for the necessary area while maintaining sufficient accuracy, generates compressed data for the less important area at a high compression ratio, and generates data for the upload information Iu. Preferably reduce capacity.

FIG. 3 is an example of functional blocks of the data processing unit 14. FIG. The data processing unit 14 functionally includes a region-of-interest detection unit 41 , an irreversible compression unit 42 , a reversible compression unit 43 , a metadata addition unit 44 , and a data integration unit 45 . In FIG. 3, the blocks that exchange data are connected by solid lines, but the combinations of blocks that exchange data are not limited to those shown in FIG.

The region-of-interest detection unit 41 acquires the point cloud data generated by the rider 3 via the interface 11, and detects the region of interest in the frame of the point cloud data specified for each measurement cycle. In this case, the region-of-interest detection unit 41 refers to the region-of-interest information I1 to recognize the region-of-interest detection condition according to the application to be executed, and detects a region (for example, a rectangular region) in the frame that satisfies the detection condition. , is detected as the region of interest. The detection method of the region of interest may be any method such as object detection (recognition) based on point cloud data, image recognition, and estimation based on luminance value distribution. This will be described later with reference to (B). Note that the region-of-interest detection unit 41 acquires information about the application that is the use of the point cloud data from the data collection device 4 or another processing block in the controller 13, and based on the information about the acquired application, A detection condition for the region of interest may be determined. In this case, the region-of-interest detection conditions are recorded in the region-of-interest information I1 in association with each application. Select conditions.

Then, the region-of-interest detection unit 41 supplies the data corresponding to the measurement points that do not belong to the region of interest (also referred to as “first data D1”) to the irreversible compression unit 42, and the data corresponding to the measurement points that belong to the region of interest. Data (also referred to as “second data D2”) is supplied to the lossless compression section 43 . The region-of-interest detection unit 41 also supplies information (also referred to as “detection information I2”) regarding the detection of the region of interest to the metadata provision unit 44 . Here, the detection information I2 is information generated in the detection of the region of interest. , information on detection accuracy, etc.).

The irreversible compression unit 42 performs irreversible compression on the first data D1 supplied from the region of interest detection unit 41 . Here, the first data D1 is data corresponding to measurement points that do not belong to the region of interest, and is data of low importance in the application to be executed. The irreversible compression method executed by the irreversible compression unit 42 may be any method. Further, when a compression mode such as a compression ratio or a compression algorithm is defined in the region of interest information I1 or the like, the lossy compression unit 42 compresses the first data D1 according to the compression mode defined in the region of interest information I1 or the like. Perform lossy compression. Then, the irreversible compression unit 42 supplies data obtained by irreversibly compressing the first data D1 (also referred to as “irreversible compressed data Da1”) to the data integration unit 45 .

Here, the irreversible compression unit 42 may change the compression rate for each frame. For example, the irreversible compression unit 42 may increase the compression rate as the region of interest in the frame becomes smaller (that is, as the number of measurement points corresponding to the first data D1 for each frame increases). In this case, for example, when the second data D2 does not exist and the first data D1 is the entire frame, the irreversible compression unit 42 maximizes the compression rate and reduces the data amount of the irreversible compressed data Da1 to zero. (that is, the irreversible compressed data Da1 is not generated).

The reversible compression section 43 performs reversible compression on the second data D2 supplied from the region of interest detection section 41 . Here, the second data D2 is data corresponding to the measurement points belonging to the region of interest, and is data of high importance in the application to be executed. The lossless compression method executed by the lossless compression unit 43 may be any method. Moreover, when the compression mode is defined in the region of interest information I1 or the like, the reversible compression unit 43 performs lossless compression of the second data D2 according to the compression mode defined in the region of interest information I1. Then, the irreversible compression unit 42 supplies data obtained by reversibly compressing the second data D2 (also referred to as “reversible compressed data Da2”) to the metadata adding unit 44 .

The metadata addition unit 44 adds the detection information I2 supplied from the region of interest detection unit 41 as metadata to the lossless compressed data Da2 generated by the lossless compression unit 43 . Then, the metadata adding unit 44 supplies the second compressed data “Db2”, which is the reversible compressed data Da2 to which the metadata is added, to the data integrating unit 45 .

The data integration unit 45 integrates the irreversible compressed data Da1 generated by the irreversible compression unit 42 and the reversible compressed data Db2 generated by the metadata adding unit 44 for each frame (also referred to as “integrated data Du”). ). Then, the data integration unit 45 supplies the integrated data Du integrated for each frame to the upload unit 15 . After that, the upload unit 15 transmits the upload information Iu including one or more integrated data Du to the data collection device 4 . After receiving the upload information Iu, the data collection device 4 stores the upload information Iu. Then, the data collection device 4 decompresses the lossy-compressed data Da1 and reversible-compressed data Db2 of the integrated data Du included in the received upload information Iu, and uses the decompressed data for a predetermined application.

Next, a specific example of detection processing of the region of interest by the region of interest detection unit 41 will be described. 4A and 4B are diagrams showing the measurement range of the rider 3. FIG. In FIGS. 4A and 4B, the region of interest detected by the region-of-interest detection unit 41 is highlighted by a dashed frame and hatching.

In the example of FIG. 4A, the region-of-interest detection unit 41 determines the region of interest based on the brightness measured at each measurement point. Specifically, the region-of-interest detection unit 41 identifies a measurement point whose brightness is higher than a threshold pre-recorded in the region-of-interest information I1 or the like, and sets the region of interest based on the identified measurement point. In this case, for example, the region-of-interest detection unit 41 sets the smallest rectangular region including measurement points whose brightness is greater than the threshold as the region of interest. On the other hand, the region-of-interest detection unit 41 regards the region of the frame other than the rectangular region described above as not the region of interest.

According to the example of FIG. 4A, the region-of-interest detection unit 41 sets a region in which an object such as a road surface and features around the road exists as a region of interest, and there is no loss of information in the compression process. can be subject to lossless compression as follows: On the other hand, the region-of-interest detection unit 41 excludes regions of low brightness and no object from the region of interest, and increases the compression rate in the compression process to suitably reduce the amount of data. As described above, according to the example of FIG. 4A, efficient compression of the amount of data transmission can be performed without missing important information.

In the example of FIG. 4B, the region-of-interest detection unit 41 detects a dynamic object region by detecting changes in point cloud data between frames, and based on the detected dynamic object region. Set a region of interest. In this case, for example, the region-of-interest detection unit 41 sets the smallest rectangular region (so-called bounding box) including the region of the dynamic object as the region of interest. In this case, the region-of-interest detection unit 41 may detect the above-described dynamic object region using an arbitrary technique for detecting a dynamic object region based on time-series image data. On the other hand, the region-of-interest detection unit 41 regards the region of the frame other than the rectangular region described above as not the region of interest.

According to the example of FIG. 4B, the region-of-interest detection unit 41 sets the region in which the dynamic object exists as the region of interest when the information of the dynamic object is important in the applied application, and performs the compression processing. can be subjected to lossless compression so that there is no loss of information in On the other hand, in this case, the region-of-interest detection unit 41 can exclude regions in which no dynamic object exists from the region of interest, increase the compression rate in the compression process, and suitably reduce the amount of data. Thus, also in the example of FIG. 4B, efficient compression of the amount of data transmission can be performed without missing important information.

The setting example of the region of interest is not limited to the examples of FIGS. 4A and 4B, and the region of interest may be set according to various conditions depending on the application using the point cloud data. For example, when the region-of-interest information I1 or the like specifies that a specific type of object (including a moving object) is to be detected, the region-of-interest detection unit 41 detects the specified type of object. , the region of interest may be set based on the detection result. In this case, the defined type of object is, for example, a pedestrian, a forward vehicle, a specific feature (including a white line, a sign, etc.), or a combination thereof. In this case, the region-of-interest detection unit 41 may detect a region of a specific type of object, for example, based on any trained reasoner based on semantic segmentation, instance segmentation, or the like. The reasoner described above is, for example, a learning model trained to output a region classification result for each pixel (measurement point) when one or a predetermined number of frames are input.

(4) Processing Flow FIG. 5 is an example of a flow chart showing processing procedures in this embodiment. The information processing device 1 repeatedly executes the processing of the flowchart of FIG.

First, the data processing unit 14 of the information processing device 1 acquires point cloud data for each frame generated by the rider 3 via the interface 11 (step S11). Then, the data processing unit 14 detects a region of interest based on the point cloud data acquired in step S11 (step S12). In this case, for example, the data processing unit 14 refers to the region-of-interest information I1 and detects the region of interest in the target frame based on the region-of-interest detection conditions according to the application to be applied.

Then, the data processing unit 14 determines whether or not a region of interest exists in the target frame (step S13). Then, if a region of interest exists in the target frame (step S13; Yes), the data processing unit 14 losslessly compresses the second data D2, which is data of measurement points belonging to the region of interest, and removes the data from the region of interest. The first data D1, which is the data of the measuring point to which it belongs, is irreversibly compressed (step S14). As a result, the data processing unit 14 converts the first data D1 into lossy-compressed data Da1, and converts the second data D2 into lossless-compressed data Da2. In this case, the data processing unit 14 efficiently compresses the data of the measurement points belonging to the region of interest by losslessly compressing the data of the measurement points belonging to the region of interest to suitably suppress the loss of information. quantity can be reduced.

Then, the data processing unit 14 adds detection information I2 relating to the detection of the region of interest as metadata to the losslessly compressed data Da2 generated in step S14 (step S15). Thereby, the data processing unit 14 generates lossless compression data Db2.

On the other hand, if the region of interest does not exist in the target frame in step S13 (step S13; No), the data processing unit 14 irreversibly compresses all the data in the target frame (step S17). Thereby, the data processing unit 14 generates the irreversible compressed data Da1. In step S17, the data processing unit 14 does not have to generate the irreversible compressed data Da1, which is the data to be transmitted to the data collecting device 4. FIG. This case corresponds to maximizing the compression ratio.

Then, the upload unit 15 transmits the upload information Iu to the data collection device 4 via the interface 11 (step S16). In this case, the upload information Iu includes integrated data Du obtained by integrating the lossy-compressed data Da1 generated in step S14 and the lossless-compressed data Db2 generated in step S15, or the lossy-compressed data generated in step S17. Da1 is included.

As described above, the controller 13 of the information processing device 1 according to this embodiment acquires measurement data from the rider 3, which is a measurement device. Then, the controller 13 detects the region of interest in the frames that are measurement data for each measurement cycle by the lidar 3 . Then, the controller 13 compresses the first data D1, which is measurement data that does not belong to the region of interest, and the second data D2, which is measurement data that belongs to the region of interest, in different compression modes. The controller 13 then transmits the upload information Iu including the compressed first data D1 and second data D2 to the data collecting device 4 . As a result, the information processing device 1 can suitably reduce the amount of data to be transmitted to the data collecting device 4 while suitably ensuring the accuracy of important measurement data.

(6) Modification A modification suitable for the above embodiment will be described. The following modifications may be combined and applied to the above embodiment.

(Modification 1)
The information processing device 1 may generate and transmit the upload information Iu based on the measurement result of an external sensor other than the rider 3 that measures the distance. Even in this case, the information processing apparatus 1 regards the data measured by the external sensor in one measurement cycle as one frame, detects the region of interest in the frame, and reversibly converts the data belonging to the region of interest. Compress and lossy compress data that falls outside the region of interest. This makes it possible to suitably reduce the amount of data to be uploaded while preventing the loss of important data.

(Modification 2)
The information processing device 1 may compress the distance information and the reflection intensity information in different compression modes. For example, in the case of the first data D1 belonging to the outside of the region of interest, the information processing device 1 increases the compression ratio in lossy compression of the reflection intensity information rather than the distance information. In another example, in the case of the second data D2 belonging to the region of interest, the information processing apparatus 1 losslessly compresses only the distance information, and lossy compresses the reflection intensity information. According to these examples, the information processing apparatus 1 can perform compression processing by prioritizing the accuracy of the distance information over the accuracy of the reflection intensity information.

It should be noted that, in the above-described embodiments, the program can be stored using various types of non-transitory computer readable media and supplied to a controller or the like that is a computer. Non-transitory computer readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic storage media (e.g., floppy disks, magnetic tapes, hard disk drives), magneto-optical storage media (e.g., magneto-optical discs), CD-ROMs (Read Only Memory), CD-Rs, CD-R/W, semiconductor memory (eg mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory)).

Although the present invention has been described with reference to the examples, the present invention is not limited to the above examples. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention. That is, the present invention naturally includes various variations and modifications that a person skilled in the art can make according to the entire disclosure including the scope of claims and technical ideas. In addition, the disclosures of the cited patent documents and the like are incorporated herein by reference.

REFERENCE SIGNS LIST 1 information processing device 2 sensor group 3 lidar 4 data collection device

Claims

Acquisition means for acquiring measurement data by the measuring device;
detection means for detecting a region of interest in a frame that is the measurement data for each measurement cycle by the measurement device;
compression means for compressing the first data, which is the measurement data that does not belong to the region of interest, and the second data, which is the measurement data that belongs to the region of interest, in different compression modes;
transmission means for transmitting the compressed first data and the second data to a data collection device;
Information processing device having
The information processing apparatus according to claim 1, wherein said compression means lossy-compresses said first data and losslessly-compresses said second data.
The information processing apparatus according to claim 1 or 2, further comprising metadata adding means for adding metadata relating to detection of the region of interest to the compressed second data.
The information processing apparatus according to any one of claims 1 to 3, wherein the detection means determines detection conditions for the region of interest based on an application to be applied.
The measurement device generates the measurement data including luminance information,
5. The information processing apparatus according to claim 1, wherein said detection means detects said region of interest based on luminance.
The information processing apparatus according to any one of claims 1 to 4, wherein said detection means detects a dynamic object in said frame and sets said region of interest based on a detection result of said dynamic object.
The measurement data includes luminance information and reflection intensity information,
The information according to any one of claims 1 to 6, wherein said compression means compresses said luminance information and said reflection intensity information in at least one of said first data and said second data in different compression modes. processing equipment.
A computer-implemented control method comprising:
Acquiring measurement data from a measuring device,
detecting a region of interest in a frame that is the measurement data for each measurement cycle by the measurement device;
Compressing first data, which is the measurement data that does not belong to the region of interest, and second data, which is the measurement data that belongs to the region of interest, in different compression modes;
transmitting the compressed first data and second data to a data collection device;
control method.
Acquiring measurement data from a measuring device,
detecting a region of interest in a frame that is the measurement data for each measurement cycle by the measurement device;
Compressing first data, which is the measurement data that does not belong to the region of interest, and second data, which is the measurement data that belongs to the region of interest, in different compression modes;
A program that causes a computer to execute a process of transmitting the compressed first data and second data to a data collection device.
A storage medium storing the program according to claim 9.