Motion tracking system and method

Abstract

The present invention provides a motion tracking system and a motion tracking method. The motion tracking system includes three motion sensing devices that can be worn on a user's body part. In the method, first sensing data is obtained based on motion sensors placed on the motion sensing devices, and second sensing data is obtained based on wireless signals transmitted between the motion sensing devices. The user's motion information is determined by a determining factor. The determining factor includes the first sensing data and the second sensing data. Therefore, the accuracy of tracking the user's motion can be improved.

Description

Technical Field

[0001] The present invention generally relates to a method for tracking a user's motion, and more particularly to a motion tracking system and a motion tracking method. Background Art

[0002] In order to provide intuitive operations on electronic devices (such as game consoles, computers, smartphones, smart appliances, etc.), the user's movements can be detected to directly operate the electronic device according to the user's movements.

[0003] In conventional technology, some electronic devices may allow a user's body parts (such as hands, legs, head, etc.) to control the operation of these electronic devices, and may track the movement of these body parts. However, these electronic devices only provide a way to detect the movement of multiple body parts at the same time. For example, a virtual reality (VR) product may provide a handheld controller, and each handheld controller includes an inertial measurement unit (IMU) to track the movement of the user's hand. Sometimes, only one motion tracking method may be limited by its hardware or tracking mechanism, and cause abnormal or inaccurate tracking results. Summary of the invention

[0004] Sometimes, the tracking result using only a single sensor may be inaccurate. Therefore, the present invention is directed to a motion tracking system and a motion tracking method.

[0005] In one of the exemplary embodiments, the motion tracking method is applicable to a motion tracking system, which includes a first motion sensing device, a second motion sensing device, and a third motion sensing device wearable on a human body part of a user. The motion tracking method includes (but is not limited to) the following steps. First sensing data is obtained based on motion sensors disposed on the first motion sensing device, the second motion sensing device, and the third motion sensing device. Second sensing data is obtained based on a wireless signal transmitted between the first motion sensing device, the second motion sensing device, and the third motion sensing device. The motion information of the user is determined based on a determining factor including the first sensing data and the second sensing data.

[0006] In one of the exemplary embodiments, the motion tracking system includes (but is not limited to) three motion sensing devices and a processor. The motion sensing device can be worn on a human body part of a user. Each motion sensing device includes a wireless transceiver and a motion sensor. The wireless transceiver is used to transmit or receive wireless signals. The motion sensor is used to sense the movement of a human body part of the user. The processor is configured to obtain first sensing data based on the motion sensor of the motion sensing device, and obtain second sensing data based on the wireless signal data transmitted between the three motion sensing devices, and determine the user's motion information by a determinant including the first sensing data and the second sensing data.

[0007] Based on the above, the motion tracking system and motion tracking method according to the embodiments of the present invention can track the movement of a single operating part of the user based on the sensing data from the wireless signal and the motion sensor, thereby providing an accurate and reliable tracking mechanism.

[0008] However, it should be understood that this overview may not contain all aspects and embodiments of the invention, is not intended to be limiting or restrictive in any way, and the invention as disclosed herein is and will be understood by those of ordinary skill in the art to encompass obvious improvements and modifications thereto. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments of the invention and together with the description serve to explain the principles of the invention.

[0010] Figure 1 is a block diagram illustrating a motion tracking system according to one of the exemplary embodiments of the present invention;

[0011] Figure 2 is a schematic diagram illustrating a motion tracking system according to one of the exemplary embodiments of the present invention;

[0012] Figure 3 is a flow chart illustrating a motion tracking method according to one of the exemplary embodiments of the present invention;

[0013] Figure 4 is a schematic diagram illustrating a motion tracking method according to one of the exemplary embodiments of the present invention;

[0014] Figure 5 is a schematic diagram illustrating a motion tracking method according to one of the exemplary embodiments of the present invention.

[0015] Description of Figure Numbers

[0016] 10: Motion tracking system;

[0017] 20: Motion tracking system;

[0018] 100: motion sensing device;

[0019] 110: wireless transceiver;

[0020] 130: motion sensor;

[0021] 200: computing equipment;

[0022] 240: memory;

[0023] 250: processor;

[0024] 300: Head-mounted display;

[0025] 310: wireless transceiver;

[0026] 360: Image sensor;

[0027] B1, B2, B3, B4, B5: human body parts;

[0028] S310, S330, S350: steps;

[0029] FOV: Field of view. DETAILED DESCRIPTION

[0030] Reference will now be made in detail to the preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Whenever possible, the same reference numerals are used in the drawings and the description to refer to the same or like parts.

[0031] Figure 1 1 is a block diagram illustrating a motion tracking system 10 according to one of the exemplary embodiments of the present invention. Figure 1 , the motion tracking system 10 includes (but is not limited to) three or more motion sensing devices 100 and a computing device 200. The motion tracking system 10 may be applicable to VR, AR, MR, XR or other reality-related technologies.

[0032] Each motion sensing device 100 includes (but is not limited to) a wireless transceiver 110 and a motion sensor 130. The motion sensing device 100 can be a handheld controller or a wearable device, such as a wearable controller, a smart watch, an ankle sensor, a belt, a head-mounted display (HMD) or the like. In one embodiment, each motion sensing device 100 can be worn on a human body part of the user. The human body part can be a hand, head, ankle, leg, waist or other parts.

[0033] The wireless transceiver 110 may be a communication transceiver compatible with Bluetooth, Wi-Fi, IR, RFID or other wireless communication technologies. In one embodiment, the wireless transceiver 110 is used to transmit and / or receive wireless signals together with the wireless transceivers 110 of other motion sensing devices 100, and will generate the first sensing data of the sequence based on the wireless signals transmitted between the motion sensing devices 100. A detailed process for generating the first sensing data of the sequence will be introduced later.

[0034] The motion sensor 130 may be an accelerometer, a gyroscope, a magnetometer, an inertial measurement unit (IMU), or any combination of the foregoing sensors. In an embodiment, the motion sensor 130 is used to sense the motion of the corresponding human body part of the user wearing the motion sensing device 100 over a period of time, so as to generate a sequence of first sensing data from the sensing results (such as acceleration, rotation, magnetism, etc.) of the motion sensor 130 at multiple time points within the time period. For one example, the first sensing data includes 3-degree of freedom (3-DoF) data, and the 3-DoF data is related to the orientation information of the human body part in a three-dimensional (3D) space, such as acceleration of yaw, roll, and pitch.

[0035] The computing device 200 includes, but is not limited to, a memory 240 and a processor 250. The computing device 200 may be one of a computer, a server, a smart phone, a tablet computer, or the motion sensing device 100.

[0036] The memory 240 may be any type of fixed or removable random-access memory (RAM), read-only memory (ROM), flash memory, or similar device or combination of the above devices. The memory 240 may be used to store program code, device configuration, buffer data, or permanent data (such as sensor data, motion information, distance relationship, etc.), and these data will be described later.

[0037] The processor 250 is connected to the memory 240, and the processor 250 is configured to load the program code stored in the memory 240, so as to execute the program of the exemplary embodiment of the present invention. In one embodiment, the functions of the processor 150 are implemented by using a programmable unit such as a central processing unit (CPU), a microprocessor, a microcontroller, a digital signal processing (DSP) chip, a field programmable gate array (FPGA), etc. In some embodiments, the functions of the processor 250 can also be implemented by an independent electronic device or an integrated circuit (IC), and the operation of the processor 250 can also be implemented by software.

[0038] It should be noted that the processor 250 may or may not be disposed on the same device as one, part, or all of the motion sensing devices 100. However, the devices equipped with the motion sensor 130 and the processor 250, respectively, may also include a communication transceiver with a compatible communication technology such as Bluetooth, Wi-Fi, IR, or a physical transmission line to transmit / receive data to each other.

[0039] In one embodiment, the motion tracking system 10 may further include a head mounted display (HMD) 300. The HMD 300 may be worn on the user's head. The HMD 300 includes, but is not limited to, a wireless transceiver 310 and an image sensor 360.

[0040] The description of the wireless transceiver 310 may refer to the description of the wireless transceiver 110 , and will be omitted. This means that the HMD 300 can communicate with the motion sensing device 100 through the wireless transceiver 310 .

[0041] Image sensor 360 may be a camera, such as a monochrome camera or a color camera, a depth camera, a video recorder, or other sensor capable of capturing images.

[0042] Figure 2 is a schematic diagram showing a motion tracking system 20 according to one of the exemplary embodiments of the present invention. Figure 2 The motion tracking system 20 includes an HMD 300 and four motion sensing devices 100 (the four devices are two ankle sensors worn on human body parts B1 and B2 (i.e., two ankles) and two handheld controllers worn on human body parts B3 and B4 (i.e., two hands)). In some embodiments, the HMD 300 may further include another motion sensor 130 (not shown) to obtain orientation information of human body part B5 (i.e., head). The processor 250 is embedded in the HMD 300.

[0043] It should be noted that the motion tracking system 20 is only an example to illustrate the placement of the motion sensing device 100, the HMD 300, and the processor 250. However, there are still many other implementations of the behavior understanding system 10, and the present invention is not limited thereto.

[0044] In order to better understand the operation process provided in one or more embodiments of the present invention, several embodiments are illustrated below to explain in detail the operation process of the motion tracking system 10 or the motion tracking system 20. The devices and modules in the motion tracking system 10 or the motion tracking system 20 are applied in the following embodiments to explain the control method provided herein. Each step of the control method can be adjusted according to the actual implementation situation and should not be limited to the content described herein.

[0045] Figure 3 is a flow chart showing a motion tracking method according to one of the exemplary embodiments of the present invention. Figure 3 , the processor 250 may obtain first sensing data based on the motion sensors 130 disposed on the three motion sensing devices 100 (step S310). Specifically, with respect to different types of motion sensors 130, acceleration, rotation, magnetism, orientation and / or 3-DoF / 6-DoF of the motion of the corresponding human body part in the 2D / 3D space may be obtained, and one or more sensing results of the motion sensor 130 may become the sequence first sensing data of the human body part.

[0046] On the other hand, the processor 250 may obtain the second sensing data based on the wireless signals transmitted between the three motion sensing devices 100 (step S330). In one embodiment, the processor 250 may obtain the signal strength of the wireless signals from the three or more motion sensing devices 100 at multiple time points, and each signal strength will be recorded in the memory 240 together with its corresponding transmitter and receiver. The signal strength may be a received signal strength indication (RSSI), a received channel power parameter (RCPI), a reference signal received power (RSRP), or the like. In one embodiment, the motion sensing device 100 may monitor the signal strength of all detectable wireless signals, and each wireless signal includes a specific identifier of the transmitter and / or receiver. The motion sensing device 100 may further feed back the signal strength with the corresponding identifier to the computing device 200. In another embodiment, the computing device 200 may monitor the signal strength of all detectable wireless signals, and the processor 250 records the signal strength and the corresponding identifier of the transmitter in the memory 240. The signal strength will be recorded for a period of time to generate a sequence of second sensing data. This means that the second sensing data contains a time-arranged sequence of signal intensities.

[0047] In some embodiments, the processor 250 may further obtain third sensing data based on the image captured from the image sensor 360. The third sensing data may be sensing results (such as brightness, color, depth, etc.) of the sequence of images and / or pixels in the images.

[0048] Next, the processor 250 may determine the user's motion information from a determinant including the first sensing data and the second sensing data (step S350). In one embodiment, the motion information may include position information and orientation information. First, regarding the position information, in one embodiment, the processor 250 may determine the user's position information based on the first sensing data. In this embodiment, the determinant includes the first sensing data. The displacement of the corresponding human body part can be estimated by double integration of the acceleration detected on the three axes of the human body part (i.e., the second sensing data) to further determine the position information based on the displacement. For example, the position information may be coordinates on two or three axes, a position relative to a reference, etc.

[0049] In another embodiment, the processor 250 may obtain the location information based on the second sensing data based on the wireless signal between the three motion sensing devices 100. In this embodiment, the determining factor includes the second sensing data, and it should be noted that the signal strength of the wireless signal is related to the relative distance between the two motion sensing devices 100. In addition, based on trilateration, the three distances between the three points can be used to determine the relative location information of the three points. Assuming that the three motion sensing devices 100 are the aforementioned three points, the processor 250 may determine the relative distance between every two motion sensing devices 100 as the distance relationship between the motion sensing devices 100. Then, the processor 250 may generate the location information of the tracking device based on the distance relationship and the trilateration.

[0050] Taking the motion tracking system 20 as an example, the processor 250 may obtain the signal strength of the wireless signal from the motion sensing device 100 for the human body part B3 to the HMD 300 for the human body part B5 (one of the motion sensing devices 100 in this embodiment), the wireless signal from the motion sensing device 100 for the human body part B4 to the HMD 300 for the human body part B5, and the wireless signal from the motion sensing device 100 for the human body part B3 to the motion sensing device 100 for the human body part B4. The processor 250 may determine the distance relationship thereof according to the signal strength, and then generate the position information of the human body part B3 based on the distance relationship. The position information may be a coordinate or a relative position.

[0051] It should be noted that the embodiment is not limited to selecting three motion sensing devices 100. For example, the signal strengths of the wireless signal from the motion sensing device 100 for the human body part B2 to the motion sensing device 100 for the human body part B3, the wireless signal from the motion sensing device 100 for the human body part B3 to the motion sensing device 100 for the human body part B1, and the wireless signal from the motion sensing device 100 for the human body part B2 to the motion sensing device 100 for the human body part B1 can be used to estimate the position information of the human body part B1. The combination of the motion sensing devices 100 can be changed as needed.

[0052] In another embodiment, the processor 250 may determine the user's position information based on the third sensing data. In this embodiment, the determining factor includes the third sensing data. The position and displacement of the human body part in the image may be used to determine the position information in the real environment. Figure 2 For example, the sensing intensity and pixel position corresponding to the human body part B4 in the image can be used to estimate the depth information of the human body part B4 (ie, the distance relative to the HMD 300 ) and estimate the 2D position of the human body part B4 on a plane parallel to the image sensor 360 .

[0053] It should be noted that the accuracy of the position information based on only one sensing method (e.g., based on one of the wireless transceiver 110, the motion sensor 130, and the image sensor 360) may be different. Therefore, two or more sensing methods can be used to determine the position information of the corresponding human body part.

[0054] In one embodiment, the processor 250 may obtain the first location information based on the first sensing data, obtain the second location information based on the second sensing data, and obtain the adjusted location information based on the first location information and the second location information. In this embodiment, the determining factor includes the first sensing data and the second sensing data. The processor 250 may determine the location information based on a combination of the first location information and the second location information. In some embodiments, the combination is a weighted combination. The adjusted location information is determined based on the weighted first location information and the weighted second location information.

[0055] In one embodiment, the weight of the weighted combination of the first position information and the second position information may be fixed. In another embodiment, the weight of the weighted combination of the first position information and the second position information may be variable. The weight of the first position information may be a value from 0 to 100%, and the weight of the second position information may be a value from 0 to 100%. However, the weights of the first position information and the second position information cannot both be 0 at the same time.

[0056] It should be noted that in some embodiments, the position information determined based on the third sensing data generated by the image of the image sensor 360 may be more accurate than the position information determined based on the wireless transceiver 110 and / or the motion sensor 130. Therefore, in one embodiment, the determining factor may include the second sensing data and the third sensing data. The processor 250 may determine the position information based on a combination of the position information obtained based on the first sensing data, the second sensing data, and the third sensing data.

[0057] In one embodiment, the processor 250 may obtain a first portion of the position information according to the second sensing data in a first duration, obtain a second portion of the position information according to the third sensing data in a second duration, and combine the first portion and the second portion of the position information into combined position information. The third sensing data detecting the human body portion may be used to correct the position information based on the second sensing data in the first duration and the second duration. The processor 250 may determine the combined position information based on the first portion and the second portion of the position information in different durations. For example, a position (1, 1) is determined based on the second sensing data in the first duration, another position (2, 1) is determined based on the third sensing data in the second duration, and the combined position information may be a displacement from the position (1, 1) to the position (2, 1).

[0058] In some embodiments, the processor 250 may determine the position information based on a weighted combination of the second position information and the third position information. Based on actual conditions, the weights of the second position information and the third position information may be variable or fixed. For example, the weight of the third position information may be greater than the weight of the second position information. In another embodiment, if the human body part is present in the third sensing data, the position information is a weighted combination, and if the human body part is not present in the third sensing data, the position is the second position information.

[0059] In one embodiment, the image sensor 360 may be designed with a specific field of view (FOV). If a human body part is located outside the FOV of the image sensor 360, the processor 250 may not be able to determine the motion information of the human body part using only the third sensing data, and should consider the first sensing data or the second sensing data.

[0060] In one embodiment, the processor 250 may determine whether a human body part of the user exists in the third sensing data of the sequence, and determine whether to use the distance relationship between the three motion sensing devices 100 to determine the position information based on trilateration according to the result of the determination of the existence of the human body part. The processor 250 may use machine learning technology (such as deep learning, artificial neural network (ANN) or support vector machine (SVM) etc.) to identify the target human body part in the third sensing data.

[0061] Figure 4 is a schematic diagram illustrating a motion tracking method according to one of the exemplary embodiments of the present invention. Figure 4 , assuming that the motion sensing device 100 of the human body part B4 is the target device. In this figure, the human body part B4 exists in the field of view FOV of the HMD 300 (ie, the human body part B4 exists in the third sensing data).

[0062] Figure 5 is a schematic diagram illustrating a motion tracking method according to one of the exemplary embodiments of the present invention. Figure 5 , assuming that the motion sensing device 100 of the human body part B3 is the target device. In this figure, the human body part B5 does not exist in the field of view FOV of the HMD 300 (ie, the human body part B3 does not exist in the third sensing data).

[0063] It should be noted that Figure 4 and Figure 5 The size and shape of the field of view shown in are only examples and may be modified based on actual needs.

[0064] Therefore, the field of view of the image sensor 360 is used to determine whether the human body part is present in the third sensing data. In one embodiment, it is assumed that the human body part is outside the field of view (i.e., not present in the third sensing data) at the first duration, and the human body part is within the field of view of the image sensor 360 at the second duration (i.e., present in the third sensing data). In some embodiments, it is assumed that the human body part is located inside the field of view of the image sensor 360 at the first duration and the second duration.

[0065] In another embodiment, the processor 250 may obtain the first position information according to the first sensing data, obtain the second position information according to the second sensing data, obtain the third position information according to the third sensing data, and obtain the adjusted position information according to the first position information, the second position information, and the third position information. In this embodiment, the determining factor includes the first sensing data, the second sensing data, and the third sensing data. The processor 250 may determine the adjusted position information according to a combination of the first motion information, the second motion information, and the third position information.

[0066] In one embodiment, the combination is a weighted combination. The processor 250 may determine a first weight of the first position information and a second weight of the second position information based on the third position information. In one embodiment, the first weight and the second weight are repeatedly changed. During the duration that the human body part is present in the third sensing data, the third position information will be regarded as the corrected position information, and the weighted combination of the first position information and the second position information with the first weight and the second weight will be adjusted according to the third position information. It should be noted that the processor 250 may obtain the weighted combination by multiplying the first weight by the first position information to obtain the first parameter, by multiplying the second weight by the second position information to obtain the second parameter, and by adding the first parameter to the second parameter to obtain the adjusted position information.

[0067] In one embodiment, the first weight and the second weight of the subsequent time point can be determined based on an equation in which the third position information is equal to a weighted combination of the first position information and the second position information of the previous time point. For example, at the third time point, in the 3-dimensional coordinate system, the first weight is 0.5 and the second weight is 0.5, the first position information is (6, 6, 6) and the second position information is (10, 10, 10), and the adjusted position information will be (8, 8, 8). If the third position information is (7, 7, 7), then the first weight and the second weight at the fourth time point will be determined as 0.75 and 0.25, respectively. Then, at the fourth time point, if the first position information is (7, 6, 6) and the second position information is (12, 10, 10) in the 3-dimensional coordinate system, then the adjusted position information will be (8.25, 7, 7).

[0068] In another embodiment, the first weight and the second weight at the current time point may be determined based on an equation in which the third position information is equal to a weighted combination of the first position information and the second position information at the current time point. For example, at the second time point, in the 3-dimensional coordinate system, the first position information is (6, 6, 6) and the second position information is (10, 10, 10). If the third position information is (7, 7, 7), then the first weight and the second weight at the second time point will be determined as 0.75 and 0.25, respectively. Then, the adjusted position information at the second time point will be determined as (7, 7, 7).

[0069] In some embodiments, if the human body part of the user does not exist in the third sensing data, the first weight and the second weight are fixed. If the human body part is outside the field of view of the image sensor 360, the third weight and the second weight will be the same as the previous first weight and the second weight at the previous time point when the human body part of the user is still present in the third sensing data. For example, at a first time point, the human body part is within the field of view of the image sensor 360, and the first weight is 0.5 and the second weight is 0.5. Then, at a second time point, the human body part is outside the field of view of the image sensor 360. Same as the first weight and the second weight at the first time point, at the second time point, the first weight will be 0.5 and the second weight will be 0.5. Until the human body part of the user is present in the third sensing data, the first weight and the second weight will change according to the third sensing data.

[0070] In another embodiment, the processor 250 may determine the adjusted location information based on a weighted combination of the first location information, the second location information, and the third location information. The adjusted location information is determined based on the sum of the weighted first location information, the weighted second location information, and the weighted third location information. Based on actual conditions, the weights of the three location information may be variable or fixed.

[0071] On the other hand, regarding orientation information, in one embodiment, the processor 250 may directly use the first sensing data of the sequence as orientation information. For example, the orientation information may be acceleration, angular velocity in three axes, orientation, 3-DoF information, and / or 6-DoF information.

[0072] In another embodiment, the processor 250 may determine the orientation information according to the third sensing data. Figure 4 As an example, two postures of the human body part B4 in the image at different time points can be used to estimate the orientation information.

[0073] In some embodiments, the processor 250 may determine the orientation information based on the first sensing data and the third sensing data. The orientation information may be a weighted combination of the first sensing data and the third sensing data. For example, the position information is determined based on the sum of the weighted first orientation information based on the motion sensor 130 and the weighted second orientation information based on the image sensor 360.

[0074] In one embodiment, the field of view of the image sensor 360 will be a condition on whether to use the orientation information based on the third sensing data. If the human body part is present in the third sensing data, the orientation information can be determined based on the first sensing data and the third sensing data. If the human body part is not present in the third sensing data, the orientation information can be determined based on the first sensing data alone.

[0075] In one embodiment, the processor 250 may determine the motion information of the user based on the orientation information and the position information. The orientation information may be generated based on the first sensing data, the third sensing data, or a combination of the first sensing data and the third sensing data as described above. The position information may be generated based on the first sensing data, the second sensing data, and the third sensing data as described above. Figure 2 Taking the human body part B1 or the human body part B2 in FIG. 1 as an example, the motion information may be related to lifting, pointing, kicking, stepping or jumping motions.

[0076] In another embodiment, the processor 250 may determine the user's motion information based on the orientation information based on the first sensing data and the adjusted position information based on the first position information and the second position information. The processor 250 may predict the user's motion regardless of whether the human body part exists in the third sensing data.

[0077] In another embodiment, the processor 250 may determine the user's motion information based on the orientation information based on the first sensing data and the combined position information based on the second sensing data and the third sensing data. This means that when a human body part exists and does not exist in the third sensing data, the motion information may be determined based on the orientation information and the combined position information within two durations.

[0078] by Figure 4 and Figure 5 For example, in Figure 4 The hand-raising movement of body part B4 is determined in Figure 5 Next, the swinging motion of the human body part B4 from top to bottom is determined.

[0079] In one embodiment, the processor 250 may determine the user's motion information based only on the position information based on the second sensing data. In another embodiment, the processor 250 may determine the user's motion information based only on the combined position information based on the second sensing data and the third sensing data. In some embodiments, if the human body part does not exist in the third sensing data, the processor 250 may determine the user's motion information based only on the position information based on the second sensing data, and if the human body part exists in the third sensing data, the processor 250 may determine the user's motion information based only on the position information or the combined position information based on the third sensing data.

[0080] The displacement or trajectory of a human body part can be tracked, and motion information can be determined based on the displacement or trajectory. Figure 4 and Figure 5 As an example, the human body part B3 moves from top to bottom, and the human body part B4 is determined to swing from top to bottom.

[0081] In summary, in the motion tracking system and motion tracking method for multiple operating parts of a user in the embodiments of the present invention, the movement of a human body part can be tracked based on signal strength, sensing results of a motion sensor and / or camera images. If it is concluded based on the detection results of the camera image that the tracked human body part does not exist within the FOV, the signal strength between the motion sensing devices can be used to compensate for the accuracy of the sensing results obtained using the motion sensor in determining the position information. In addition, if the tracked human body part exists within the FOV, the camera image can be used to correct the position estimation result based on the signal strength. In this way, several tracking methods can be used for different conditions to improve the accuracy of the tracking results.

[0082] It will be apparent to those skilled in the art that various modifications and changes may be made to the structure of the present invention without departing from the scope or spirit of the present invention. In view of the above, it is desired that the present invention covers modifications and changes of the present invention, provided that the modifications and changes fall within the scope of the appended claims and their equivalents.

Claims

1. A motion tracking method, applicable to a motion tracking system, wherein the motion tracking system comprises a first motion sensing device, a second motion sensing device and a third motion sensing device wearable on a human body part of a user, and the motion tracking method comprises: obtaining first sensing data based on motion sensors disposed on the first motion sensing device, the second motion sensing device, and the third motion sensing device; obtaining second sensing data based on wireless signals transmitted between the first motion sensing device, the second motion sensing device, and the third motion sensing device; determining the movement information of the user by a determining factor; obtaining third sensing data based on an image captured from the image sensor, Obtaining orientation information and first position information according to the first sensing data; obtaining second position information according to the second sensing data; Obtaining third position information according to the third sensing data; Obtaining adjusted location information according to the first location information, the second location information, and the third location information includes: Determine a first weight and a second weight according to the third position information; Obtaining a first parameter by multiplying the first weight by the first position information; obtaining a second parameter by multiplying the second weight by the second position information; and obtaining the adjusted position information by adding the first parameter to the second parameter; and determining the motion information of the user according to the orientation information and the adjusted position information, wherein the determining factor includes the first sensing data, the second sensing data and the third sensing data, The body part of the user exists in the third sensing data.

2. The motion tracking method according to claim 1, wherein the step of determining the motion information of the user comprises: obtaining a first portion of position information according to the second sensing data within a first duration; obtaining a second portion of position information according to the third sensing data within a second duration; combining the first part and the second part of the position information into combined position information; as well as The motion information of the user is determined based on the orientation information and the combined position information. The motion tracking method according to claim 1 , wherein the first weight and the second weight are repeatedly changed. 4 . The motion tracking method according to claim 1 , wherein in response to the human body part of the user not existing in the third sensing data, the first weight and the second weight are fixed. 5 . The motion tracking method according to claim 2 , wherein the human body part of the user does not exist in the third sensing data during the first duration, and the human body part of the user exists in the third sensing data during the second duration.

6. A motion tracking system comprising: Three motion sensing devices, wearable on a user's body part, wherein each of the motion sensing devices comprises: Wireless transceivers, which transmit or receive wireless signals; a motion sensor that senses motion of one of the body parts of the user; An image sensor to obtain an image; and A processor configured to perform: obtaining first sensing data based on the motion sensors of the three motion sensing devices; obtaining second sensing data based on wireless signals transmitted between the three motion sensing devices; determining the movement information of the user by a determining factor; obtaining third sensing data based on the image; Obtaining orientation information and first position information according to the first sensing data; obtaining second position information according to the second sensing data; Obtaining third position information according to the third sensing data; Obtain adjusted location information according to the first location information, the second location information, and the third location information determining the motion information of the user according to the orientation information and the adjusted position information; Determine a first weight and a second weight according to the third position information; Obtaining a first parameter by multiplying the first weight by the first position information; obtaining a second parameter by multiplying the second weight by the second position information; and The adjusted position information is obtained by adding the first parameter to the second parameter, wherein the determining factor includes the first sensing data, the second sensing data and the third sensing data, The body part of the user exists in the third sensing data.

7. The motion tracking system of claim 6, wherein the processor is configured to perform: obtaining a first portion of position information according to the second sensing data within a first duration; obtaining a second portion of position information according to the third sensing data within a second duration; combining the first part and the second part of the position information into combined position information; as well as The motion information of the user is determined based on the orientation information and the combined position information. The motion tracking system according to claim 6 , wherein the first weight and the second weight are repeatedly changed. 9 . The motion tracking system of claim 6 , wherein in response to the human body part of the user not being present in the third sensing data, the first weight and the second weight are fixed. 10 . The motion tracking system according to claim 7 , wherein the human body part of the user does not exist in the third sensing data during the first duration, and the human body part of the user exists in the third sensing data during the second duration.

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