CN114157950A - Head movement detection method, smart headset, and computer-readable storage medium - Google Patents
Head movement detection method, smart headset, and computer-readable storage medium Download PDFInfo
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- 230000009471 action Effects 0.000 claims abstract description 54
- 238000006073 displacement reaction Methods 0.000 claims abstract description 30
- 230000003993 interaction Effects 0.000 claims abstract description 23
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- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
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Abstract
The invention discloses a head movement detection method, an intelligent earphone and a computer readable storage medium, wherein the method comprises the following steps: the method comprises the steps of calibrating preset precision of an intelligent earphone and confirming that a user wears the intelligent earphone; dynamically reading and recording first position data of the intelligent earphone, and detecting whether a preset action trigger interrupt exists or not based on the recorded first position data each time; when the preset action trigger interruption is detected, reading and recording second position data of the intelligent earphone; performing difference calculation according to the first position data and the second position data of the same time sequence to obtain displacement data; and carrying out data analysis on a plurality of displacement data recorded in a preset time length and the first position data and the second position data corresponding to the time sequence to obtain the head movement action of the user in the preset time length. By implementing the invention, the collection of the head action of the user is realized, and a brand-new man-machine interaction mode is further provided.
Description
Technical Field
The present invention relates to the field of headset technology, and in particular, to a head movement detection method, an intelligent headset, and a computer-readable storage medium.
Background
Currently, wireless headsets have taken a large share in the smart wearable device market by virtue of their fashionable appearance and high quality processing of audio. However, at present, the man-machine interaction of most earphones is limited to functions such as AI voice recognition, touch function recognition and the like.
However, in many scenarios, users may want more human-computer interaction functions, for example, when it is inconvenient to free hands or voice control is not effective, the need for implementing human-computer interaction through earphones is more urgent.
Disclosure of Invention
The invention mainly aims to provide a head movement detection method, an intelligent headset and a computer readable storage medium, and aims to solve the technical problem of capturing head movements of a user to realize human-computer interaction.
In order to achieve the above object, the present invention provides a head movement detection method, including the steps of:
the method comprises the steps of calibrating preset precision of an intelligent earphone, and confirming that the intelligent earphone is worn by a current interactive object of the intelligent earphone;
dynamically reading and recording first position data of the intelligent earphone, and detecting whether a preset action trigger interrupt exists or not based on the recorded first position data each time;
when the preset action trigger interruption is detected, reading and recording second position data of the intelligent earphone;
performing difference calculation according to the first position data and the second position data of the same time sequence to obtain displacement data;
and performing data analysis on a plurality of displacement data recorded in a preset time length and the first position data and the second position data corresponding to the time sequence to acquire the head movement action of the current interactive object of the intelligent earphone in the preset time length.
Optionally, the position data of the smart headset includes an accelerometer value and a gyroscope value, and the step of reading the position data of the smart headset includes:
reading the value of an accelerometer and the value of a gyroscope in the intelligent earphone;
the step of reading the value of the accelerometer and the value of the gyroscope in the smart headset then comprises:
and substituting the value of the accelerometer and the value of the gyroscope into a preset rotation algorithm to obtain the head rotation angle of the current interactive object of the intelligent earphone.
Optionally, the step of performing data analysis on the plurality of displacement data recorded within the preset time period and the first position data and the second position data corresponding to the time sequence to obtain the head movement of the current interaction object of the smart headset within the preset time period includes:
and carrying out track recognition on the plurality of displacement data and the plurality of head rotating angles recorded in the preset time length to obtain a track recognition result, and taking the track recognition result as the head movement action of the current interaction object of the intelligent earphone in the preset time length.
Optionally, the smart headset includes a preset chip, the preset chip includes an accelerometer and a gyroscope, and the step of calibrating the preset precision of the smart headset includes:
initializing and setting preset parameters in the preset chip;
and calibrating the preset precision of the accelerometer and the gyroscope according to the preset parameters.
Optionally, the step of calibrating the accelerometer with a preset accuracy includes:
initializing the accelerometer, and reading corresponding X-axis position data and Y-axis position data according to the preset parameters;
respectively calculating according to the X-axis position data and the Y-axis position data to obtain an average value and a standard deviation;
and substituting the average value and the standard deviation into a preset matrix formula to calculate a calibration value.
Optionally, the step of calibrating the gyroscope with a preset precision includes:
initializing the gyroscope, and reading corresponding X-axis rotation data and Y-axis rotation data according to the preset parameters;
respectively calculating according to the X-axis rotation data and the Y-axis rotation data to obtain an average value and a standard deviation;
and substituting the average value and the standard deviation into a preset matrix formula to calculate a calibration value.
Optionally, the step of calibrating the accelerometer and the gyroscope with the preset precision according to the preset parameter includes:
and after the preset precision calibration of the accelerometer and the gyroscope is finished, storing the calibration value into a preset storage space.
Optionally, after the step of detecting whether there is a preset action-triggered interrupt, the method further includes:
and when the preset action trigger interruption is not detected, executing the step of dynamically reading and recording the first position data of the intelligent earphone.
In addition, to achieve the above object, the present invention also provides an intelligent headset, including: a memory, a processor and a head motion detection program stored on the memory and executable on the processor, the head motion detection program when executed by the processor implementing the steps of the head motion detection method as described above.
Further, to achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a head movement detection program which, when executed by a processor, implements the steps of the head movement detection method as described above.
The invention provides a head movement detection method, an intelligent earphone and a computer readable storage medium, wherein in the head movement detection method, preset precision calibration is carried out on the intelligent earphone, then the current interactive object of the intelligent earphone is confirmed to wear the intelligent earphone, then first position data of the intelligent earphone is dynamically read and recorded, whether preset action triggering interruption exists or not is detected based on the first position data recorded each time, when the preset action triggering interruption is detected, second position data of the intelligent earphone is read and recorded, difference value calculation is carried out according to the first position data and the second position data of the same time sequence to obtain displacement data, and data analysis is carried out on a plurality of pieces of displacement data recorded in a preset time length and the first position data and the second position data of corresponding time sequences, the head movement action of the current interaction object of the intelligent headset within the preset time is obtained, the head action of the user is collected, a brand-new man-machine interaction mode is further provided, the head action of the user can be used as an instruction for the intelligent headset or other related equipment, and the use experience of the user is improved.
Drawings
Fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a head movement detection method according to a first embodiment of the present invention;
FIG. 3 is a schematic diagram of a gyroscope for detecting rotation angle according to the head movement detection method of the present invention;
fig. 4 is a flowchart illustrating a head movement detection method according to a second embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The main solution of the embodiment of the invention is as follows: a head motion detection method, comprising the steps of:
the method comprises the steps of calibrating preset precision of an intelligent earphone, and confirming that the intelligent earphone is worn by a current interactive object of the intelligent earphone;
dynamically reading and recording first position data of the intelligent earphone, and detecting whether a preset action trigger interrupt exists or not based on the recorded first position data each time;
when the preset action trigger interruption is detected, reading and recording second position data of the intelligent earphone;
performing difference calculation according to the first position data and the second position data of the same time sequence to obtain displacement data;
and performing data analysis on a plurality of displacement data recorded in a preset time length and the first position data and the second position data corresponding to the time sequence to acquire the head movement action of the current interactive object of the intelligent earphone in the preset time length.
At present, the human-computer interaction of most earphones is limited to functions such as AI voice recognition and touch function recognition, but in many scenes, users may want to have more human-computer interaction functions, for example, when hands are not convenient to free for operation or voice control is not effective, the need of realizing human-computer interaction through the earphones is more urgent.
The invention provides a head movement detection method, which can acquire the head movement action of the current interactive object of an intelligent earphone within a preset time length by implementing the head movement detection method, realizes the acquisition of the head action of a user, further provides a brand new man-machine interaction mode, can issue an instruction to the intelligent earphone or other associated equipment according to the head action of the user, and improves the use experience of the user.
As shown in fig. 1, fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present invention.
The terminal of the embodiment of the invention can be an intelligent earphone, and can also be a movable terminal device worn on the head, such as a wireless earphone, a Bluetooth earphone, a TWS earphone and the like.
As shown in fig. 1, the terminal may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may comprise interactive keys and the optional user interface 1003 may also comprise a standard wired, wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the terminal may further include RF (Radio Frequency) circuits, sensors, audio circuits, WiFi modules, and the like. Such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that may adjust the brightness of the display screen according to the brightness of ambient light, and a proximity sensor that may turn off the display screen and/or the backlight when the mobile terminal is moved to the ear. As one of the motion sensors, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally, three axes), detect the magnitude and direction of gravity when the mobile terminal is stationary, and can be used for applications (such as horizontal and vertical screen switching, related games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer and tapping) and the like for recognizing the attitude of the mobile terminal; of course, the mobile terminal may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which are not described herein again.
Those skilled in the art will appreciate that the terminal structure shown in fig. 1 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a head movement detection program.
In the terminal shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to invoke a head motion detection program stored in the memory 1005 and perform the following operations:
the method comprises the steps of calibrating preset precision of an intelligent earphone, and confirming that the intelligent earphone is worn by a current interactive object of the intelligent earphone;
dynamically reading and recording first position data of the intelligent earphone, and detecting whether a preset action trigger interrupt exists or not based on the recorded first position data each time;
when the preset action trigger interruption is detected, reading and recording second position data of the intelligent earphone;
performing difference calculation according to the first position data and the second position data of the same time sequence to obtain displacement data;
and performing data analysis on a plurality of displacement data recorded in a preset time length and the first position data and the second position data corresponding to the time sequence to acquire the head movement action of the current interactive object of the intelligent earphone in the preset time length.
Further, the processor 1001 may call a head motion detection program stored in the memory 1005, and also perform the following operations:
the position data of the smart headset comprises an accelerometer value and a gyroscope value, and the step of reading the position data of the smart headset comprises:
reading the value of an accelerometer and the value of a gyroscope in the intelligent earphone;
further, the processor 1001 may call a head motion detection program stored in the memory 1005, and also perform the following operations:
and substituting the value of the accelerometer and the value of the gyroscope into a preset rotation algorithm to obtain the head rotation angle of the current interactive object of the intelligent earphone.
Further, the processor 1001 may call a head motion detection program stored in the memory 1005, and also perform the following operations:
the step of performing data analysis on the plurality of displacement data recorded within the preset time length and the first position data and the second position data corresponding to the time sequence to obtain the head movement action of the current interaction object of the intelligent headset within the preset time length comprises the following steps:
and carrying out track recognition on the plurality of displacement data and the plurality of head rotating angles recorded in the preset time length to obtain a track recognition result, and taking the track recognition result as the head movement action of the current interaction object of the intelligent earphone in the preset time length.
Further, the processor 1001 may call a head motion detection program stored in the memory 1005, and also perform the following operations:
the intelligent earphone comprises a preset chip, the preset chip comprises an accelerometer and a gyroscope, and the step of calibrating the preset precision of the intelligent earphone comprises the following steps:
initializing and setting preset parameters in the preset chip;
and calibrating the preset precision of the accelerometer and the gyroscope according to the preset parameters.
Further, the processor 1001 may call a head motion detection program stored in the memory 1005, and also perform the following operations:
initializing the accelerometer, and reading corresponding X-axis position data and Y-axis position data according to the preset parameters;
respectively calculating according to the X-axis position data and the Y-axis position data to obtain an average value and a standard deviation;
and substituting the average value and the standard deviation into a preset matrix formula to calculate a calibration value.
Further, the processor 1001 may call a head motion detection program stored in the memory 1005, and also perform the following operations:
initializing the gyroscope, and reading corresponding X-axis rotation data and Y-axis rotation data according to the preset parameters;
respectively calculating according to the X-axis rotation data and the Y-axis rotation data to obtain an average value and a standard deviation;
and substituting the average value and the standard deviation into a preset matrix formula to calculate a calibration value.
Further, the processor 1001 may call a head motion detection program stored in the memory 1005, and also perform the following operations:
and after the preset precision calibration of the accelerometer and the gyroscope is finished, storing the calibration value into a preset storage space.
Further, the processor 1001 may call a head motion detection program stored in the memory 1005, and also perform the following operations:
and when the preset action trigger interruption is not detected, executing the step of dynamically reading and recording the first position data of the intelligent earphone.
Referring to fig. 2, a first embodiment of the present invention provides a head movement detection method including:
step S10, calibrating the preset precision of the intelligent earphone, and confirming that the intelligent earphone is worn by the current interactive object of the intelligent earphone;
the executing subject of this embodiment is a smart headset, which may be a smart headset, such as a Wireless headset, a bluetooth headset, a TWS (True Wireless Stereo) headset, etc., for convenience of description, the smart headset may be replaced by a headset hereinafter, but this does not represent a limitation to this embodiment.
It should be noted that the current interaction object of the smart headset is a user wearing the headset.
It can be understood that, in order to ensure accurate detection of the head movement of the user, after the headset enters the head movement detection state, the headset needs to be precisely calibrated, and meanwhile, it needs to be confirmed that the headset is worn by the user.
Step S20, dynamically reading and recording first position data of the intelligent headset, and detecting whether a preset action triggering interruption exists or not based on the first position data recorded each time;
it should be noted that the first position data of the smart headset may be used to represent the current position data of the headset, and may also be used to represent the current head position data of the user. The step of reading and recording the first position data is performed dynamically, i.e. the reading and recording of the position data is performed all the time after the headset enters the head movement detection state.
Step S30, when the preset action trigger interruption is detected, reading and recording second position data of the intelligent headset;
it should be noted that the preset action trigger interrupt is used to determine whether a user generates a large head action, and the trigger condition may be set according to a requirement, for example, a mode for sensitivity adjustment may be set. When the earphone detects that the preset action is triggered to be interrupted, the earphone indicates that the head action of the user reaches a preset detection threshold, and at the moment, reading and recording of second position data are needed, wherein the second position data have a similar meaning to that of the first position data for representation.
Step S40, calculating the difference value according to the first position data and the second position data of the same time sequence to obtain displacement data;
it can be understood that, because the collection of the first position data is dynamic, and the second position data is obtained only when the head movement of the user reaches a preset detection threshold, it is necessary to ensure that the time sequence of the first position data corresponds to the time sequence of the second position data to accurately reflect the head position change of the user, and therefore, the displacement difference value obtained by performing difference value calculation according to the first position data and the second position data of the same time sequence is the data capable of accurately reflecting the head displacement distance of the user.
Step S50, performing data analysis on the plurality of displacement data recorded within the preset time period and the first position data and the second position data corresponding to the time sequence, and acquiring the head movement of the current interaction object of the smart headset within the preset time period.
It should be noted that the preset time period may be set according to actual requirements, and may be 5 seconds, 10 seconds, 15 seconds, or the like, which is not limited in this embodiment.
It can be understood that the accurate intention of the user cannot be known only from a few data, and the head movement of the user in a certain time period can be known only by performing data analysis on the first position data and the second position data of a plurality of corresponding time sequences within a certain time period.
In this embodiment, the position data of the smart headset includes an accelerometer value and a gyroscope value, and after step S30, the method includes:
and substituting the value of the accelerometer and the value of the gyroscope into a preset rotation algorithm to obtain the head rotation angle of the current interactive object of the intelligent earphone.
It should be noted that the position data of the smart headset is a data value collected by an accelerometer and a gyroscope in an IMU (Inertial Measurement Unit) chip preset inside the smart headset.
Regarding the accelerometer, when its sensing direction is consistent with the gravity acceleration direction, it is determined that the device is in a horizontal state, the acceleration measured at this time is the gravity acceleration g, and when its sensing direction is deviated by an angle θ, the acceleration value measured by the test is F (θ) ═ g cos θ.
Regarding the gyroscope, when the user wears the headset to perform a head turning motion, the head turning motion can be simulated into a coordinate system rotating around the Z axis as shown in fig. 3, where a solid line coordinate system X, Y, and Z are initial coordinate systems, a new dotted line coordinate system X, Y, and Z is obtained after the head turning, and the rotation angle is θ, it can be known from the related knowledge of linear algebra that a matrix of 3 × 3 can express the rotation of an object, for example, the rotation around the Z axis we can express the following (i.e. the preset rotation algorithm):
Therefore, the value of M can be reversely deduced only by reading the values of the accelerometer and the gyroscope at the initial position, and the turning angle is further obtained.
In this embodiment, step S50 includes:
and carrying out track recognition on the plurality of displacement data and the plurality of head rotating angles recorded in the preset time length to obtain a track recognition result, and taking the track recognition result as the head movement action of the current interaction object of the intelligent earphone in the preset time length.
It can be understood that if a user head trajectory is desired, the rotation angle of the headset and the displacement deviation from the original position need to be read according to a certain time sequence, accelerometer and gyroscope data of the device are read for multiple times within a certain time period, and the data points of each time sequence are connected into a line, so that the head movement action of the user within the time period can be obtained.
In the present embodiment, there is provided a head movement detection method in which, firstly, the preset precision calibration is carried out on the intelligent earphone, then the current interactive object of the intelligent earphone is confirmed to be worn by the intelligent earphone, then dynamically reading and recording first position data of the intelligent earphone, detecting whether a preset action trigger interrupt exists or not based on the first position data recorded each time, reading and recording second position data of the intelligent earphone when detecting that the preset action is triggered to be interrupted, performing difference calculation according to the first position data and the second position data of the same time sequence to obtain displacement data, and acquiring the head movement action of the current interactive object of the intelligent earphone within the preset time length by carrying out data analysis on a plurality of displacement data recorded within the preset time length and the first position data and the second position data corresponding to the time sequence. This embodiment uses accelerometer and gyroscope cooperation, and the multiple spot reads the equipment position fast, simulates out User's head orbit, and in the use, the User can set up UI (User Interface), uses the head action to come operating device, or simulates the head action and reaches man-machine interaction's purpose, can be according to User's head action to do intelligent earphone or other relevant equipment assign the instruction, show the use that has promoted the User and experienced.
Further, referring to fig. 4, a second embodiment of the head movement detection method according to the present invention is provided, based on the embodiment shown in fig. 2, where the smart headset includes a preset chip, the preset chip includes an accelerometer and a gyroscope, and the step of calibrating the preset precision of the smart headset in step S10 includes:
step S11, initializing the preset parameters in the preset chip;
and step S12, calibrating the accelerometer and the gyroscope according to the preset parameters.
In this embodiment, step S12 includes:
initializing the accelerometer, and reading corresponding X-axis position data and Y-axis position data according to the preset parameters; respectively calculating according to the X-axis position data and the Y-axis position data to obtain an average value and a standard deviation; and substituting the average value and the standard deviation into a preset matrix formula to calculate a calibration value.
Initializing the gyroscope, and reading corresponding X-axis rotation data and Y-axis rotation data according to the preset parameters; respectively calculating according to the X-axis rotation data and the Y-axis rotation data to obtain an average value and a standard deviation; and substituting the average value and the standard deviation into a preset matrix formula to calculate a calibration value.
In this embodiment, step S12 includes the following steps:
and step S13, after finishing the calibration of the accelerometer and the gyroscope with preset precision, storing the calibration value into a preset storage space.
It should be noted that the preset chip is the IMU chip preset in the intelligent headset mentioned in the first embodiment, the preset parameters may be parameters such as product reading rate and precision, and the initialized rate value and precision value may be determined according to actual requirements.
In this embodiment, the precision calibration of the accelerometer and the gyroscope will refer to the precision values of the initialization setting, and the read data amounts are different according to different set precisions, where the read data in this embodiment is 1s of data, and finally, the calibration values of the two measurement devices are calculated according to a preset matrix formula, and finally, the calibration values are written into a preset storage space so as to remove errors after each detection.
This embodiment carries out the precision calibration through accelerometer and the gyroscope to among the chip of predetermineeing, can further guarantee the accuracy that detects, reduces the error that assembly, environment caused, and the error is so that get rid of the error in the automatic after detecting at every turn in the value of storing the calibration after the calibration. According to the method, data are acquired through an IMU chip preset in the earphone, the motion track of the current head of a user is identified through analysis of data such as ACC (accelerometer), Gyro (gyroscope) and the like, action analysis is achieved, and therefore participation and experience of the user are improved.
Furthermore, an embodiment of the present invention further provides a computer-readable storage medium, where a head movement detection program is stored on the computer-readable storage medium, and when executed by a processor, the head movement detection program implements the following operations:
the method comprises the steps of calibrating preset precision of an intelligent earphone, and confirming that the intelligent earphone is worn by a current interactive object of the intelligent earphone;
dynamically reading and recording first position data of the intelligent earphone, and detecting whether a preset action trigger interrupt exists or not based on the recorded first position data each time;
when the preset action trigger interruption is detected, reading and recording second position data of the intelligent earphone;
performing difference calculation according to the first position data and the second position data of the same time sequence to obtain displacement data;
and performing data analysis on a plurality of displacement data recorded in a preset time length and the first position data and the second position data corresponding to the time sequence to acquire the head movement action of the current interactive object of the intelligent earphone in the preset time length.
Further, the head motion detection program when executed by the processor further performs the following operations:
the position data of the smart headset comprises an accelerometer value and a gyroscope value, and the step of reading the position data of the smart headset comprises:
reading the value of an accelerometer and the value of a gyroscope in the intelligent earphone;
further, the head motion detection program when executed by the processor further performs the following operations:
and substituting the value of the accelerometer and the value of the gyroscope into a preset rotation algorithm to obtain the head rotation angle of the current interactive object of the intelligent earphone.
Further, the head motion detection program when executed by the processor further performs the following operations:
the step of performing data analysis on the plurality of displacement data recorded within the preset time length and the first position data and the second position data corresponding to the time sequence to obtain the head movement action of the current interaction object of the intelligent headset within the preset time length comprises the following steps:
and carrying out track recognition on the plurality of displacement data and the plurality of head rotating angles recorded in the preset time length to obtain a track recognition result, and taking the track recognition result as the head movement action of the current interaction object of the intelligent earphone in the preset time length.
Further, the head motion detection program when executed by the processor further performs the following operations:
the intelligent earphone comprises a preset chip, the preset chip comprises an accelerometer and a gyroscope, and the step of calibrating the preset precision of the intelligent earphone comprises the following steps:
initializing and setting preset parameters in the preset chip;
and calibrating the preset precision of the accelerometer and the gyroscope according to the preset parameters.
Further, the head motion detection program when executed by the processor further performs the following operations:
initializing the accelerometer, and reading corresponding X-axis position data and Y-axis position data according to the preset parameters;
respectively calculating according to the X-axis position data and the Y-axis position data to obtain an average value and a standard deviation;
and substituting the average value and the standard deviation into a preset matrix formula to calculate a calibration value.
Further, the head motion detection program when executed by the processor further performs the following operations:
initializing the gyroscope, and reading corresponding X-axis rotation data and Y-axis rotation data according to the preset parameters;
respectively calculating according to the X-axis rotation data and the Y-axis rotation data to obtain an average value and a standard deviation;
and substituting the average value and the standard deviation into a preset matrix formula to calculate a calibration value.
Further, the head motion detection program when executed by the processor further performs the following operations:
and after the preset precision calibration of the accelerometer and the gyroscope is finished, storing the calibration value into a preset storage space.
Further, the head motion detection program when executed by the processor further performs the following operations:
and when the preset action trigger interruption is not detected, executing the step of dynamically reading and recording the first position data of the intelligent earphone.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A head motion detection method, characterized by comprising the steps of:
the method comprises the steps of calibrating preset precision of an intelligent earphone, and confirming that the intelligent earphone is worn by a current interactive object of the intelligent earphone;
dynamically reading and recording first position data of the intelligent earphone, and detecting whether a preset action trigger interrupt exists or not based on the recorded first position data each time;
when the preset action trigger interruption is detected, reading and recording second position data of the intelligent earphone;
performing difference calculation according to the first position data and the second position data of the same time sequence to obtain displacement data;
and performing data analysis on a plurality of displacement data recorded in a preset time length and the first position data and the second position data corresponding to the time sequence to acquire the head movement action of the current interactive object of the intelligent earphone in the preset time length.
2. The head motion detection method of claim 1, wherein the position data of the smart headset comprises values of an accelerometer and values of a gyroscope, and the step of reading the position data of the smart headset comprises:
reading the value of an accelerometer and the value of a gyroscope in the intelligent earphone;
the step of reading the value of the accelerometer and the value of the gyroscope in the smart headset then comprises:
and substituting the value of the accelerometer and the value of the gyroscope into a preset rotation algorithm to obtain the head rotation angle of the current interactive object of the intelligent earphone.
3. The head movement detection method according to claim 2, wherein the step of performing data analysis on the plurality of displacement data recorded within a preset time period and the first position data and the second position data of the corresponding time sequence to obtain the head movement action of the current interaction object of the smart headset within the preset time period comprises:
and carrying out track recognition on the plurality of displacement data and the plurality of head rotating angles recorded in the preset time length to obtain a track recognition result, and taking the track recognition result as the head movement action of the current interaction object of the intelligent earphone in the preset time length.
4. The head movement detection method according to claim 3, wherein the smart headset comprises a preset chip, the preset chip comprises an accelerometer and a gyroscope, and the step of calibrating the smart headset with the preset precision comprises:
initializing and setting preset parameters in the preset chip;
and calibrating the preset precision of the accelerometer and the gyroscope according to the preset parameters.
5. The method of head motion detection according to claim 4, wherein said step of calibrating said accelerometer to a predetermined accuracy comprises:
initializing the accelerometer, and reading corresponding X-axis position data and Y-axis position data according to the preset parameters;
respectively calculating according to the X-axis position data and the Y-axis position data to obtain an average value and a standard deviation;
and substituting the average value and the standard deviation into a preset matrix formula to calculate a calibration value.
6. The head motion detection method of claim 4, wherein said step of calibrating said gyroscope to a predetermined accuracy comprises:
initializing the gyroscope, and reading corresponding X-axis rotation data and Y-axis rotation data according to the preset parameters;
respectively calculating according to the X-axis rotation data and the Y-axis rotation data to obtain an average value and a standard deviation;
and substituting the average value and the standard deviation into a preset matrix formula to calculate a calibration value.
7. The method for detecting head movements according to claim 5 or 6, characterized in that said step of calibrating said accelerometer and gyroscope with a preset precision according to said preset parameters is followed by the steps of:
and after the preset precision calibration of the accelerometer and the gyroscope is finished, storing the calibration value into a preset storage space.
8. The head motion detection method of claim 7, wherein said step of detecting the presence of a preset action-triggering interrupt further comprises, after said step of detecting the presence of a preset action-triggering interrupt:
and when the preset action trigger interruption is not detected, executing the step of dynamically reading and recording the first position data of the intelligent earphone.
9. A smart headset, comprising: memory, a processor and a head motion detection program stored on the memory and executable on the processor, the head motion detection program when executed by the processor implementing the steps of the head motion detection method according to any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that a head-motion detection program is stored thereon, which when executed by a processor implements the steps of the head-motion detection method according to any one of claims 1 to 8.
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