WO2019134305A1

WO2019134305A1 - Method and apparatus for determining pose, smart device, storage medium, and program product

Info

Publication number: WO2019134305A1
Application number: PCT/CN2018/084233
Authority: WO
Inventors: 杨宇; 王冉冉
Original assignee: 青岛海信电器股份有限公司
Priority date: 2018-01-03
Filing date: 2018-04-24
Publication date: 2019-07-11
Also published as: CN108196701B; CN108196701A

Abstract

Provided are a method and apparatus for determining a pose, a smart device, a storage medium, and a program product. The method for determining a pose comprises: determining a first pose on the basis of movement data acquired by an IMU and the most recently determined pose of a smart device (101); obtaining a first magnetic vector acquired by a magnetic sensor and searching a stored pose mapping table for a second pose on the basis of the first magnetic vector (102); and when the second pose is found, determining the current pose of the smart device on the basis of the first pose and the second pose (103). According to the method and apparatus for determining a pose, the smart device, the storage medium, and the program product, the requirements for the magnetic field in a surrounding environment are reduced.

Description

Method, device, smart device, storage medium and program product for determining posture

This application claims priority to Chinese Patent Application No. 201810003966.9 filed on Jan. 3, 2018, the entire disclosure of which is incorporated herein by reference. In the application.

Technical field

The present application relates to the field of pose tracking technology, and in particular, to a method, device, smart device, storage medium and program product for determining a posture.

Background technique

At present, applications of smart devices such as smart phones, VR (Virtual Reality) devices, and AR (Augmented Reality) devices are becoming more and more popular. When a smart device such as this moves along with the user, the smart device can determine the current posture of the smart device according to the action that the user performs with the user, and then respond according to the current posture.

Summary of the invention

Embodiments of the present application provide a method, an apparatus, a smart device, a storage medium, and a program product for determining a gesture. In a first aspect, a method of determining a pose is provided, the method comprising:

Obtaining, when the motion data collected by the inertial measurement unit IMU in the smart device is received at the current sampling moment, the posture of the smart device that was last determined before the current sampling time, and determining based on the motion data and the last time The posture of the smart device determines a first posture;

Obtaining a first magnetic force vector acquired by a magnetic sensor in the smart device, and searching for a second posture from the stored attitude mapping table based on the first magnetic force vector, the gesture mapping table is used to indicate a magnetic force vector and a posture Correspondence between

When the second gesture is found, the current posture of the smart device is determined based on the first posture and the second posture.

In a second aspect, an apparatus for determining a pose is provided, the apparatus comprising:

a first acquiring module, configured to acquire, when the motion data collected by the inertial measurement unit IMU in the smart device is received at the current sampling moment, the posture of the smart device determined last time before the current sampling moment;

a first determining module, configured to determine a first posture based on the motion data and the posture of the smart device that is last determined;

a second acquiring module, configured to acquire a first magnetic force vector collected by a magnetic sensor in the smart device;

a first searching module, configured to search, according to the first magnetic force vector, a second posture from a stored attitude mapping table, where the gesture mapping table is used to indicate a correspondence between a magnetic force vector and a posture;

And a second determining module, configured to determine a current posture of the smart device based on the first posture and the second posture when the second posture is found.

The third aspect provides a virtual reality VR device, where the VR device includes:

IMU for collecting motion data;

a magnetic sensor for acquiring a magnetic force vector;

processor;

a memory for storing the processor executable instructions;

The processor is configured as the steps of any of the methods described in the above first aspect.

In a fourth aspect, a computer readable storage medium is provided having stored thereon instructions that, when executed by a processor, implement the steps of any of the methods of the first aspect described above.

In a fifth aspect, a computer program product is provided, which, when run on a computer, causes the computer to perform any of the methods described above in the first aspect.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the present application. Other drawings may also be obtained from those of ordinary skill in the art in light of the inventive work.

Figure 1A is a schematic view showing a roll angle, a pitch angle, and a yaw angle;

FIG. 1B is a flowchart of a method for determining a posture according to an embodiment of the present application; FIG.

2 is a flowchart of another method for determining a posture provided by an embodiment of the present application;

3A is a schematic structural diagram of an apparatus for determining a posture according to an embodiment of the present application;

FIG. 3B is a schematic structural diagram of an apparatus for determining a posture according to an embodiment of the present application; FIG.

3C is a schematic structural diagram of a first searching module according to an embodiment of the present application;

3D is a schematic structural diagram of a second determining module provided by an embodiment of the present application;

FIG. 4 is a schematic structural diagram of a smart device for determining a posture provided by an embodiment of the present application.

Detailed ways

In order to make the objects, technical solutions and advantages of the present application more clear, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

Before the detailed description of the embodiments of the present application, the application scenarios involved in the embodiments of the present application are introduced.

Currently, applications such as smart phones, VR devices, and AR devices are becoming more and more popular. When a smart device such as this moves with the user, the smart device can determine the current posture of the smart device according to the actions that the user makes with the user. For example, the user can wear a VR head-mounted display and drive the VR head-mounted display together by rotating the head. At this time, the VR head-mounted display can determine its current posture, that is, the VR headset The display can determine its current roll angle, pitch angle, and yaw angle relative to the standard coordinate system, and characterize its current pose by roll angle, pitch angle, and yaw angle. As another example, a user can hold a smartphone and rotate the smartphone in different directions and planes. In this case, the smartphone can respond accordingly by determining its own posture and according to the determined posture. The method for determining the posture provided in the embodiment of the present application may be applied to the foregoing scenario, and when the smart device such as a VR device, an AR device, or a smart phone moves along with the user action, determining the posture according to the embodiment of the present application. The method determines its current posture and provides data support for the next step of response.

In the related art, an IMU (Inertial Measurement Unit) and a magnetic sensor are disposed in the smart device, wherein the IMU generally includes a gyroscope and an accelerometer, and the smart device can calculate the first by integrating the angular velocity measured by the gyroscope. Roll angle, first pitch angle and first yaw angle. Afterwards, the smart device can correct the first roll angle and the first pitch angle according to the acceleration measured by the accelerometer, and calculate the second yaw angle according to the magnetic data measured by the magnetic sensor, and the first yaw angle by the second yaw angle The yaw angle is corrected, and the corrected roll angle, pitch angle, and yaw angle can be used to characterize the current posture of the smart device. FIG. 1A is a schematic view of a roll angle, a pitch angle, and a yaw angle. As shown in FIG. 1A, the coordinate system is established by the smart device, with the center of mass of the smart device as the origin, the X axis is perpendicular to the front of the smart device and points to the direction of the front of the smart device, and the Y axis is perpendicular to the X axis to point to the smart device. On the right side, the Z axis is perpendicular to the X and Y axes and points to the top of the smart device. As shown in FIG. 1A, when the smart device rotates around the X axis, the angle of rotation is the roll angle. When the smart device rotates around the Y axis, the angle of rotation is the pitch angle, when the smart device is around the Z axis. When rotated, the angle of rotation is the yaw angle.

However, in the above process of determining the posture, since the magnetic sensor is susceptible to the influence of the surrounding magnetic field, when the surrounding magnetic field is not uniform, the measured magnetic data is inaccurate, and the calculated data is based on the magnetic data. There will be deviations in the yaw angle. On this basis, in order to ensure that a more accurate attitude can be determined by the second yaw angle, it is necessary to ensure the accuracy of the magnetic data, and in order to ensure the accuracy of the magnetic data, There is a strict requirement on the magnetic field of the environment in which the current smart device is located. In other words, the method of determining the second yaw angle by the magnetic force data in the related art has strict requirements on the magnetic field of the application environment, resulting in determining the posture in the related art. The method of application has a narrow scope.

Next, a method for determining a posture provided by an embodiment of the present application is introduced.

FIG. 1B is a flowchart of a method for determining a posture according to an embodiment of the present application. The method can be applied to an intelligent device, where the IMU and the magnetic sensor are configured, and the smart device can be a smart device such as a smart phone, a tablet computer, a VR device, or an AR device. Referring to FIG. 1B, the method includes the following steps:

Step 101: When receiving the motion data collected by the IMU in the smart device at the current sampling moment, acquiring the posture of the smart device determined last time before the current sampling moment, and determining the motion device based on the motion data and the posture of the smart device determined last time. The first gesture.

The IMU can collect data according to the preset duration, and the time at which the data is collected is the sampling moment. After the IMU collects the motion data at each sampling time, the IMU can send the data to the smart device. Additionally, the IMU can include a gyroscope and an accelerometer, based on which the data acquired by the IMU can include angular velocity data acquired by the gyroscope, which can include angular velocity components of the smart device on three axes of the world coordinate system. In addition, the data collected by the IMU may also include gravity data acquired by the accelerometer.

Step 102: Acquire a first magnetic force vector acquired by a magnetic sensor in the smart device, and search for a second posture from the stored attitude mapping table based on the first magnetic force vector.

The gesture mapping table is used to indicate a correspondence between the magnetic force vector and the posture, or to indicate a correspondence between the magnetic force vector, the posture, and the score. That is to say, the gesture map can store multiple records, and each record is a correspondence between a set of magnetic vectors and gestures, or each record is a set of magnetic vectors, poses and scores. Correspondence between them.

It should also be noted that the magnetic sensor can also perform data acquisition according to the preset duration, that is, the magnetic sensor and the IMU synchronize data acquisition. Alternatively, the sampling period of the data collected by the magnetic sensor may be other integer multiples of the preset duration, that is, the sampling period of the data collected by the magnetic sensor is greater than the sampling period of the IMU, and the moment when the magnetic sensor performs data collection is also the IMU. Sampling moment. Alternatively, the sampling period of the data collected by the magnetic sensor is greater than the sampling period of the IMU, and the sampling timing is not synchronized.

In addition, in the embodiment of the present application, the magnetic sensor collects the readings on the three coordinate axes of the world coordinate system when collecting data, that is, the magnetic component on each axis in the world coordinate system, and the smart device can The first magnetic force vector is obtained from the three components.

Step 103: Determine the current posture of the smart device based on the first posture and the second posture when the second posture is found.

After determining the first posture and the second posture, if the first posture and the second posture are different, the first posture may be corrected according to the second posture, thereby obtaining the current posture of the smart device. If the first posture and the second posture are the same, the first posture may be determined as the current posture of the smart device.

In the embodiment of the present application, when the motion data collected by the IMU in the smart device is received at the current sampling moment, the posture of the smart device determined last time before the current sampling moment is acquired, and based on the motion data and the last determined intelligence. The posture of the device determines a first posture, acquires a first magnetic force vector collected by the magnetic sensor in the smart device, and searches for a second posture from the stored posture mapping table based on the first magnetic force vector, and when the second posture is found, A current posture of the smart device is determined based on the first posture and the second posture. Therefore, after obtaining the first magnetic force vector, the embodiment of the present application does not directly calculate the yaw angle of the posture according to the first magnetic force vector, but uses the first magnetic force vector according to the indication in the stored posture mapping table. The correspondence between the magnetic force vector and the posture determines the second posture. If the first magnetic force vector is directly used to calculate the yaw angle of the attitude, since the first magnetic force vector directly participates in the operation, the requirement of the magnetic field environment that affects the accuracy of the first magnetic vector is very strict, and in the embodiment of the present application, Determining the second posture according to the stored attitude map by using the first magnetic force vector, the first magnetic vector does not need to directly participate in the operation to obtain the second posture, and therefore, compared to directly calculating the yaw angle by using the first magnetic vector, The requirements of the surrounding magnetic field are more relaxed and applicable to a wider range of applications.

FIG. 2 is a flowchart of another method for determining a gesture provided by an embodiment of the present application. The method can be applied to an intelligent device, where the IMU and the magnetic sensor are configured, and the smart device can be a smart device such as a smart phone, a tablet computer, a VR device, or an AR device. Referring to Figure 2, the method includes the following steps:

Step 201: When receiving the motion data collected by the IMU in the smart device at the current sampling moment, acquiring the posture of the smart device determined last time before the current sampling moment, and determining the motion device based on the motion data and the posture of the smart device determined last time. The first gesture.

According to the foregoing description, the IMU can collect three angular velocities, and the smart device can integrate the three angular velocities according to the three angular velocities and the sampling period of the IMU to determine the smart device from the last sampling moment to the current sampling moment. The amount of change in posture. Thereafter, the smart device may acquire the posture of the smart device that was last determined before the current sampling time, and determine the first posture according to the determined posture change amount and the posture of the smart device determined last time.

It should be noted that, in the embodiment of the present application, since the smart device feeds back the posture according to the time of the received motion data collected by the IMU, the posture of the smart device determined last time before the current sampling moment may be the current sampling. The attitude of the smart device determined at the last sampling moment of the moment. In some embodiments, if the smart device only receives the data collected by the IMU at the last sampling time, but does not receive the data collected by the magnetic sensor, the posture of the smart device determined at the last sampling moment may be based on the previous one. The posture calculated by the data collected by the IMU received at the sampling time may also be the posture determined according to the data collected by the IMU received at the last sampling time and the magnetic data collected last time before the last sampling time. Of course, if the data collected by the IMU and the data collected by the magnetic sensor are received at the same sampling time, the posture of the smart device determined at the last sampling moment may be the data collected by the received IMU and the magnetic sensor at the last sampling time. The acquired data determines the resulting pose.

In some embodiments, in the embodiment of the present application, the posture of the smart device may be represented by a quaternion, and in this case, the amount of posture change may also be represented by a quaternion. Assuming that the amount of change in posture is dQ, then when expressed by a quaternion, dQ = [x, y, z, w]. Among them, the smart device can calculate from x, y, z, and w by the following formulas (1)-(4).

Where ω _x , ω _y and ω _z are components of the angular velocity on three axes, respectively, and dt is the time interval between the current sampling instant and the last sampling instant.

It should be noted that, in the embodiment of the present application, the gesture can be represented not only by the quaternion but also by the Euler angle or the matrix. In the embodiment of the present application, only the quaternion is taken as an example. Explain. In practical applications, when the attitude is expressed by the Euler angle or the matrix form, the principle of determining the amount of posture change is constant, and the amount of posture change is determined by integrating the angular velocity, and the specific implementation manner can be based on the reference. The mathematical algorithms in different forms are performed, and the embodiments of the present application will not be described again.

After determining the amount of change in the posture of the smart device between the last sampling time and the current sampling time, the smart device may calculate the first posture by the following formula (5):

Q=Q ₁ *dQ (5)

Where Q is the first posture, Q ₁ is the posture of the smart device that was last determined before the current sampling time, and dQ is the posture change amount of the smart device between the last sampling time and the current sampling time determined by the foregoing formula. .

Step 202: Acquire a first magnetic force vector acquired by a magnetic sensor in the smart device.

After determining the first gesture, the smart device can acquire the first magnetic force vector acquired by the magnetic sensor in the smart device.

It should be noted that, in general, the sampling period of the magnetic sensor may be greater than the sampling period of the IMU, and may also be the same as the sampling period of the IMU. If the sampling period of the magnetic sensor is the same as the sampling period of the IMU, the data collected by the magnetic sensor can also be received while receiving the data collected by the IMU at the current sampling time. If the sampling period of the magnetic sensor is greater than the sampling period of the IMU, then there will be two cases. In the first case, the sampling period of the magnetic sensor is an integer multiple of the sampling period of the IMU, and the sampling moment of the magnetic sensor is also the sampling moment of the IMU, so that at the current sampling moment, the smart device may receive the first collection of the magnetic sensor. The magnetic vector may also not receive the first magnetic vector acquired by the magnetic sensor. The second case is that the sampling period of the magnetic sensor and the sampling period of the IMU are not integer multiples, and the sampling moment of the magnetic sensor is not necessarily the sampling moment of the IMU, so that the smart device is also likely to receive at the current sampling moment. It is also possible that the first magnetic vector acquired by the magnetic sensor does not receive the first magnetic vector acquired by the magnetic sensor. Based on the above various situations, when the smart device acquires the first magnetic force vector acquired by the magnetic sensor, it may first determine whether the magnetic force vector collected by the magnetic sensor is received at the current sampling time, if the magnetic sensor is received at the current sampling time. The magnetic vector, then, the smart device can determine the received magnetic vector as the first magnetic vector. If the magnetic force vector acquired by the magnetic sensor is not received at the current sampling time, the smart device can acquire the magnetic force vector acquired last time before the current sampling time, and use the acquired magnetic force vector as the first magnetic force vector.

It should be noted that when the magnetic sensor collects data, it is the magnetic component on the three axes acquired, and according to the three magnetic components, the first magnetic vector can be obtained.

In some embodiments, to increase the accuracy of the data acquired by the magnetic sensor, the smart device can automatically calibrate the magnetic sensor. In some embodiments, the method for automatically calibrating the magnetic sensor by the smart device may be calibrated according to the point cloud image of the magnetic sensor and the sampled data point in the related art, and the embodiment of the present application is no longer used herein. Narration.

Step 203: Find a second magnetic force vector similar to the first magnetic force vector from the stored attitude mapping table.

The gesture mapping table may be stored in the smart device, and the gesture mapping table may include at least one record or may not have any records. When multiple records are included, each record may include a magnetic force vector corresponding to the magnetic vector. The posture, or, each record may include a magnetic force vector, a posture corresponding to the magnetic force vector, and a score.

After acquiring the first magnetic force vector, the smart device may look up a second magnetic force vector similar to the first magnetic force vector from the stored attitude mapping table.

Wherein, when no record is included in the gesture mapping table, the smart device may determine that the second magnetic force vector similar to the first magnetic force vector is not found.

When at least one record is included in the gesture mapping table, for any one of the at least one record A, the smart device may acquire the magnetic force vector in the record A, and compare the acquired magnetic force vector with the first magnetic vector. It is determined whether the acquired magnetic force vector is similar to the first magnetic force vector.

In some embodiments, since each magnetic force vector is composed of three magnetic components, and based on mathematical common knowledge, the closer the two vectors are, the smaller the angle between the two vectors is. Therefore, when calculating two When the magnetic vectors are similar, the smart device can calculate the angle between the two magnetic vectors. When the angle between the acquired magnetic force vector and the first magnetic force vector is less than or equal to the preset angle, the smart device can determine that the acquired magnetic force vector is similar to the first magnetic force vector; otherwise, the acquired magnetic vector can be determined A magnetic vector is not similar. For a specific implementation manner in which the smart device calculates the angle between the two magnetic vectors, reference may be made to the related art, which is not repeatedly described in this embodiment of the present application.

It should be noted that, in the embodiment of the present application, the preset angle is a maximum angle that can be considered to be close to the two vectors, which is preset after considering the error. For example, the preset angle may be a value of 5 degrees, 3 degrees, etc., which is not specifically limited in this embodiment of the present application.

When the smart device determines that the acquired magnetic vector is similar to the first magnetic vector, the acquired magnetic vector may be used as the second magnetic vector, that is, the smart device may determine that the second magnetic vector is found in the gesture mapping table. Otherwise, the smart device can continue to compare whether the magnetic force vector in the other records in the attitude mapping table is similar to the first magnetic force vector until all the records in the attitude mapping table are compared, if the first magnetic vector is still not found. A similar second magnetic force vector, then the smart device can determine that a second magnetic force vector similar to the first magnetic force vector is not found.

If the smart device does not find the second magnetic force vector, step 204 may be performed, and if the smart device finds the second magnetic force vector, steps 205-207 may be performed.

Step 204: When the second magnetic force vector is not found, the first magnetic force vector, the first posture, and the first preset score are correspondingly stored in the gesture mapping table, and the first posture is determined as the current posture of the smart device.

Based on the foregoing description, the second magnetic force vector may not be found to include two cases. In one case, the record does not include any record, and naturally does not include the second magnetic vector similar to the first magnetic vector. This situation usually occurs when the smart device has not loaded or recorded any data at the first moment after the restart, or it may be that the smart device first starts adding records in the gesture mapping table at the time of initialization. In other words, in the embodiment of the present application, the smart device may re-establish each record in the gesture mapping table every time it is restarted, or may complete the establishment of multiple records in the gesture mapping table only during initialization. Then, when the smart device is powered off, the gesture mapping table is stored, and when the smart device is restarted, only the stored gesture mapping table can be retrieved. In another case, the stored attitude map includes at least one record, but none of the magnetic vectors in the record is similar to the first magnetic vector. In this case, the gesture map is not yet included. Recording of the first magnetic vector. However, in either case, when the second magnetic force vector is not found, it can be stated that the record containing the first magnetic force vector has not been established in the attitude mapping table, and therefore, the smart device can establish the first magnetic force vector. The record, that is, the first magnetic force vector and the first posture calculated according to the motion data collected by the IMU are stored in the gesture mapping table. Further, based on the foregoing description, the gesture mapping table may further be used to indicate a correspondence between a magnetic force vector, a posture, and a score. In this case, the smart device may set the first magnetic force vector, the first posture, and the first The preset score correspondingly is stored in the gesture mapping table.

It should be noted that, for each record in the gesture mapping table, the score in the record is used to indicate the reliability of the record. Specifically, it is used to indicate the reliability of the magnetic vector and the corresponding pose in the record. The higher the score, the higher the reliability of the record. For newly created records, since the magnetic vector and posture in the record are directly obtained from the data collected by the smart device, the reliability of all newly created records is the same, and based on this, the smart device can be newly established. The record sets an initial score, that is, a first preset score, which is the initial reliability of the newly created record, and the subsequent smart device can continuously update the score in the record, and The reliability of the record is further judged with the extension of time based on the updated score.

The first preset score may be an arbitrary value, for example, it may be 10 points, because the first preset score is equivalent to an initial reference. Further, if the upper and lower limits of the scores allowed in the gesture mapping table are set in the smart device, the first preset score may be an intermediate value of the upper and lower limits. For example, the upper limit value of the score in the gesture mapping table is 100 points, and the lower limit value is 0 minutes. Then, the first preset score may be 50 minutes. Of course, the above is only the value of several exemplary first preset scores given in the embodiment of the present application, and the first preset score may have other possibilities, and the embodiment of the present application does not do this. Specifically limited.

In addition, it is worth noting that the gesture mapping table for indicating the correspondence between the magnetic force vector, the posture, and the score may include a preset number of records, that is, the number of records included in the gesture mapping table may exist. The upper limit value, for example, can set the upper limit value of the number of records allowed in the gesture mapping table to 1000. When the number of records included in the gesture mapping table reaches the upper limit value, and the smart device determines that the newly added record is needed, the smart device may update the new record by updating or deleting the existing record in the gesture mapping table. Added to the pose map.

In some embodiments, if the stored gesture mapping table does not include any records, the smart device adds the first magnetic force vector, the first posture, and the first preset score to the gesture mapping table, which is equivalent to The first record in the gesture mapping table is established. During multiple sampling moments in the next period of time, the smart device may repeatedly perform the above steps 201-204 multiple times, thereby establishing more in the gesture mapping table. Records to get a pose map containing multiple records. Wherein, since the first posture is calculated according to the IMU, the deviation of the first posture is mainly caused by the integration of the angular velocity, and the error is gradually accumulated over time, and in the process of initially adding the recording, due to the time of the process Relatively short, therefore, the error accumulation is relatively small, and the reliability of the multiple records added to the attitude map in this period of time is also high, or, in other words, before the cumulative deviation occurs, the pose map Multiple records in the middle have been created.

When the second magnetic force vector is not found, in addition to performing the above operation, since the second magnetic force vector similar to the first magnetic force vector does not exist in the stored attitude mapping table, the corresponding second posture cannot be obtained. The first pose is corrected, so the smart device can directly determine the first pose as the current pose of the smart device.

Step 205: When the second magnetic force vector is found, the second posture is searched from the stored attitude mapping table based on the first magnetic force vector.

The manner in which the smart device determines the current pose when the second magnetic force vector is not found is described in step 204. When the second magnetic force vector similar to the first magnetic force vector is found, the smart device may acquire the posture corresponding to the second magnetic force vector from the stored attitude mapping table to obtain the third posture; when the first posture and the third posture When the similarity between the gestures is greater than the preset similarity, the score corresponding to the third gesture is updated to the first score, and the third gesture is used as the second gesture, and the first score is corresponding to the third gesture. The score of the score is increased by the second preset score; when the similarity between the first pose and the third pose is not greater than the preset similarity, the score corresponding to the third pose is updated to the second score; When the second score is greater than 0, the third gesture is used as the second gesture, and when the second score is not greater than 0, it is determined that the second gesture is not found, wherein the second score is corresponding to the third gesture. The score is reduced by the second preset score.

In some embodiments, after acquiring the posture corresponding to the second magnetic force vector, that is, the third posture, the smart device may further determine whether the first posture and the third posture are similar, thereby determining whether the third posture can be used as the second The gesture, if the third gesture can be used as the second gesture, it can be considered that the second gesture is found, otherwise, it is considered that the second gesture is not found.

In the actual application, the smaller the angle between the two postures, the more similar the two postures are, and based on the foregoing description, in the embodiment of the present application, the quaternion can be used to represent the posture, The smart device may calculate an angle between the quaternion representing the first pose and the quaternary representing the third pose, thereby characterizing the relationship between the first pose and the third pose by the magnitude of the angle Similarity. Wherein, when the gesture is represented by a quaternion, it is assumed that the first posture Q ₁ = (Q _x1 , Q _y1 , Q _z1 , Q _w1 ), and the third posture Q ₂ = (Q _x2 , Q _y2 , Q _z2 , Q _W2 ), the smart device can calculate the angle between the two poses by the following formula (6).

Where θ is the angle between the first posture and the third posture.

After determining the angle between the first posture and the third posture, the smart device may determine whether the angle is less than a preset angle, and when the angle is less than the preset angle, the smart device may determine the first posture and The similarity between the third postures is greater than the preset similarity, otherwise, it may be determined that the similarity between the first posture and the third posture is not greater than the preset similarity.

When the first posture and the third posture are similar, the smart device may update the score corresponding to the third gesture to a first score, that is, increase the score corresponding to the third gesture by a second preset score. In order to indicate the increase in the reliability of the record. At the same time, the smart device can use the third gesture as the second gesture, and at this time, the smart device can determine that the second gesture is found.

When the first posture and the third posture are not similar, the smart device may update the score corresponding to the third gesture to a second score, that is, reduce the score corresponding to the third gesture to the second preset. A score is used to indicate that the reliability of the record is declining. After updating the score corresponding to the third gesture to the second score, since the second score is reduced compared to the previous score, the smart device may further determine whether the score of the record is greater than the score. The lower limit value of the value is used to determine whether the third posture included in the record is used as the second posture to correct the first posture.

In the embodiment of the present application, the lower limit value of the score may be 0, and the smart device may determine whether the second score corresponding to the third gesture is greater than 0, and when the second score is greater than 0, the third value may be The gesture is the second gesture, that is, the smart device can determine that the second gesture is found. When the second score is not greater than 0, it indicates that the third gesture cannot be the second gesture, that is, the smart device can determine that the second gesture is not found. That is, if the second score is greater than 0, then the third pose can be considered still available. If the second score is not greater than 0, then the reliability of the record is considered to be too low, and the third gesture is no longer available. At this time, it indicates that the third gesture cannot be used as the second gesture, that is, intelligence. The device did not find the second pose in the pose mapping table. At the same time, since the reliability of the record is too low, the score is already lower than the lower limit, and the third pose is no longer available. Therefore, the smart device can set the second magnetic vector, the third pose, and the corresponding score. The strip record is deleted from the gesture mapping table, and the first magnetic force vector, the first posture and the first preset score are stored in the gesture mapping table, or the smart device can directly use the first magnetic force vector and the first posture. The record including the second magnetic force vector, the third posture, and the corresponding score in the gesture mapping table is updated with the first preset score.

It should be noted that the second preset score may be a value smaller than the first preset score. For example, the second preset score may be 1 point, that is, the score in the gesture mapping table is updated once. That is, increase or decrease by 1 point. Further, since the sampling period of the IMU data is short, that is, the interval between each adjacent two sampling moments is relatively short, based on which, if the second preset score is set to be larger, the first pre- Let the score be set relatively small with respect to the upper limit of the score. Then, when the score in a record is continuously decreased at consecutive multiple sampling times, the score in the record is in a very short time. The value will be reduced to the lower limit of the score. It can be seen that the second preset score can also be set based on comprehensively considering the first preset score, the upper limit of the score, and the lower limit of the score.

In an implementation manner, when updating the score corresponding to the third gesture, the smart device may further update according to the degree of similarity between the third gesture and the first gesture. Wherein, since the third posture and the first posture are similarly determined by calculating an angle between the two postures, the smart device can further divide the two postures according to the angle between the two postures. The degree of similarity, when the two poses are similar, the higher the degree of similarity, the more the score corresponding to the third pose increases, that is, the second preset score is larger, the degree of similarity is lower. The less the score corresponding to the third gesture is increased, that is, the second preset score is smaller. Similarly, when the two poses are not similar, if the degree of dissimilarity between the two poses is higher, the score corresponding to the third pose is reduced, that is, the second preset score is larger. The lower the degree of dissimilarity, the less the score corresponding to the third gesture is reduced, that is, the second preset score is smaller.

In some embodiments, the smart device may divide the angular range between 0 degrees and the preset angle into multiple intervals, each interval corresponding to a similarity degree and a score, and the closer to the 0 degree interval, the higher the similarity degree. The corresponding score is larger. For example, if the preset angle is α, the smart device can divide [0, α] into three intervals, respectively

with

among them,

The corresponding degree of similarity is the highest, and the corresponding score is also the largest, assuming 3 points.

Corresponding similarity is lower than

Corresponding degree of similarity, the corresponding score is also greater than

Corresponding to the score, it can be 2 points.

The corresponding similarity is the lowest, and the corresponding score is also the smallest, which can be 1 point.

If the smart device finds the second gesture by the above method, step 206 may be performed; otherwise, step 207 may be performed.

Step 206: When the second posture is found, determining the current posture of the smart device based on the first posture and the second posture.

If the smart device finds the second gesture from the stored gesture mapping table, the smart device may correct the first gesture by using the second gesture to determine the current posture of the smart device.

The smart device may obtain the second weight corresponding to the second posture, and determine the first weight based on the second weight, after which the smart device may determine the smart device based on the first posture, the first weight, the second posture, and the second weight. Current posture.

In some embodiments, the second gesture is actually a gesture acquired from the stored gesture mapping table according to the first magnetic force vector, and for the gesture acquired from the gesture mapping table, the smart device may uniformly set a fixed weight to indicate The magnitude of the effect of the second gesture in the process of correcting the first pose, this fixed weight is also the second weight, in other words, the second weight may be the preset weight.

In some embodiments, the smart device may also determine the second weight according to the score corresponding to the second gesture. Based on the foregoing description, the second gesture is actually a third gesture corresponding to the second magnetic force vector obtained from the stored gesture mapping table, and the smart device may determine the second weight according to the score corresponding to the third gesture. The higher the corresponding score, the higher the reliability of the record, that is, the higher the reliability of the second gesture. In this case, the second weight can be set correspondingly, that is, The greater the effect of the second pose in correcting the first pose. In this way, the smart device can determine the second weight corresponding to the second posture according to the reliability of the second posture. When the second posture is more reliable, the second weight is set relatively larger, so that the first posture is corrected according to the second posture. The more accurate the current posture of the obtained smart device is, the second weight is correspondingly reduced when the reliability of the second posture is low, and the influence of the second posture in the process of correcting the first posture can be reduced, thereby effectively avoiding Large deviations appear.

It should be noted that the above is only two possible methods for determining the second weight provided by the embodiment of the present application. In addition, the smart device may determine the second weight in real time by other means, for example, the smart device may be based on The magnitude of the angular velocity collected by the IMU is used to determine the speed of the movement of the smart device. When the motion is slower, the deviation of the first posture calculated by the smart device is smaller. At this time, the weight of the second posture for correcting the first posture is Can be set relatively small.

After the second weight is acquired, since the determination is made based on the first posture and the second posture when determining the current posture of the smart device, the sum of the second weight and the first weight may be 1. Based on this, the smart device can determine the first weight based on the second weight.

After determining that the first weight and the second weight are obtained, the smart device may determine the current posture of the smart device in the following two manners.

The first mode: the smart device may calculate the current posture of the smart device by using the following formulas (7) and (8) based on the first posture, the first weight, the second posture, and the second weight;

cosΩ=Q·q (8)

Where Slerp(Q,q,gain) is the current posture of the smart device, Q is the first posture, q is the second posture, gain is the second weight, (1-gain) is the first weight, and sin(·) is The sine function, cos(·) is a cosine function.

The second mode: the smart device may calculate the current posture of the smart device by using the following formula (9) based on the first posture, the first weight, the second posture, and the second weight;

Lerp(Q,q,gain)=(1-gain)×Q+gain×q (9)

Wherein, Lerp(Q, q, gain) is the current posture of the smart device, Q is the first posture, q is the second posture, gain is the second weight, and (1-gain) is the first weight.

Step 207: When the second posture is not found, the first posture is determined as the current posture of the smart device.

When the second gesture is not found in the stored gesture mapping table by step 205, it means that there is no qualified second posture in the stored gesture mapping table that can correct the first posture. In this case, the intelligence The device can directly determine the first posture as the current posture of the smart device.

In the embodiment of the present application, the smart device may determine the first posture according to the motion data collected by the IMU and the posture of the smart device determined last time, after which the smart device may extract the magnetic vector from the stored magnetic force vector based on the first magnetic force vector collected by the magnetic sensor. Finding a second gesture in the gesture mapping table of the gesture and the score. If the second gesture is found, the smart device can correct the first gesture by using the second gesture, thereby obtaining the current posture of the smart device, if not found. The second gesture, then, the smart device can directly determine the first gesture as the current posture of the smart device. Therefore, in the embodiment of the present application, the smart device does not directly calculate the second posture according to the first magnetic force vector. If the first magnetic force vector is directly used to calculate the yaw angle of the posture, since the first magnetic force vector directly participates in the operation, Therefore, the requirement of the magnetic field environment that affects the accuracy of the first magnetic force vector is very strict. In the embodiment of the present application, the first magnetic force vector is used to find the second posture according to the stored attitude mapping table, and the first magnetic vector does not need to be used. Direct participation in the calculation to obtain the second attitude, therefore, compared to the direct use of the first magnetic vector to calculate the yaw angle, the requirements for the surrounding magnetic field are more relaxed, and the application is more extensive. In addition, in the embodiment of the present application, each record in the stored gesture mapping table includes not only a magnetic force vector and a corresponding posture, but also a score for indicating the reliability of the posture corresponding to the magnetic force vector in the record, such that In the process of searching for the second posture, in the case that the first magnetic force vector is similar to the magnetic vector in the record, the corresponding score is updated by comparing the posture in the record with the first posture. Therefore, the reliability of the record is updated. When the reliability of the record does not satisfy the condition, the record can be deleted and updated in time, thereby ensuring the accuracy of the record in the pose mapping table, thereby ensuring The accuracy of the second posture for correcting the first posture found in the attitude mapping table indirectly ensures the accuracy of the current posture of the obtained smart device. In some embodiments, the smart device may further determine, according to the score, a weight occupied by the second gesture in calculating a current posture of the smart device, and when the score corresponding to the second posture is smaller, indicating that the second posture is reliable The performance is low. At this time, by reducing the weight corresponding to the second posture, the role of the second posture in determining the current posture of the smart device can be reduced, and the second posture is effectively reduced. The risk of causing a deviation in posture. When the score corresponding to the second posture is large, it indicates that the reliability of the second posture is high. At this time, by increasing the weight corresponding to the second posture, the second posture can be increased to determine the current posture of the smart device. The role played by the process, which in turn improves the accuracy of the current posture of the identified smart device.

In addition, the method for real-time updating and deleting the records in the stored gesture mapping table in the embodiment of the present application can also effectively resist the magnetic field interference, so that the smart device can adapt to the magnetic field change very well. Next, the embodiments of the present application will explain the beneficial effects of the above-mentioned anti-magnetic field interference that can be achieved by the following specific examples.

The first case: assuming that the surrounding magnetic field changes, for example, the process of change is less than 1 second (hereinafter referred to as 1 second), and then the original magnetic field is restored, that is, the smart device is subjected to extremely short time interference, and then recovered. In the original magnetic field environment. In this case, in this 1 second, due to the change of the magnetic field, the first posture calculated according to the data collected by the IMU is not similar to the second posture obtained according to the first magnetic force vector, that is, the stored attitude map. The score corresponding to the second gesture in the table will decrease in a short time, and in the process of decreasing the score corresponding to the second gesture, when the current posture of the smart device is determined based on the first posture and the second posture, The existence of the second weight, within this 1 second, even if there is an error, it will not be very large, especially when the second weight is determined according to the corresponding score, then the second gesture determines the current posture of the smart device. The weight of the process will decrease with the decrease of the score, and the disturbance of the magnetic field will have less interference to the smart device. When the original magnetic field is restored after 1 second, the score corresponding to the second posture in the stored attitude map is gradually updated, and a more accurate record conforming to the current magnetic field environment is newly established.

The second case: assuming that the surrounding magnetic field changes and does not return to the original magnetic field, but eventually stabilizes under another magnetic field. In this case, there may be an error when determining the current posture of the smart device based on the first posture and the second posture for a period of time, but due to the existence of the second weight, the error is relatively small, that is, it can be effective. Resist magnetic field interference. Moreover, since in this process, the scores in each record in the stored pose map may be reduced due to the dissimilarity of the first pose and the second pose due to the change of the magnetic field, the finally stored pose map The records in the record are gradually deleted or updated, that is, the records included in the pose mapping table are gradually updated one by one due to the change of the magnetic field, and finally the attitude map corresponding to the other magnetic field state after stabilization is obtained. It is equivalent to the smart device finally adapting to the stable magnetic field environment, and the process of adaptation is a smooth transition.

Next, an apparatus for determining a posture provided by an embodiment of the present application will be described.

Referring to FIG. 3A, an embodiment of the present application provides a device 300 for determining a posture, where the device 300 can be integrated into a smart device, where the IMU and a magnetic sensor are configured, and the smart device can be a smart phone or a tablet computer. Smart devices such as VR devices and AR devices. The device 300 includes:

The first obtaining module 301 is configured to acquire, when the motion data collected by the inertial measurement unit IMU in the smart device is received at the current sampling moment, the posture of the smart device determined last time before the current sampling moment;

The first determining module 302 is configured to determine the first posture based on the motion data and the posture of the last determined smart device;

a second acquiring module 303, configured to acquire a first magnetic force vector collected by a magnetic sensor in the smart device;

The first searching module 304 is configured to search for a second posture from the stored gesture mapping table based on the first magnetic force vector, where the gesture mapping table is used to indicate a correspondence between the magnetic force vector and the posture;

The second determining module 305 is configured to determine a current posture of the smart device based on the first posture and the second posture when the second posture is found.

In some embodiments, the second obtaining module 303 includes:

a determining sub-module, configured to determine whether a magnetic force vector acquired by the magnetic sensor is received at the current sampling time;

a first determining submodule, configured to determine the received magnetic force vector as the first magnetic force vector when the magnetic force vector acquired by the magnetic sensor is received at the current sampling moment;

The first acquiring submodule is configured to acquire a magnetic force vector acquired last time before the current sampling moment when the magnetic force vector acquired by the magnetic sensor is not received at the current sampling moment, and use the acquired magnetic force vector as the first magnetic force vector.

In some embodiments, referring to FIG. 3B, the gesture mapping table is further used to indicate a correspondence between a magnetic force vector, a posture, and a score;

The device 300 also includes:

a second searching module 306, configured to search, from the stored attitude mapping table, a second magnetic force vector similar to the first magnetic force vector;

The triggering module 307 is configured to: when the second magnetic force vector is found, trigger the first searching module to search for the second posture from the stored attitude mapping table based on the first magnetic force vector;

The third determining module 308 is configured to: when the second magnetic force vector is not found, store the first magnetic force vector, the first posture, and the first preset score in the gesture mapping table, and determine the first posture as the smart The current posture of the device.

In some embodiments, referring to FIG. 3C, the first lookup module 304 includes:

a second obtaining sub-module 3041, configured to acquire a posture corresponding to the second magnetic force vector from the attitude mapping table, to obtain a third posture;

a second determining sub-module 3042, configured to: when the similarity between the first posture and the third posture is greater than the preset similarity, update the score corresponding to the third posture to the first score, and the third posture As the second posture, the first score is obtained by increasing the score corresponding to the third gesture by a second preset score;

The sub-module 3043 is configured to: when the similarity between the first posture and the third posture is not greater than the preset similarity, update the score corresponding to the third posture to a second score, where the second score is The score corresponding to the third gesture is decreased by the second preset score;

The third determining sub-module 3044 is configured to: when the second score is greater than 0, use the third gesture as the second gesture; and when the second score is not greater than 0, determine that the second gesture is not found.

In some embodiments, the first lookup module 304 is further configured to:

Deleting the records corresponding to the second magnetic force vector, the third posture, and the third posture in the gesture mapping table, and storing the first magnetic force vector, the first posture, and the first preset score in the attitude mapping table. in.

In some embodiments, the apparatus 300 is further configured to:

When the second gesture is not found, the first gesture is determined as the current posture of the smart device.

In some embodiments, referring to FIG. 3D, the second determining module 305 includes:

The third obtaining sub-module 3051 is configured to acquire a second weight corresponding to the second posture, and determine a first weight corresponding to the first posture based on the second weight, where the second weight is a preset weight, or is corresponding to the second posture The score is determined;

The fourth determining submodule 3052 is configured to determine a current posture of the smart device based on the first posture, the first weight, the second posture, and the second weight.

In some embodiments, the fourth determining submodule 3052 is specifically configured to:

Based on the first posture, the first weight, the second posture, and the second weight, the current posture of the smart device is calculated by the following formulas (7) and (8).

Based on the first posture, the first weight, the second posture, and the second weight, the current posture of the smart device is calculated by the following formula (9).

In summary, after acquiring the first magnetic force vector, the embodiment of the present application does not directly calculate the yaw angle of the posture according to the first magnetic force vector, but uses the first magnetic force vector to determine the first according to the stored correspondence relationship. Two gestures. If the first magnetic force vector is directly used to calculate the yaw angle of the attitude, since the first magnetic force vector directly participates in the operation, the requirement of the magnetic field environment that affects the accuracy of the first magnetic vector is very strict, and in the embodiment of the present application, Determining the second posture according to the stored attitude map by using the first magnetic force vector, the first magnetic vector does not need to directly participate in the operation to obtain the second posture, and therefore, compared to directly calculating the yaw angle by using the first magnetic vector, The requirements of the surrounding magnetic field are more relaxed and applicable to a wider range of applications.

It should be noted that, when determining the posture, the apparatus for determining the posture provided by the foregoing embodiment is only illustrated by the division of each functional module, and in actual application, the function distribution may be completed by different functional modules as needed. The internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus for determining the posture provided by the foregoing embodiment is the same as the method embodiment for determining the posture, and the specific implementation process is described in detail in the method embodiment, and details are not described herein again.

FIG. 4 is a structural block diagram of a smart device 400 provided by an exemplary embodiment of the present application. The smart device 400 can be: a smart phone, a tablet computer, a VR device, an AR device, an MP3 player (Moving Picture Experts Group Audio Layer III), and a MP4 (Moving Picture Experts Group Audio Layer IV). , motion imaging experts compress the standard audio layer 4) player.

Generally, the smart device 400 includes a processor 401 and a memory 402.

Processor 401 can include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 401 can use at least one of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). achieve. The processor 401 may also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, which is also called a CPU (Central Processing Unit); the coprocessor is A low-power processor for processing data in standby. In some embodiments, the processor 401 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and rendering of content that needs to be displayed on the display screen. In some embodiments, the processor 401 may also include an AI (Artificial Intelligence) processor for processing computational operations related to machine learning.

Memory 402 can include one or more computer readable storage media, which can be non-transitory. Memory 402 can also include high speed random access memory, as well as non-volatile memory, such as one or more disk storage devices, flash storage devices. In some embodiments, the non-transitory computer readable storage medium in memory 402 is for storing at least one instruction for execution by processor 401 to implement the determined pose provided by the method embodiments of the present application. Methods.

In some embodiments, the smart device 400 also optionally includes a peripheral device interface 403 and at least one peripheral device. The processor 401, the memory 402, and the peripheral device interface 403 may be connected by a bus or a signal line. Each peripheral device can be connected to the peripheral device interface 403 via a bus, signal line or circuit board. Specifically, the peripheral device includes at least one of a radio frequency circuit 404, a display screen 405, a camera assembly 406, an audio circuit 407, a positioning component 408, and a power source 409.

The peripheral device interface 403 can be used to connect at least one peripheral device associated with an I/O (Input/Output) to the processor 401 and the memory 402. In some embodiments, processor 401, memory 402, and peripheral interface 403 are integrated on the same chip or circuit board; in some other embodiments, any of processor 401, memory 402, and peripheral interface 403 or The two can be implemented on a separate chip or circuit board, which is not limited in this embodiment.

The RF circuit 404 is configured to receive and transmit an RF (Radio Frequency) signal, also referred to as an electromagnetic signal. Radio frequency circuit 404 communicates with the communication network and other communication devices via electromagnetic signals. The RF circuit 404 converts the electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 404 includes an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and the like. Radio frequency circuitry 404 can communicate with other smart devices via at least one wireless communication protocol. The wireless communication protocols include, but are not limited to, the World Wide Web, a metropolitan area network, an intranet, generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and/or WiFi (Wireless Fidelity) networks. In some embodiments, the radio frequency circuit 404 may further include a NFC (Near Field Communication) related circuit, which is not limited in this application.

The display screen 405 is used to display a UI (User Interface). The UI can include graphics, text, icons, video, and any combination thereof. When display 405 is a touch display, display 405 also has the ability to acquire touch signals over the surface or surface of display 405. The touch signal can be input to the processor 401 for processing as a control signal. At this time, the display screen 405 can also be used to provide virtual buttons and/or virtual keyboards, also referred to as soft buttons and/or soft keyboards. In some embodiments, the display screen 405 may be one, and the front panel of the smart device 400 is disposed; in other embodiments, the display screen 405 may be at least two, respectively disposed on different surfaces of the smart device 400 or in a folded design. In still other embodiments, the display screen 405 can be a flexible display screen disposed on a curved surface or a folded surface of the smart device 400. Even the display screen 405 can be set to a non-rectangular irregular pattern, that is, a profiled screen. The display screen 405 can be prepared by using an LCD (Liquid Crystal Display) or an OLED (Organic Light-Emitting Diode).

Camera component 406 is used to capture images or video. Optionally, camera assembly 406 includes a front camera and a rear camera. Typically, the front camera is placed on the front panel of the smart device and the rear camera is placed on the back of the smart device. In some embodiments, the rear camera is at least two, which are respectively a main camera, a depth camera, a wide-angle camera, and a telephoto camera, so as to realize the background blur function of the main camera and the depth camera, and the main camera Combine with a wide-angle camera for panoramic shooting and VR (Virtual Reality) shooting or other integrated shooting functions. In some embodiments, camera assembly 406 can also include a flash. The flash can be a monochrome temperature flash or a two-color temperature flash. The two-color temperature flash is a combination of a warm flash and a cool flash that can be used for light compensation at different color temperatures.

The audio circuit 407 can include a microphone and a speaker. The microphone is used to collect sound waves of the user and the environment, and convert the sound waves into electrical signals for processing to the processor 401 for processing, or input to the RF circuit 404 for voice communication. For the purpose of stereo acquisition or noise reduction, the microphones may be multiple, and are respectively disposed at different parts of the smart device 400. The microphone can also be an array microphone or an omnidirectional acquisition microphone. The speaker is then used to convert electrical signals from the processor 401 or the RF circuit 404 into sound waves. The speaker can be a conventional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, not only can the electrical signal be converted into human audible sound waves, but also the electrical signal can be converted into sound waves that are inaudible to humans for ranging and the like. In some embodiments, audio circuit 407 can also include a headphone jack.

The location component 408 is used to locate the current geographic location of the smart device 400 to implement navigation or LBS (Location Based Service). The positioning component 408 can be a positioning component based on a US-based GPS (Global Positioning System), a Chinese Beidou system, or a Russian Galileo system.

Power source 409 is used to power various components in smart device 400. The power source 409 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power source 409 includes a rechargeable battery, the rechargeable battery may be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged by a wired line, and a wireless rechargeable battery is a battery that is charged by a wireless coil. The rechargeable battery can also be used to support fast charging technology.

In some embodiments, smart device 400 also includes one or more sensors 410. The one or more sensors 410 include, but are not limited to, an acceleration sensor 411, a gyro sensor 412, a pressure sensor 413, a fingerprint sensor 414, an optical sensor 415, a proximity sensor 416, and a magnetic sensor 417.

The acceleration sensor 411 can detect the magnitude of the acceleration on the three coordinate axes of the coordinate system established by the smart device 400. For example, the acceleration sensor 411 can be used to detect components of gravity acceleration on three coordinate axes. The processor 401 can control the touch display screen 405 to display the user interface in a landscape view or a portrait view according to the gravity acceleration signal collected by the acceleration sensor 411. The acceleration sensor 411 can also be used for the acquisition of game or user motion data.

The gyro sensor 412 can detect the body direction and the rotation angle of the smart device 400, and the gyro sensor 412 can cooperate with the acceleration sensor 411 to collect the user's 3D motion on the smart device 400. The processor 401 can realize functions such as motion sensing (such as changing the UI according to the user's tilting operation), image stabilization at the time of shooting, game control, and inertial navigation, based on the data collected by the gyro sensor 412.

The pressure sensor 413 can be disposed on a side border of the smart device 400 and/or a lower layer of the touch display screen 405. When the pressure sensor 413 is disposed on the side frame of the smart device 400, the user's holding signal to the smart device 400 can be detected, and the processor 401 performs left and right hand recognition or shortcut operation according to the holding signal collected by the pressure sensor 413. When the pressure sensor 413 is disposed on the lower layer of the touch display screen 405, the operability control on the UI interface is controlled by the processor 401 according to the user's pressure on the touch display screen 405. The operability control includes at least one of a button control, a scroll bar control, an icon control, and a menu control.

The fingerprint sensor 414 is used to collect the fingerprint of the user. The processor 401 identifies the identity of the user according to the fingerprint collected by the fingerprint sensor 414, or the fingerprint sensor 414 identifies the identity of the user according to the collected fingerprint. Upon identifying that the user's identity is a trusted identity, the processor 401 authorizes the user to perform related sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying and changing settings, and the like. The fingerprint sensor 414 can be disposed on the front, back, or side of the smart device 400. When the smart device 400 is provided with a physical button or vendor logo, the fingerprint sensor 414 can be integrated with a physical button or vendor logo.

Optical sensor 415 is used to collect ambient light intensity. In one embodiment, the processor 401 can control the display brightness of the touch display screen 405 based on the ambient light intensity acquired by the optical sensor 415. Specifically, when the ambient light intensity is high, the display brightness of the touch display screen 405 is raised; when the ambient light intensity is low, the display brightness of the touch display screen 405 is lowered. In another embodiment, the processor 401 can also dynamically adjust the shooting parameters of the camera assembly 406 based on the ambient light intensity acquired by the optical sensor 415.

Proximity sensor 416, also referred to as a distance sensor, is typically disposed on the front panel of smart device 400. Proximity sensor 416 is used to capture the distance between the user and the front of smart device 400. In one embodiment, when the proximity sensor 416 detects that the distance between the user and the front of the smart device 400 is getting smaller, the touch screen 405 is controlled by the processor 401 to switch from the bright screen state to the touch screen state; when the proximity sensor 416 When it is detected that the distance between the user and the front side of the smart device 400 gradually becomes larger, the processor 401 controls the touch display screen 405 to switch from the state of the screen to the bright state.

The magnetic sensor 417, also called geomagnetic and magnetic sensor, can detect the magnetic field strength and direction of the environment in which the smart device 400 is located. In the embodiment of the present application, the acceleration sensor 411, the gyro sensor 412, and the magnetic sensor 417 may be combined to determine the current posture of the smart device.

Those skilled in the art will appreciate that the structure illustrated in FIG. 4 does not constitute a limitation to smart device 400, may include more or fewer components than illustrated, or may combine certain components, or employ different component arrangements.

The embodiment of the present application provides a computer readable storage medium having instructions stored thereon, the instructions being executed by a processor to implement the steps of any of the foregoing method embodiments.

The embodiment of the present application provides a computer program product that, when run on a computer, causes the computer to perform the steps of any of the above method embodiments.

A person skilled in the art may understand that all or part of the steps of implementing the above embodiments may be completed by hardware, or may be instructed by a program to execute related hardware, and the program may be stored in a computer readable storage medium. The storage medium mentioned may be a read only memory, a magnetic disk or an optical disk or the like.

The above is only the preferred embodiment of the present application, and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application are included in the protection of the present application. Within the scope.

Claims

A method for determining a posture, the method comprising:

Obtaining, when the motion data collected by the inertial measurement unit IMU in the smart device is received at the current sampling moment, the posture of the smart device that was last determined before the current sampling time, and determining based on the motion data and the last time The posture of the smart device determines a first posture;

Obtaining a first magnetic force vector acquired by a magnetic sensor in the smart device, and searching for a second posture from the stored attitude mapping table based on the first magnetic force vector, the gesture mapping table is used to indicate a magnetic force vector and a posture Correspondence between

When the second gesture is found, the current posture of the smart device is determined based on the first posture and the second posture.
The method according to claim 1, wherein the acquiring the first magnetic force vector collected by the magnetic sensor in the smart device comprises:

Determining whether a magnetic force vector acquired by the magnetic sensor is received at a current sampling time;

When the magnetic force vector acquired by the magnetic sensor is received at the current sampling moment, the received magnetic force vector is determined as the first magnetic force vector;

When the magnetic force vector acquired by the magnetic sensor is not received at the current sampling time, the magnetic force vector acquired last time before the current sampling time is acquired, and the acquired magnetic force vector is taken as the first magnetic force vector.
The method according to claim 1, wherein the gesture mapping table is further configured to indicate a correspondence between a magnetic force vector, a posture and a score; and the gesture map based on the first magnetic force vector is stored. Before looking for the second pose, it also includes:

Finding a second magnetic force vector similar to the first magnetic force vector from the attitude mapping table;

And when the second magnetic force vector is found, performing the step of searching for a second posture from the stored attitude mapping table based on the first magnetic force vector;

When the second magnetic force vector is not found, the first magnetic force vector, the first posture, and the first preset score are correspondingly stored in the attitude mapping table, and the first posture is determined. The current posture of the smart device.
The method according to claim 3, wherein the finding the second gesture from the stored gesture mapping table based on the first magnetic force vector comprises:

Acquiring a posture corresponding to the second magnetic force vector from the attitude mapping table to obtain a third posture;

When the similarity between the first posture and the third posture is greater than a preset similarity, updating the score corresponding to the third posture to a first score, and using the third gesture as In the second posture, the first score is obtained by adding a score corresponding to the third gesture to a second preset score;

When the similarity between the first posture and the third posture is not greater than the preset similarity, updating the score corresponding to the third posture to a second score, the second score The value is obtained by decreasing the score corresponding to the third gesture by the second preset score;

When the second score is greater than 0, the third gesture is taken as the second gesture;

When the second score is not greater than 0, it is determined that the second gesture is not found.
The method according to claim 4, wherein after the determining does not find the second gesture, the method further comprises:

Deleting the records in the gesture mapping table by the scores corresponding to the second magnetic force vector, the third posture, and the third posture, and the first magnetic force vector, the first posture and The first preset score is correspondingly stored in the gesture mapping table.
The method according to any one of claims 1-5, wherein after the searching for the second gesture from the stored posture and the mapping table based on the first magnetic force vector, the method further comprises:

When the second gesture is not found, the first gesture is determined as the current posture of the smart device.
The method according to any one of claims 1-5, wherein the determining the current posture of the smart device based on the first posture and the second posture comprises:

Obtaining a second weight corresponding to the second posture, and determining, according to the second weight, a first weight corresponding to the first posture, where the second weight is a preset weight, or corresponding to the second posture The score is determined;

Determining a current posture of the smart device based on the first posture, the first weight, the second posture, and the second weight.
The method according to claim 7, wherein the determining the current posture of the smart device based on the first posture, the first weight, the second posture, and the second weight comprises :

Calculating a current posture of the smart device by using a formula according to the first posture, the first weight, the second posture, and the second weight;

cosΩ=Q·q

The Slerp (Q, q, gain) is the current posture of the smart device, the Q is the first posture, the q is the second posture, and the gain is the second weight The (1-gain) is the first weight, sin(·) is a sine function, and cos(·) is a cosine function.
The method according to claim 7, wherein the determining the current posture of the smart device based on the first posture, the first weight, the second posture, and the second weight comprises :

Calculating a current posture of the smart device by using a formula according to the first posture, the first weight, the second posture, and the second weight;

Lerp(Q,q,gain)=(1-gain)×Q+gain×q

The Lerp (Q, q, gain) is the current posture of the smart device, the Q is the first posture, the q is the second posture, and the gain is the second weight The (1-gain) is the first weight.
A device for determining a posture, characterized in that the device comprises:

a first acquiring module, configured to acquire, when the motion data collected by the inertial measurement unit IMU in the smart device is received at the current sampling moment, the posture of the smart device that is determined last time before the current sampling moment;

a first determining module, configured to determine a first posture based on the motion data and the posture of the smart device that is last determined;

a second acquiring module, configured to acquire a first magnetic force vector collected by a magnetic sensor in the smart device;

a first searching module, configured to search, according to the first magnetic force vector, a second posture from a stored attitude mapping table, where the gesture mapping table is used to indicate a correspondence between a magnetic force vector and a posture;

And a second determining module, configured to determine a current posture of the smart device based on the first posture and the second posture when the second posture is found.
The apparatus according to claim 10, wherein the second obtaining module comprises:

a determining submodule, configured to determine whether a magnetic force vector acquired by the magnetic sensor is received at a current sampling time;

a first determining submodule, configured to determine the received magnetic force vector as the first magnetic force vector when receiving the magnetic force vector acquired by the magnetic sensor at the current sampling moment;

a first acquiring submodule, configured to: when the magnetic force vector acquired by the magnetic sensor is not received at the current sampling moment, acquire a magnetic force vector acquired last time before the current sampling time, and use the acquired magnetic force vector as the first A magnetic vector.
The apparatus according to claim 10, wherein the gesture mapping table is further configured to indicate a correspondence between a magnetic force vector, a posture, and a score;

The device also includes:

a second searching module, configured to search, from the gesture mapping table, a second magnetic force vector similar to the first magnetic force vector;

a triggering module, configured to: when the second magnetic force vector is found, trigger the second determining module to search for a second posture from the stored attitude mapping table based on the first magnetic force vector;

a third determining module, configured to: when the second magnetic force vector is not found, store the first magnetic force vector, the first posture, and the first preset score in the gesture mapping table, and The first posture is determined as the current posture of the smart device.
The device according to claim 12, wherein the first lookup module comprises:

a second acquiring submodule, configured to acquire a posture corresponding to the second magnetic force vector from the stored attitude mapping table, to obtain a third posture;

a second determining submodule, configured to update a score corresponding to the third gesture to a first score when a similarity between the first gesture and the third gesture is greater than a preset similarity, And the third gesture is used as the second posture, and the first score is obtained by adding a score corresponding to the third gesture to a second preset score;

a sub-module, configured to update a score corresponding to the third gesture to a second score when a similarity between the first gesture and the third gesture is not greater than the preset similarity The second score is obtained by reducing the score corresponding to the third gesture by the second preset score;

a third determining submodule, configured to: when the second score is greater than 0, use the third gesture as the second gesture; when the second score is not greater than 0, determine that the The second gesture.
The device according to claim 13, wherein the first search module is further configured to:

Deleting the records in the gesture mapping table by the scores corresponding to the second magnetic force vector, the third posture, and the third posture, and the first magnetic force vector, the first posture and The first preset score is correspondingly stored in the gesture mapping table.
A smart device, characterized in that the smart device comprises:

IMU for collecting motion data;

a magnetic sensor for acquiring a magnetic force vector;

processor;

a memory for storing the processor executable instructions;

Wherein the processor is configured as the steps of any of the methods of claims 1-9.
A computer readable storage medium, wherein the computer readable storage medium stores instructions that, when executed by a processor, perform the steps of the method of any of the preceding claims 1-9.
A computer program product, wherein the computer program product, when run on a computer, causes the computer to perform the steps of the method of any of the preceding claims 1-9.