KR20220112095A - Object tracking apparatus, object tracking, recording medium recording program performing the same - Google Patents

Abstract

An object tracking apparatus includes: a sensor unit acquiring information on a 3D space based on light received as a response to emitting light into the 3D space; a memory storing one or more commands; and a processor. The processor identifies objects in the 3D space from the acquired information on the 3D space by executing the one or more commands, classifies the identified objects into a plurality of groups based on reflexibility of the received light, and tracks an object of a group selected among the plurality of groups.

Description

Object tracking device, object tracking method, and recording medium recording the program performing the same

It relates to an object tracking apparatus, an object tracking method, and a recording medium recording a program for performing the same.

With the development of sensing technology such as LiDAR (Light Detection And Ranging, LiDAR) technology, advanced control functions in which sensing technology is grafted are recently appearing in various industrial technology fields. As the commercialization of autonomous vehicles approaches, lidar technology is also developing rapidly.

LiDAR is a technology that emits light to an object in a 3D space and then receives the reflected light, and obtains information about the 3D space therefrom. Lidar cannot perceive color like a camera image sensor, but it can detect distant objects and has excellent spatial resolution.

To provide an object tracking apparatus, an object tracking method, and a recording medium recording a program for performing the object tracking method, and an object tracking method used to track an object by classifying spatial information obtained using a sensor into a plurality of groups based on the reflectance of light.

An object tracking method according to a first aspect includes: acquiring information about a three-dimensional space based on light received in response to emitting light in the three-dimensional space; identifying objects in the 3D space from the obtained 3D space information; classifying the identified objects into a plurality of groups based on the reflectance of the received light; and tracking an object of a selected group from among the plurality of groups, wherein the plurality of groups correspond to a first group corresponding to an object having a tag including a retroreflective material and an object not having the tag a second group.

A computer-readable recording medium recording a program for execution by a computer according to the second aspect is an instruction for obtaining information about a three-dimensional space based on light received in response to emitting light in the three-dimensional space field; instructions for identifying objects in the three-dimensional space from the obtained information on the three-dimensional space; instructions for classifying the identified objects into a plurality of groups based on the reflectance of the received light; and instructions for tracking an object of a selected group from among the plurality of groups, wherein the plurality of groups correspond to a first group corresponding to an object having a tag including a retroreflective material and an object not having the tag a second group.

An object tracking apparatus according to a third aspect includes: a sensor unit configured to obtain information on a three-dimensional space based on light received in response to light emission in the three-dimensional space; a memory storing one or more instructions; and by executing the one or more instructions, identify objects in the three-dimensional space from the obtained information on the three-dimensional space, and classify the identified objects into a plurality of groups based on the reflectance of the received light; , a processor for tracking an object of a selected group from among the plurality of groups, wherein the plurality of groups correspond to a first group corresponding to an object having a tag including a retroreflective material and an object not having the tag a second group.

1 is a diagram for explaining a first environment in which an object tracking device is used.
2 is a diagram for explaining a second environment in which an object tracking device is used.
3 is a diagram for explaining the configuration and operation of an object tracking apparatus according to an embodiment.
4 is a diagram for explaining the configuration and operation of a server according to an embodiment.
5 is a flowchart illustrating an object tracking method according to an embodiment.
6 is a flowchart illustrating an object tracking method according to another embodiment.
7 is a detailed flowchart illustrating a process for tracking an identified object.

Hereinafter, various embodiments will be described in detail with reference to the drawings. In order to more clearly describe the features of the embodiments, detailed descriptions of matters widely known to those of ordinary skill in the art to which the following embodiments belong will be omitted.

On the other hand, in the present specification, when a component is "connected" with another component, it includes not only a case of 'directly connected' but also a case of 'connected with another component interposed therebetween'. In addition, when a component "includes" another component, it means that other components may be further included, rather than excluding other components, unless otherwise stated.

Also, terms including an ordinal number such as 'first' or 'second' used in this specification may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another.

The present embodiments relate to an object tracking apparatus, an object tracking method, and a recording medium recording a program for performing the same, and detailed descriptions are given for matters widely known to those of ordinary skill in the art to which the following embodiments belong. omit

1 is a view for explaining a first environment in which the object tracking apparatus 100 is used.

The object tracking apparatus 100 is a sensing device capable of acquiring spatial information and may include at least one sensor. The object tracking apparatus 100 may emit light in the 3D space, and in response thereto may acquire information on the 3D space based on the received light. The object tracking apparatus 100 may be located indoors or outdoors, in a place capable of detecting a space corresponding to the ROI or as wide as possible. For example, as shown in FIG. 1 , in the case of an electronic product retailer, the object tracking apparatus 100 may be installed in the center of the ceiling of an indoor space in which electronic products are displayed.

The object tracking apparatus 100 may include a light detection and ranging sensor, and, if necessary, may further include various types of sensors such as a radar sensor, an infrared image sensor, an ultrasonic sensor, and the like. . The object tracking apparatus 100 uses a plurality of sensors of the same type or different It is also possible to use a combination of the sensors of

The lidar sensor cannot detect the color of objects in 3D space, but can detect the shape, size, and position. In other words, although the lidar sensor cannot detect the color or texture of an object, it can check the approximate shape and size of an object from a relatively long distance, so it is free from problems such as invasion of privacy and can utilize the approximate shape and size of the object. suitable for the field For example, the lidar sensor may be used in fields such as autonomous driving and traffic flow tracking.

If such a lidar sensor is used to track a moving object such as a person, it is possible to analyze a movement pattern or behavior, thereby increasing the efficiency of operation or solving a safety problem by monitoring a person such as a worker. However, as described above, although the approximate shape, size, and position of the object can be confirmed, the color cannot be confirmed. Therefore, if it is necessary to distinguish objects with similar appearances, measures are required. Hereinafter, a technique for distinguishing and tracking objects having similar appearances using a tag coated with a retroreflective material will be described.

Referring to FIG. 1 , a situation in which several people are present at an electronic product store may be identified. In order to sell more products and provide better service to customers through optimal advertisement and product placement, the manager of an electronic product store determines how customers move, what products they spend a lot of time in, and the number of customers. They need to know what products they have seen, etc. At this time, since the employee of the electronic product store is not a customer, it should be able to be excluded from the object to be tracked. In the case of LiDAR, there is no problem of invasion of customer privacy, but since it is difficult to distinguish non-customer employees from customers, separate measures are required.

A customer is a non-cooperating entity that is not obligated to follow a manager's instructions, whereas an employee is a collaborating entity that follows the manager's instructions. In order to distinguish between the two types of objects with the lidar sensor, a tag that can be detected by the lidar sensor may be attached to an employee who is a collaborating object. A tag is a predetermined material that can be distinguished and detected by a lidar sensor, for example, a name plate, a badge, a label, a string, clothing, and a hat coated with a retroreflective material. It may be in one form, but is not limited thereto.

A lidar sensor emits light and receives reflected light, in general, the distance to an object and the intensity of the received light have a quadratic relationship. On the other hand, since the retroreflective material reflects the light emitted from the LIDAR sensor to the LIDAR sensor as it is regardless of the incident angle, the distance to the object and the intensity of the received light have a linear relationship. Therefore, when a tagged collaborating object (employee) and an untagged non-cooperating object (customer) with a retroreflective material applied thereto are detected using lidar, the intensities of the light reflected by the tag are different, in other words, the reception Since the reflectance of the emitted light is different, the tag can serve as a marker that can distinguish between a cooperative object and a non-cooperative object.

Referring to FIG. 1 , it can be seen that two of five employees in an electronic product store are attaching a tag in the form of a name plate, badge, or label to their body. The object tracking apparatus 100 may obtain information on a three-dimensional space in an electronic product store by using a lidar sensor. The object tracking apparatus 100 clusters the information on the three-dimensional space obtained by using the lidar sensor for each object, and then removes the object information including the light reflected by the tag, so that the non-cooperative object corresponding to the customer of object information can be obtained. In this way, if the object information of the non-cooperating object is used in the 3D space information obtained through the lidar sensor, the object information of the cooperative object is removed, the pattern or behavior of the customer's movement is accurately analyzed without noise. This can serve as a basis for preparing a plan to increase the efficiency of the operation of electronic product stores.

2 is a diagram for explaining a second environment in which the object tracking apparatus 100 is used.

FIG. 2 is an example for explaining an example in which object information of a cooperation object should be utilized, unlike the first environment of FIG. 1 . In an environment such as a construction site, it is important to monitor people such as workers for safety. To this end, construction workers following the instructions of the construction site manager may wear a hat, helmet, vest, outerwear, shoes, etc. as a cooperative object, a tag coated with a retroreflective material.

Referring to FIG. 2 , it can be seen that five workers at the construction site are wearing helmets, vests, and tops coated with retroreflective materials. The object tracking apparatus 100 may obtain information about a three-dimensional space of a construction site by using a lidar sensor. The object tracking apparatus 100 clusters the information on the three-dimensional space obtained by using the lidar sensor for each object, and then selects object information including the light reflected by the tag, thereby cooperating corresponding to the construction site workers. It is possible to obtain object information of an object. In this way, by utilizing the object information of the cooperative object among the information about the three-dimensional space obtained through the lidar sensor, the movement or behavior of the workers can be monitored, so that the safety problem of the workers can be solved. For example, when the operator moves to a dangerous place or the movement of the operator is monitored in a place other than an area where the movement is expected, a warning broadcast may be broadcast or the situation may be notified to the manager's terminal.

3 is a diagram for explaining the configuration and operation of the object tracking apparatus 100 according to an embodiment.

Referring to FIG. 3 , the object tracking apparatus 100 according to an embodiment may include a memory 110 , a processor 120 , a sensor unit 130 , and a communication interface device 140 . Those of ordinary skill in the art related to the present embodiment can see that other general-purpose components other than those shown in FIG. 3 may be further included.

The memory 110 may store software and/or programs. The memory 110 may store instructions executable by the processor 120 .

The processor 120 may access and use data stored in the memory 110 , or store new data in the memory 110 . The processor 120 may execute instructions stored in the memory 110 . The processor 120 may execute a computer program installed in the object tracking device 100 . In addition, the processor 120 may store and execute a computer program or application received from the outside in the memory 110 . The processor 120 may include at least one processing module. For example, the processor 120 may include a processing module executing an object tracking program for tracking an object in a three-dimensional space in the form of a dedicated processing module. The processor 120 may control other components included in the object tracking apparatus 100 to perform an operation corresponding to an execution result such as an instruction or a computer program.

The sensor unit 130 may include at least one sensor for sensing a 3D space. The sensor unit 130 may include a light emitting unit that emits light in a three-dimensional space and a light receiving unit that receives light, and a dedicated processing module for obtaining information about the three-dimensional space based on the intensity of the light received by the light receiving unit. may include more. The sensor unit 130 may acquire shape data or distance data for an object located within a detection range.

The sensor unit 130 may be a LiDAR (Light Detection and Ranging) sensor, and may acquire data for a 360-degree space including at least one 3D LiDAR sensor. The sensor unit 130 may further include various types of sensors, such as a radar sensor, an infrared image sensor, and an ultrasonic sensor, depending on the environment. For example, the sensor unit 130 may further include at least one of a radar sensor and an ultrasonic sensor to receive data on a blind area that cannot be detected by the lidar sensor or a proximity space within a predetermined distance from the object tracking apparatus 100 . can be obtained

The communication interface device 140 may perform wired/wireless communication with other devices or networks. To this end, the communication interface device 140 may include a communication module supporting at least one of various wired and wireless communication methods. For example, a communication module that performs short-distance communication such as RFID (Radio Frequency Identification), NFC (Near Field Communication), Bluetooth, various types of wireless communication, or wired communication using a coaxial cable or optical cable, etc. may be included. have. The communication interface device 140 may be connected to a device located outside the object tracking device 100 to transmit/receive signals or data. The object tracking device 100 may communicate with a terminal device of a manager through the communication interface device 140 or may be connected to a server that manages an area in which the object tracking device 100 is located.

An example of the processor 120 according to the above configuration executes one or more instructions stored in the memory 110 , so that objects in the three-dimensional space can be identified from the information on the three-dimensional space obtained from the sensor unit 130 . have. The processor 120 may cluster the obtained 3D space information and identify different objects using an object classification model. Each of the identified objects may be tagged with different object identification information to be distinguished from each other. Furthermore, when the tag is identified, the processor 120 may further classify and identify the identified objects based on at least one of a type, shape, and number of tags among the identified objects.

The processor 120 may classify the identified objects into a plurality of groups based on the reflectance of the received light. Even if the light emitting unit of the sensor unit 130 uniformly emits a predetermined light in a three-dimensional space, the light receiving unit of the sensor unit 130 may receive light having different reflectivities from objects. The reflectance of the light may vary depending on the property of the surface of the object, and the processor 120 may distinguish light having a reflectance greater than or equal to a predetermined reference based on the intensity of the received light. The plurality of groups may include a first group corresponding to an object having a tag including a retroreflective material and a second group corresponding to an object having no tag. The first group may correspond to an object that reflects light having a reflectance greater than or equal to a predetermined standard by the tag, and the second group may correspond to an object that reflects light having only a reflectance lower than a predetermined reference.

Each of the groups classified as described above may be tagged with different group identification information to be distinguished from each other. Accordingly, a plurality of groups to which different group identification information is tagged may be categorized, and information on the 3D space of some groups may be filtered during data analysis. Alternatively, group identification information may be tagged only for some groups. Accordingly, information on the 3D space of the group to which the group identification information is tagged may be filtered, or information on the 3D space of the group excluding the group to which the group identification information is tagged among a plurality of groups may be filtered.

By having group identification information and object identification information, each object can be classified as an object having a tag to which a retroreflective material is applied, by group identification information, and by object identification information, with other objects in the same group can be distinguished.

The processor 120 may track an object of a selected group among a plurality of groups. At least one group from among the plurality of groups may be selected. For example, when classified into the first group and the second group, the first group may be selected, the second group may be selected, or both the first group and the second group may be selected. Information on the group to be selected may be preset or may be set according to an external input through the communication interface device 140 or the user interface device (not shown). The processor 120 may accumulate location information of an object of a selected group from among a plurality of groups, track a movement of the identified object, and analyze a movement pattern of the identified object based on the tracked movement.

The processor 120 of another example according to the above configuration executes one or more instructions stored in the memory 110 , thereby receiving information on the 3D space obtained from the sensor unit 130 in a plurality of groups based on the reflectance of the received light. can be classified into After clustering the information on the 3D space for each object, the processor 120 may find light having a reflectance greater than or equal to a predetermined reference. For example, the plurality of groups may include a first group corresponding to an object having a tag including a retroreflective material and a second group corresponding to an object having no tag. The first group may correspond to an object that reflects light having a reflectance greater than or equal to a predetermined standard by the tag, and the second group may correspond to an object that reflects light having only a reflectance lower than a predetermined reference.

Each of the groups classified as described above may be tagged with different group identification information to be distinguished from each other.

The processor 120 may identify an object in the 3D space by using information on the 3D space of the selected group from among the plurality of groups. At least one group may be selected from among the plurality of groups, and information on the group to be selected may be preset or set according to an external input through the communication interface device 140 or the user interface device (not shown). can The processor 120 may use information about the 3D space of at least one group among the plurality of groups. For example, when classified into the first group and the second group, an object in the 3D space is identified using information on the 3D space tagged as the first group, or an object in the 3D space tagged as the second group is identified. An object in a three-dimensional space can be identified using the information about the object. Alternatively, an object in a 3D space may be identified for both the first group and the second group.

When an object in the 3D space is identified using the information on the 3D space tagged as the second group, the object classification model may be used to classify and identify different objects. On the other hand, when identifying an object in a 3D space using information about the 3D space tagged as the first group, the type, shape, and number of tags including retroreflective materials as well as a method using an object classification model Based on at least one of the objects, different objects may be distinguished and identified.

Each of the identified objects may be tagged with different object identification information to be distinguished from each other. By having group identification information and object identification information, each object can be classified as an object having a tag to which a retroreflective material is applied, by group identification information, and by object identification information, with other objects in the same group can be distinguished.

The processor 120 may track the identified object. The processor 120 may track the sensed 3D space including the identified at least one object. The processor 120 may track the three-dimensional space by determining attribute information of at least one of a type, a three-dimensional shape, a position, a posture, a size, a trajectory, and a speed of at least one identified object in the sensed three-dimensional space. have. The processor 120 may accumulate location information of the identified object, track the movement of the identified object, and analyze a movement pattern of the identified object based on the tracked movement.

On the other hand, when the tag is not detected despite the object having the tag, for example, when the tag is not detected because the tag is hidden or the density of the 3D space information obtained from the sensor unit 130 is low, the processor 120 classifies the obtained 3D space information into a second group, and provides second group identification information corresponding to the second group. Thereafter, from the time when the tag is recognized, the processor 120 classifies the information on the 3D space corresponding to the object having the recognized tag into the first group again, and divides the second group identification information into the first group. It can be updated with the first group identification information.

On the other hand, when the tag includes an electronic tag chip, the processor 120 recognizes a tag within a predetermined distance from the object tracking device 100 through short-distance communication using the communication interface device 140 and recognizes the recognized tag. Information on a 3D space corresponding to an object having a tag may be classified into a first group. For example, if the tag is an 'RFID tag' coated with a retroreflective material, even if the sensor unit 130 does not detect the tag, the processor 120 performs the communication interface device 140 including the RFID communication module. tags can be recognized. The processor 120 may classify information on a 3D space corresponding to an object having a recognized tag into a first group, and may provide first group identification information corresponding to the first group.

Meanwhile, the processor 120 may transmit information related to the tracked 3D space to the outside through the communication interface device 140 .

4 is a diagram for explaining the configuration and operation of the server 200 according to an embodiment. The server 200 may be replaced by a computing device, an operator, a console device, or the like.

As described above, the object tracking device 100 identifies and classifies objects in a three-dimensional space into a plurality of groups using information about the three-dimensional space, and is in the form of an embedded device equipped with a processor for tracking the identified objects. However, the present invention is not limited thereto. The object tracking apparatus 100 transmits the acquired information on the 3D space to the server 200 that provides the object tracking service, and uses the information on the 3D space to identify an object in the 3D space and a plurality of groups A series of processing classified as can be processed by the server 200 . Since the data for the three-dimensional space obtained by the object tracking device 100 is anonymized, there is no privacy infringement problem even if it is transmitted to the server 200 and processed.

The server 200 may be implemented with a technology such as cloud computing. The server 200 may perform high-speed data communication with the object tracking apparatus 100 .

Referring to FIG. 4 , the server 200 may include a memory 210 , a processor 220 , and a communication interface device 230 . Those of ordinary skill in the art related to the present embodiment can see that other general-purpose components other than the components shown in FIG. 4 may be further included. Previously, the description of the object tracking apparatus 100 may be applied to the configuration of the server 200 with the same name, even if omitted below.

Each component of the block diagram of FIG. 4 may be separated, added, or omitted according to an implementation method of the server 200 . That is, one component may be subdivided into two or more components, two or more components may be combined into one component, and some components may be further added or removed depending on the implementation method.

The memory 210 may store instructions executable by the processor 220 . The memory 210 may store software or a program.

The processor 220 may execute instructions stored in the memory 210 . The processor 220 may perform overall control of the server 200 . The processor 220 may obtain information and a request received through the communication interface device 230 , and store the received information in a storage (not shown). In addition, the processor 220 may process the received information. For example, the processor 220 obtains information used for object tracking from information received from the object tracking device 100 or performs a processing operation for managing the received information to be stored in storage (not shown). can In addition, the processor 220 provides an object tracking service to the manager's terminal through the communication interface device 230 using data or information stored in storage (not shown) as a response to the request obtained from the manager's terminal. Information to provide can be transmitted.

The communication interface device 230 may perform wired/wireless communication with other devices or networks. The communication interface device 230 may be connected to a device located outside the server 200 to transmit/receive signals or data. The server 200 may communicate with the object tracking device 100 through the communication interface device 230 or may be connected to another server connected through a network. For example, the server 200 may obtain data on the 3D space from the object tracking device 100 through the communication interface device 230 .

The storage (not shown) may store various types of software and information necessary for the server 200 to provide an object tracking service. For example, the storage (not shown) may store various data or information used in programs, applications, and charging services executed in the server 200 .

The server 200 may be composed of a load balancing server and functional servers that provide a charging service. The server 200 may be composed of a plurality of servers divided by function, or may be an integrated server.

5 is a flowchart illustrating an object tracking method according to an embodiment. A detailed description of the content overlapping with the content described with respect to the object tracking apparatus 100 in the above will be omitted below.

In operation 510, the object tracking apparatus 100 may obtain information on the 3D space based on the light received in response to the emission of the light in the 3D space.

In operation 520, the object tracking apparatus 100 may identify objects in the 3D space from the obtained information on the 3D space. The object tracking apparatus 100 may cluster the obtained 3D space information and identify different objects using an object classification model. When the tag is identified, the object tracking apparatus 100 may classify and identify the objects corresponding to the first group in more detail based on at least one of the type, shape, and number of the tag among the identified objects.

In operation 530, the object tracking apparatus 100 may classify the identified objects into a plurality of groups based on the reflectance of the received light. The plurality of groups may include a first group corresponding to an object having a tag including a retroreflective material and a second group corresponding to an object having no tag. The first group may correspond to an object that reflects light having a reflectance greater than or equal to a predetermined standard by the tag, and the second group may correspond to an object that reflects light having only a reflectance lower than a predetermined reference.

In operation 540, the object tracking apparatus 100 may track an object of a group selected from among a plurality of groups.

6 is a flowchart illustrating an object tracking method according to another embodiment. A detailed description of the content overlapping with the content described with respect to the object tracking apparatus 100 in the above will be omitted below.

In operation 610, the object tracking apparatus 100 may obtain information on the 3D space based on the light received in response to the emission of the light in the 3D space.

In operation 620, the object tracking apparatus 100 may classify the obtained information on the 3D space into a plurality of groups based on the reflectance of the received light. The plurality of groups may include a first group corresponding to an object having a tag including a retroreflective material and a second group corresponding to an object having no tag. The first group may correspond to an object that reflects light having a reflectance greater than or equal to a predetermined standard by the tag, and the second group may correspond to an object that reflects light having only a reflectance lower than a predetermined reference.

In operation 630, the object tracking apparatus 100 may identify the object in the 3D space by using the information on the 3D space of the selected group from among the plurality of groups.

When the object tracking apparatus 100 identifies an object in the 3D space by using the information on the 3D space tagged as the second group, the object tracking apparatus 100 may classify and identify different objects using the object classification model. When the object tracking apparatus 100 identifies an object in a 3D space using the information on the 3D space tagged as the first group, the object tracking device 100 determines at least one of the type, shape, and number of the tag including the retroreflective material. Based on this, it can be distinguished and identified as different objects.

In operation 640, the object tracking apparatus 100 may track the identified object.

7 is a detailed flowchart illustrating a process for tracking an identified object.

Step 540 of FIG. 5 or step 640 of FIG. 6 described above will be described in detail.

In operation 710 , the object tracking apparatus 100 may track the movement of the identified object by accumulating location information of the identified object of the selected group. Furthermore, the object tracking apparatus 100 may predict the movement of the identified object based on the accumulated location information.

In operation 720, the object tracking apparatus 100 may analyze a movement pattern of the identified object based on the tracked movement. For example, when a certain rule is found in the movement pattern, the object tracking apparatus 100 may adjust the layout of the space or change the arrangement of products to increase operational efficiency. In addition, the object tracking apparatus 100 may check a case where an out-of-prediction object movement occurs, take measures to prevent a safety accident, and solve a safety problem.

Each of the above-described embodiments may be provided in the form of a computer program or application stored in a medium in order to execute predetermined steps for performing the object tracking method. In other words, each of the above-described embodiments may be provided in the form of a computer program or application stored in a medium, which causes at least one processor of the server to perform predetermined steps for performing the object tracking method.

The above-described embodiments may be implemented in the form of a computer-readable storage medium that stores instructions and data executable by a computer or processor. At least one of the instructions and data may be stored in the form of a program code, and when executed by the processor, a predetermined program module may be generated to perform a predetermined operation. Such computer-readable storage media include read-only memory (ROM), random-access memory (RAM), flash memory, CD-ROMs, CD-Rs, CD+Rs, CD-RWs, CD+RWs, DVD-ROMs. , DVD-Rs, DVD+Rs, DVD-RWs, DVD+RWs, DVD-RAMs, BD-ROMs, BD-Rs, BD-R LTHs, BD-REs, magnetic tapes, floppy disks, magneto-optical data storage devices, optical data storage devices, hard disks, solid-state disks (SSDs), and may store instructions or software, associated data, data files, and data structures, and may store instructions or It can be any device capable of providing software, associated data, data files, and data structures.

So far, examples have been mainly looked at. Those of ordinary skill in the art to which the disclosed embodiments pertain will understand that the disclosed embodiments can be implemented in modified forms without departing from the essential characteristics. Therefore, the disclosed embodiments are to be considered in an illustrative rather than a restrictive sense. The scope of the invention is indicated in the claims rather than the description of the above-described embodiments, and all differences within an equivalent range should be construed as being included in the scope of the invention.

Claims (15)

obtaining information on the three-dimensional space based on the light received in response to the emission of the light into the three-dimensional space;
identifying objects in the 3D space from the obtained 3D space information;
classifying the identified objects into a plurality of groups based on the reflectance of the received light; and
tracking an object of a selected group among the plurality of groups;
The plurality of groups includes a first group corresponding to an object having a tag including a retroreflective material and a second group corresponding to an object not having the tag, the object tracking method. The method of claim 1,
The first group corresponds to an object reflecting light having a reflectivity greater than or equal to a predetermined standard by the tag, and the second group corresponds to an object reflecting light having only a reflectance lower than the predetermined reference, object tracking Way. The method of claim 1,
The step of identifying the object in the three-dimensional space,
An object tracking method for clustering the obtained three-dimensional space information and identifying different objects using an object classification model. 4. The method of claim 3,
The step of identifying the object in the three-dimensional space,
An object tracking method for classifying and identifying objects corresponding to the first group based on at least one of a type, a shape, and a number of the tag among the identified objects. The method of claim 1,
The tag is in the form of any one of a name plate, a badge, a label, a string, clothing, and a hat to which the retroreflective material is applied. The method of claim 1,
The tracking step is
accumulating location information of the objects of the selected group to track the movement of the identified objects; and
Based on the tracked movement, analyzing the movement pattern of the identified object; Containing, object tracking method. The method of claim 1,
When the tag includes an electronic tag chip,
Further comprising the step of recognizing the tag within a predetermined distance from the object tracking device through short-range communication,
The step of classifying into the plurality of groups comprises:
Classifying the object having the recognized tag into the first group, an object tracking method. instructions for obtaining information on the three-dimensional space based on the light received in response to the emission of the light into the three-dimensional space;
instructions for identifying objects in the three-dimensional space from the obtained information on the three-dimensional space;
instructions for classifying the identified objects into a plurality of groups based on the reflectance of the received light; and
including instructions for tracking an object of a selected group among the plurality of groups,
The plurality of groups may include a first group corresponding to an object having a tag including a retroreflective material and a second group corresponding to an object not having the tag. recorded media. a sensor unit configured to acquire information on the three-dimensional space based on the light received in response to the emission of the light into the three-dimensional space;
a memory that stores one or more instructions; and
by executing the one or more instructions, identify objects in the three-dimensional space from the obtained information about the three-dimensional space, and classify the identified objects into a plurality of groups based on the reflectance of the received light, a processor for tracking an object of a selected group among the plurality of groups;
The plurality of groups includes a first group corresponding to an object having a tag including a retroreflective material and a second group corresponding to an object not having the tag, the object tracking device. 10. The method of claim 9,
The first group corresponds to an object reflecting light having a reflectivity greater than or equal to a predetermined standard by the tag, and the second group corresponds to an object reflecting light having only a reflectance lower than the predetermined reference, object tracking Device. 10. The method of claim 9,
By executing the one or more instructions, the processor clusters the obtained three-dimensional space information and identifies different objects using an object classification model. 12. The method of claim 11,
The processor by executing the one or more instructions, based on at least one of the type, shape, and number of the tag among the identified objects, to distinguish and identify objects corresponding to the first group, object tracking device . 10. The method of claim 9,
The tag is in the form of any one of a name plate, a badge, a label, a string, clothing, and a hat to which the retroreflective material is applied. 10. The method of claim 9,
The processor, by executing the one or more instructions, accumulates position information of the objects of the selected group, tracks the movement of the identified object, and analyzes the movement pattern of the identified object based on the tracked movement which is an object tracking device. 10. The method of claim 9,
Further comprising a communication interface device,
When the tag includes an electronic tag chip,
The processor recognizes the tag within a predetermined distance from the object tracking device through short-distance communication using the communication interface device by executing the one or more instructions, and classifies the object having the recognized tag into the first group which is an object tracking device.

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