Intelligent glasses wearing detection method, device and equipment

Abstract

This application discloses a method, apparatus, and device for detecting the wearing of smart glasses. The method involves acquiring data from a contact sensor; determining whether the data from the contact sensor is within a critical wearing threshold range; if the data is within this range, activating an eye data acquisition device; determining whether someone is wearing smart glasses based on the data acquired by the eye data acquisition device; and then deactivating the eye data acquisition device. This approach implements an event-triggered eye-tracking assisted wearing detection mechanism, only briefly activating the eye data acquisition device when a blurred wearing state is initially detected based on a low-power sensor, avoiding continuous operation of the eye data acquisition device. Therefore, it effectively balances high robustness in wearing detection with low power consumption of the device.

Description

Technical Field

[0001] This application relates to the field of smart wearable device technology, specifically to a method and apparatus for detecting the wearing of smart glasses, as well as electronic devices. Background Technology

[0002] Smart glasses wear detection refers to determining whether glasses are correctly worn on a person's face. Current smart glasses primarily rely on capacitive contact sensors for wear detection. While this offers advantages such as low power consumption, it is susceptible to interference from differences in user head shape, glasses slippage, sweat, or hair, leading to false positives—for example, identifying glasses as worn when they are not, and vice versa. Some high-end devices employ eye-tracking to assist in smart glasses wear detection, offering higher robustness. Currently, eye-tracking-assisted smart glasses wear detection uses an eye-tracking camera to continuously detect the presence of eyes; that is, it detects wear by continuously running an eye-tracking camera, and if no eyes are detected for a period of time, the screen turns off (or goes into standby mode).

[0003] However, in the process of implementing this application, the applicant discovered that the existing solutions have at least the following problems: the eye-tracking module runs continuously and the eye-tracking algorithm relies on high frame rate image processing, which leads to high power consumption and is not suitable for lightweight smart glasses with limited batteries. Summary of the Invention

[0004] This application provides a method for detecting the wearing of smart glasses, addressing the problem in existing technologies that cannot simultaneously achieve low device power consumption and high robustness in wear detection. This application also provides a smart glasses wear detection device and an electronic device.

[0005] This application provides a method for detecting the wearing of smart glasses, including: Acquire data from contact sensors; Determine whether the data from the contact sensor is within the wear threshold range; If the data from the contact sensor is within the wear threshold range, the human eye data acquisition device is activated. Based on the collected human eye data, it can be determined whether someone is wearing smart glasses; The human eye data acquisition device is turned off.

[0006] Optional, also includes: Obtain the wearing threshold of the contact sensor between the two states of not wearing and wearing; The wearing critical threshold range is determined based on the wearing critical threshold.

[0007] Optional, also includes: Acquire motion data from smart glasses; Based on the motion data, determine whether the smart glasses have been put on or taken off. If the removal / wearing action is detected, the human eye data acquisition device is activated.

[0008] Optionally, acquiring the motion data of the smart glasses includes: The motion data is acquired using an inertial measurement device, and the motion data includes: acceleration and angular velocity; The step of determining whether a glasses-wearing action has occurred based on the motion data includes: Based on the acceleration and acceleration threshold, as well as the angular velocity and angular velocity threshold, it is determined whether the action of putting on or taking off glasses has occurred.

[0009] Optional, also includes: Acquire motion data from smart glasses; Based on the motion data, determine whether the smart glasses have been put on or taken off. If the data from the contact sensor is within the wearing threshold range and a glasses-wearing action occurs, it is determined that someone is wearing smart glasses.

[0010] Optional, also includes: Acquire motion data from smart glasses; Based on the motion data, determine whether the smart glasses have been put on or taken off. If the data from the contact sensor is within the wear threshold range, the eye data acquisition device is activated, including: If the data from the contact sensor is within the wearing threshold range and no glasses are being put on or taken off, the human eye data acquisition device is activated.

[0011] Optionally, the human eye data acquisition device includes: an eye-tracking camera; The step of determining whether someone is wearing smart glasses based on collected human eye data includes: Based on the eye-tracking images captured by the eye-tracking camera, it can be determined whether someone is wearing smart glasses.

[0012] Optionally, the human eye data acquisition device includes: an infrared light source and an infrared signal receiving device; The step of determining whether someone is wearing smart glasses based on collected human eye data includes: Based on the infrared reflection signal from the eye received by the infrared signal receiving device, it can be determined whether someone is wearing smart glasses.

[0013] Optionally, the human eye data acquisition device includes: an eye image acquisition device; The step of determining whether someone is wearing smart glasses based on collected human eye data includes: Based on the eye images acquired by the eye image acquisition device, pupil detection or eyelid detection is performed; If a pupil or eyelid is detected from the eye image, it is determined that someone is wearing smart glasses.

[0014] Optional, also includes: If it is determined based on the aforementioned human eye data that someone is wearing smart glasses, then it is determined whether the wearer is a real person; If the wearer is a real person, then it is determined that someone is wearing smart glasses.

[0015] Optional, also includes: If it is determined that someone is wearing smart glasses, then the smart glasses will be activated.

[0016] Optionally, the step of waking up the smart glasses if it is determined that someone is wearing them includes: If it is determined that someone is wearing smart glasses, then it checks whether the wearer is a preset user; If the wearer is a preset user, then the smart glasses are activated.

[0017] This application provides a method for detecting the wearing of smart glasses, including: Acquire motion data from smart glasses; Based on the motion data, determine whether the smart glasses have been put on or taken off. If the aforementioned removal / wearing action is detected, the human eye data acquisition device is activated; Based on the collected human eye data, it can be determined whether someone is wearing smart glasses; The human eye data acquisition device is turned off.

[0018] This application provides a smart glasses wearing detection device, comprising: A sensor data acquisition unit is used to acquire data from contact sensors. The first judgment unit is used to determine whether the data of the contact sensor is within the wear threshold range; The first activation unit is used to activate the human eye data acquisition device if the data of the contact sensor is within the wear threshold range. The second judgment unit is used to determine whether someone is wearing smart glasses based on the collected human eye data; The shut-off unit is used to shut down the human eye data acquisition device.

[0019] This application provides a smart glasses wearing detection device, comprising: The glasses motion data acquisition unit is used to acquire motion data from the smart glasses. The first judgment unit is used to determine whether the action of putting on or taking off smart glasses has occurred based on the motion data; The activation unit is used to activate the human eye data acquisition device if the removal / wearing action is determined to have occurred. The second judgment unit is used to determine whether someone is wearing smart glasses based on the collected human eye data; The shut-off unit is used to shut down the human eye data acquisition device.

[0020] This application provides an electronic device, including: Processor; and A memory for storing a program for implementing the method described in any of the preceding methods, wherein the device is powered on and the program of the method is executed by the processor.

[0021] This application also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the various methods described above.

[0022] This application also provides a computer program product including instructions that, when run on a computer, cause the computer to perform the various methods described above.

[0023] Compared with the prior art, this application has the following advantages: The smart glasses wearing detection method provided in this application acquires data from a contact sensor; determines whether the data from the contact sensor is within the wearing threshold range; if the data from the contact sensor is within the wearing threshold range, activates the human eye data acquisition device; determines whether someone is wearing smart glasses based on the acquired human eye data; and then deactivates the human eye data acquisition device. This approach implements an event-triggered eye-tracking assisted wearing detection mechanism, only briefly activating the human eye data acquisition device when a blurred wearing state is initially detected based on existing low-power sensors, avoiding continuous operation of the human eye data acquisition device. Therefore, it effectively balances high robustness of wearing detection with low device power consumption. Specifically, compared to existing pure contact solutions, the method provided in this application effectively improves the robustness of wearing detection and avoids false wake-ups of smart glasses due to head shape / wearing misalignment. Compared to existing continuous eye-tracking detection, power consumption is reduced by more than 80% (the human eye data acquisition device, such as the eye-tracking module, operates for less than 2 minutes per day). Its ultra-low power design is suitable for smart glasses with TWS-level battery capacity and for scenarios requiring precise wearing perception, such as all-weather AI glasses and AR glasses. Furthermore, this processing method is compatible with existing smart glasses hardware, requiring no additional sensors and reusing existing capacitors, IMUs, and eye-tracking modules in smart glasses.

[0024] The smart glasses wearing detection method provided in this application acquires motion data from the smart glasses; determines whether a smart glasses wearing or removing action has occurred based on the motion data; if the wearing or removing action is determined to have occurred, an eye data acquisition device is activated; based on the acquired eye data, it is determined whether someone is wearing the smart glasses; and the eye data acquisition device is then deactivated. This approach implements an event-triggered eye-tracking assisted wearing detection mechanism, only briefly activating the eye data acquisition device when a glasses wearing or removing action (fuzzy wearing state) is initially detected based on the existing motion data detection device, avoiding continuous operation of the eye data acquisition device. Therefore, it effectively balances high robustness of wearing detection with low device power consumption. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating an embodiment of the smart glasses wearing detection method provided in this application; Figure 2 This is a schematic flowchart illustrating a specific embodiment of the smart glasses wearing detection method provided in this application; Figure 3 This is another specific flowchart illustrating an embodiment of the smart glasses wearing detection method provided in this application. Detailed Implementation

[0026] Many specific details are set forth in the following description to provide a full understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this application; therefore, this application is not limited to the specific embodiments disclosed below.

[0027] This application provides a method and apparatus for detecting the wearing of smart glasses, as well as an electronic device. The various solutions are described in detail below in each embodiment.

[0028] First Embodiment Please refer to Figure 1 This is a flowchart of the smart glasses wearing detection method of this application. In this embodiment, the method may include the following steps: Step S101: Acquire data from the contact sensor.

[0029] Contact sensors in smart glasses include, but are not limited to: capacitive sensors, resistive touch / pressure sensors, piezoelectric sensors, infrared proximity + contact sensors, etc.

[0030] In one example, the contact sensor is a capacitive sensor, which can be integrated into the temple of the smart glasses to form a microelectrode. Capacitive sensing technology determines the wearing status by detecting changes in capacitance when the sensor comes into contact with the wearer's skin. When the user wears the glasses, skin contact causes the capacitance between the electrode and ground to increase; after removing the glasses, the capacitance decreases. The chip can identify the wearing status by continuously monitoring this capacitance change and comparing it to a preset threshold. For example, by using a single chip to simultaneously cover wearing and sliding detection, power consumption can be optimized by the "duration" of capacitance changes, achieving low-power operation. In specific implementations, an intermittent wake-up mechanism (such as sampling once every 100ms) can be used, and the static power consumption can be as low as 5-10μA to extend the device's battery life.

[0031] Step S103: Determine whether the data of the contact sensor is within the wear threshold range.

[0032] Step S105: If the data from the contact sensor is within the wear threshold range, then the human eye data acquisition device is activated.

[0033] The method of detecting glasses wearing based on wearing signals from contact sensors is susceptible to interference from differences in user head shape, glasses slippage, sweat, or hair. Furthermore, humidity or temperature / humidity changes can distort the wearing signals (such as capacitance signals) from the contact sensors, leading to misjudgments of glasses wearing, such as identifying glasses as worn when they are not, or vice versa. To improve the accuracy of smart glasses wearing detection, the method provided in this application introduces the concept of a critical wearing threshold range. This range determines whether the smart glasses wearing signal obtained from the contact sensor falls within this range. If it is within this range, the smart glasses are considered to be in a state of ambiguous wearing, and the human eye data acquisition device can be activated, thereby realizing an event-triggered human eye data-assisted wearing detection mechanism.

[0034] The wearing threshold, also known as the wearing boundary point, refers to the critical signal of the smart glasses' contact sensor between the states of not wearing and wearing. The wearing threshold range refers to the critical signal range formed by individual differences in the smart glasses' contact sensor signal between the states of not wearing and wearing, due to factors such as user head shape, glasses slippage, and interference from sweat or hair.

[0035] In one example, the method provided in this application embodiment may further include the following steps: obtaining a wearing threshold between the smart glasses in two states: not worn and worn; and determining the wearing threshold range based on the wearing threshold. In specific implementations, the width of the wearing threshold range can be set according to actual needs; and the wearing threshold range can be determined based on the wearing threshold and the width.

[0036] Taking a capacitive sensor as an example, the critical threshold range for wearing can be a range of capacitance values ​​set based on the capacitance value at the “wearing / not wearing” boundary. For example, the lower limit of the capacitance value range is 20% lower than the capacitance value at the “wearing / not wearing” boundary, and the upper limit is 20% higher than the capacitance value at the “wearing / not wearing” boundary. That is, the boundary value of the capacitance value range is ±20% of the capacitance value at the “wearing / not wearing” boundary.

[0037] Step S107: Based on the collected human eye data, determine whether someone is wearing smart glasses.

[0038] This step involves detecting eyewear use based on eye data collected by an eye data acquisition device.

[0039] In one example, the human eye data acquisition device includes an eye-tracking camera; step S107 can be implemented as follows: based on the eye-tracking images acquired by the eye-tracking camera, determine whether someone is wearing smart glasses. This processing method achieves eye-tracking-assisted wear detection.

[0040] In one example, the human eye data acquisition device includes an infrared light source and an infrared signal receiving device; step S107 can be implemented as follows: based on the infrared reflection signal from the eye received by the infrared signal receiving device, it is determined whether someone is wearing smart glasses. This processing method achieves wear detection assisted by the characteristics of the eye's infrared reflection signal, which can further reduce device power consumption compared to eye-tracking cameras.

[0041] In one example, the human eye data acquisition device includes an eye image acquisition device; step S107 can be implemented as follows: based on the eye image acquired by the eye image acquisition device, pupil detection or eyelid detection is performed; if a pupil or eyelid is identified from the eye image, it is determined that someone is wearing smart glasses. This processing method achieves eye feature-assisted wearing detection, and compared to eye-tracking cameras, it can further reduce device power consumption.

[0042] In one example, step S107 can be implemented as follows: based on the iris data collected by the human eye data acquisition device, determine whether someone is wearing smart glasses. This processing method achieves iris feature-assisted wear detection, which can further reduce device power consumption compared to eye-tracking cameras.

[0043] Step S109: Turn off the human eye data acquisition device.

[0044] The method provided in this application adopts an event-triggered human eye data-assisted wearing detection mechanism. Only when a blurred wearing state is initially detected by an existing low-power contact sensor, the human eye data acquisition device is activated "briefly" through steps S105 and S109, avoiding continuous operation of the human eye data acquisition device. Taking an eye-tracking camera as an example, experiments have shown that a brief activation time of 200 to 500 milliseconds is sufficient to obtain a wearing detection result with high accuracy through step S107.

[0045] Please refer to Figure 2 This is a flowchart illustrating the smart glasses wearing detection method of this application. In one example, the method provided in this embodiment may further include the following steps: Step S201: Obtain motion data from the smart glasses.

[0046] Step S203: Based on the motion data, determine whether the action of putting on or taking off the smart glasses has occurred.

[0047] In practice, the motion data can be acquired through an inertial measurement unit (IMU), which may include acceleration and angular velocity. Step S203 can be implemented as follows: based on the acceleration and acceleration threshold, and the angular velocity and angular velocity threshold, it is determined whether an action of putting on or taking off glasses has occurred. For example, if the acceleration is greater than the acceleration threshold and the angular velocity is greater than the angular velocity threshold, it is determined that an action of putting on or taking off glasses has occurred.

[0048] Step S205: If the removal / wearing action is determined to have occurred, the human eye recognition device is activated.

[0049] The method provided in this application embodiment realizes an event-triggered human eye data-assisted wearing detection mechanism through steps S201 to S205, as well as steps S107 and S109. When the blurry wearing state is initially detected by the existing low-power motion detection device, the human eye data acquisition device is activated "shortly" through steps S205 and S109 to avoid continuous operation of the human eye data acquisition device.

[0050] Please refer to Figure 3 This is another specific flowchart of the smart glasses wearing detection method of this application. In one example, the method provided in this embodiment may further include the following steps: Step S201: Obtain motion data from the smart glasses.

[0051] Step S203: Based on the motion data, determine whether the action of putting on or taking off the smart glasses has occurred.

[0052] Step S301: If the data from the contact sensor is within the wearing threshold range and a glasses-wearing action occurs, it is determined that someone is wearing smart glasses.

[0053] The method provided in this application embodiment, through steps S201, S203 and S301, and steps S101 and S103, enables direct determination that someone is wearing smart glasses when the wearing detection result obtained based on the contact sensor is consistent with the wearing detection result obtained based on motion data, without activating the human eye data acquisition device; therefore, it can further improve and reduce power consumption and detection efficiency.

[0054] In one example, step S103 can be implemented as follows: if the data from the contact sensor is within the wearing threshold range and no glasses are being put on or taken off, then the eye data acquisition device is activated. This approach ensures that when the wearing detection result obtained from the contact sensor differs from the wearing detection result obtained from motion data, the eye data acquisition device is activated to further perform eye data-assisted wearing detection, avoiding activation of the eye data acquisition device only when the wearing signal is within the wearing threshold range; therefore, device power consumption can be further reduced.

[0055] In one example, the method provided in this application embodiment may further include the following steps: if it is determined based on the human eye data that someone is wearing smart glasses, then determine whether the wearer is a real person; if the wearer is a real person, then determine that someone is wearing smart glasses. This processing method allows for further determination of whether the wearer is a real person after determining that someone is wearing smart glasses based on the human eye data. Typically, the eyes of a model or the eyes of a person on a screen do not correspond to real people; only when the wearer is a real person can it be finally determined that someone is wearing smart glasses. Therefore, the accuracy of glasses wearing can be further improved.

[0056] In one example, the method provided in this application embodiment may further include the following step: if it is determined that someone is wearing smart glasses, then wake up the smart glasses. This processing method ensures that the glasses wake-up device is in working order after detecting that someone is wearing glasses.

[0057] In specific implementation, the step of waking up the smart glasses if someone is detected wearing them can be achieved as follows: if someone is detected wearing the smart glasses, then check whether the wearer is a preset user; if the wearer is a preset user, then wake up the smart glasses. This approach ensures that the glasses will only activate when the wearer is a preset user, thus effectively improving device security.

[0058] In one example, detecting whether the wearer is a preset user can be achieved as follows: acquiring the wearer's iris data; and determining whether the wearer is a preset user based on the iris data and the preset user's iris data. This processing method allows for the detection of whether the wearer is a preset user based on their iris data, thus effectively improving user recognition efficiency and accuracy.

[0059] In one example, the method provided in this application embodiment may further include the following steps: if it is detected that no one is wearing the smart glasses, then the smart glasses are set to a sleep state or turned off. This approach ensures that the glasses are turned off or put into a sleep state upon detection that no one is wearing them; therefore, it can effectively reduce the power consumption of the glasses.

[0060] As can be seen from the above embodiments, the smart glasses wearing detection method provided in this application acquires data from a contact sensor; determines whether the data from the contact sensor is within the wearing threshold range; if the data from the contact sensor is within the wearing threshold range, then activates the human eye data acquisition device; based on the acquired human eye data, determines whether someone is wearing smart glasses; and then deactivates the human eye data acquisition device. This processing method achieves an event-triggered eye-tracking assisted wearing detection mechanism, only briefly activating the human eye data acquisition device when a blurred wearing state is initially detected based on existing low-power sensors, avoiding continuous operation of the human eye data acquisition device; therefore, it can effectively balance high wearing detection robustness with low device power consumption.

[0061] Second Embodiment In the above embodiments, a method for detecting the wearing of smart glasses is provided. Correspondingly, this application also provides a device for detecting the wearing of smart glasses. This device corresponds to the embodiments of the method described above. Since the device embodiments are basically similar to the method embodiments, the description is relatively simple, and relevant parts can be referred to in the description of the method embodiments. The device embodiments described below are merely illustrative.

[0062] This application also provides a smart glasses wearing detection device, including: a sensor data acquisition unit, a first judgment unit, a human eye data acquisition device activation unit, a second judgment unit, and a human eye data acquisition device deactivation unit.

[0063] The device includes a sensor data acquisition unit for acquiring data from a contact sensor; a first judgment unit for determining whether the data from the contact sensor is within a wear threshold range; a first activation unit for activating the human eye data acquisition device if the data from the contact sensor is within a wear threshold range; a second judgment unit for determining whether someone is wearing smart glasses based on the acquired human eye data; and a shutdown unit for shutting down the human eye data acquisition device.

[0064] In one example, the device may further include: a wearing critical threshold range determination unit, configured to acquire a wearing critical threshold between the contact sensor in two states: not worn and worn; and determine the wearing critical threshold range based on the wearing critical threshold.

[0065] In one example, the device may further include: a glasses-wearing action recognition unit, used to acquire motion data of smart glasses; and to determine whether a smart glasses-wearing action has occurred based on the motion data; and a second activation unit, used to activate the human eye data acquisition device if the wear-wearing action is determined to have occurred.

[0066] In one example, acquiring motion data of smart glasses includes: acquiring the motion data via an inertial measurement device, the motion data including: acceleration and angular velocity; determining whether a glasses-wearing action has occurred based on the motion data includes: determining whether a glasses-wearing action has occurred based on the acceleration and acceleration threshold, and the angular velocity and angular velocity threshold.

[0067] In one example, the device may further include: a glasses-wearing action recognition unit, used to acquire motion data of the smart glasses; and to determine whether a smart glasses-wearing action has occurred based on the motion data; and a determination unit, specifically used to determine that someone is wearing smart glasses if the data of the contact sensor is within the wearing threshold range and a glasses-wearing action has occurred.

[0068] In one example, the device may further include: a glasses-wearing action recognition unit, used to acquire motion data of the smart glasses; and to determine whether a smart glasses-wearing action has occurred based on the motion data; and a second determination unit, specifically used to activate the human eye data acquisition device if the data of the contact sensor is within the wearing threshold range and no glasses-wearing action has occurred.

[0069] In one example, the human eye data acquisition device includes an eye-tracking camera; the step of determining whether someone is wearing smart glasses based on the acquired human eye data includes determining whether someone is wearing smart glasses based on the eye-tracking images acquired by the eye-tracking camera.

[0070] In one example, the human eye data acquisition device includes an infrared light source and an infrared signal receiving device; the step of determining whether someone is wearing smart glasses based on the acquired human eye data includes determining whether someone is wearing smart glasses based on the infrared reflection signal from the eye received by the infrared signal receiving device.

[0071] In one example, the human eye data acquisition device includes: an eye image acquisition device; the step of determining whether someone is wearing smart glasses based on the acquired human eye data includes: performing pupil detection or eyelid detection based on the eye image acquired by the eye image acquisition device; if a pupil or eyelid is identified from the eye image, it is determined that someone is wearing smart glasses.

[0072] In one example, the device may further include: a third determination unit, configured to determine whether the wearer is a real person if it is determined based on the human eye data that someone is wearing smart glasses; and if the wearer is a real person, determine that someone is wearing smart glasses.

[0073] In one example, the device may further include: a glasses wake-up unit for waking up the smart glasses if it is determined that someone is wearing them.

[0074] In one example, the glasses wake-up unit is specifically used to detect whether the wearer is a preset user if it is determined that someone is wearing smart glasses; if the wearer is a preset user, the smart glasses are woken up.

[0075] Third Embodiment In the above embodiments, a method for detecting the wearing of smart glasses was provided. Correspondingly, this application also provides a method for detecting the wearing of smart glasses. This method corresponds to the embodiments of the above methods, so it is described simply. For relevant details, please refer to the description of the first method embodiment. The method embodiments described below are merely illustrative.

[0076] Another smart glasses wearing detection method provided in this application includes the following steps: Step 1: Obtain motion data from the smart glasses.

[0077] Step 2: Based on the motion data, determine whether the smart glasses have been put on or taken off.

[0078] Step 3: If the removal / wearing action is determined to have occurred, the human eye data acquisition device is activated.

[0079] Step 4: Based on the collected human eye data, determine whether someone is wearing smart glasses.

[0080] Step 5: Turn off the human eye data acquisition device.

[0081] As can be seen from the above embodiments, motion data is used to determine whether a smart glasses wearing or removing action has occurred; if such an action is detected, the human eye data acquisition device is activated; based on the acquired human eye data, it is determined whether someone is wearing smart glasses; and then the human eye data acquisition device is deactivated. This processing method implements an event-triggered eye-tracking-assisted wearing detection mechanism. The human eye data acquisition device is only briefly activated when a glasses wearing or removing action (fuzzy wearing state) is initially detected based on the existing motion data detection device, avoiding continuous operation of the human eye data acquisition device. Therefore, it can effectively balance high robustness of wearing detection with low device power consumption.

[0082] Fourth embodiment In the above embodiments, a method for detecting the wearing of smart glasses is provided. Correspondingly, this application also provides a device for detecting the wearing of smart glasses. This device corresponds to the embodiments of the method described above. Since the device embodiments are basically similar to the method embodiments, the description is relatively simple, and relevant parts can be referred to in the description of the method embodiments. The device embodiments described below are merely illustrative.

[0083] This application also provides a smart glasses wearing detection device, comprising: a glasses motion data acquisition unit, a first judgment unit, a start unit, a second judgment unit, and a stop unit. The glasses motion data acquisition unit is used to acquire motion data of the smart glasses; the first judgment unit is used to determine, based on the motion data, whether a smart glasses wearing or removing action has occurred; the start unit is used to activate the human eye data acquisition device if the wearing or removing action is determined to have occurred; the second judgment unit is used to determine, based on the acquired human eye data, whether someone is wearing smart glasses; and the stop unit is used to stop the human eye data acquisition device.

[0084] Fifth Embodiment In the above embodiments, a method for detecting the wearing of smart glasses is provided. Correspondingly, this application also provides an electronic device. This device corresponds to the embodiments of the above method. Since the device embodiments are basically similar to the method embodiments, the description is relatively simple, and relevant parts can be referred to in the description of the method embodiments. The device embodiments described below are merely illustrative.

[0085] The electronic device of this embodiment includes: a memory and a processor; the memory is used to store a program for implementing the smart glasses wearing detection method, and the device is powered on and runs the program of the smart glasses wearing detection method through the processor.

[0086] Memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0087] In specific implementations, the electronic device may further include one or more of the following components: a power supply component, an input / output (I / O) interface, and a communication component. The power supply component provides power to various components of the electronic device. The power supply component may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device. The I / O interface provides an interface between the processor 503 and peripheral interface modules, which may be a keyboard, click wheel, buttons, etc. The communication component is configured to facilitate wired or wireless communication between the electronic device and user devices (such as smartphones, tablets, etc.).

[0088] Sixth Embodiment This application also provides a computer-readable storage medium. Since the embodiments of the computer-readable storage medium are substantially similar to the method embodiments, the description is relatively simple; relevant details can be found in the description of the method embodiments. The computer-readable storage medium embodiments described below are merely illustrative.

[0089] In this embodiment, a non-transitory computer-readable storage medium including instructions is provided, such as a memory including instructions, which can be executed by a processor of an electronic device to complete the smart glasses wearing detection method provided in this disclosure. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0090] It should be noted that the embodiments of this application may involve the use of user data. In practical applications, user-specific personal data may be used in the scheme described herein within the scope permitted by applicable laws and regulations, provided that it complies with the applicable laws and regulations of the country (e.g., with the user's explicit consent, with the user being properly notified, etc.).

[0091] Although this application discloses preferred embodiments as described above, it is not intended to limit this application. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of this application. Therefore, the scope of protection of this application should be determined by the scope defined in the claims of this application.

[0092] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0093] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0094] 1. Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include non-transitory computer-readable media, such as modulated data signals and carrier waves.

[0095] 2. Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

Claims

1. A method for detecting the wearing of smart glasses, characterized in that, include: Acquire data from contact sensors; Determine whether the data from the contact sensor is within the wear threshold range; If the data from the contact sensor is within the wear threshold range, the human eye data acquisition device is activated. Based on the collected human eye data, it can be determined whether someone is wearing smart glasses; The human eye data acquisition device is turned off.

2. The method according to claim 1, characterized in that, Also includes: Obtain the wearing threshold of the contact sensor between the two states of not wearing and wearing; The wearing critical threshold range is determined based on the wearing critical threshold.

3. The method according to claim 1, characterized in that, Also includes: Acquire motion data from smart glasses; Based on the motion data, determine whether the smart glasses have been put on or taken off. If the removal / wearing action is detected, the human eye data acquisition device is activated.

4. The method according to claim 3, characterized in that, The acquisition of motion data from smart glasses includes: The motion data is acquired using an inertial measurement device, and the motion data includes: acceleration and angular velocity; The step of determining whether a glasses-wearing action has occurred based on the motion data includes: Based on the acceleration and acceleration threshold, as well as the angular velocity and angular velocity threshold, it is determined whether the action of putting on or taking off glasses has occurred.

5. The method according to claim 1, characterized in that, Also includes: Acquire motion data from smart glasses; Based on the motion data, determine whether the smart glasses have been put on or taken off. If the data from the contact sensor is within the wearing threshold range and a glasses-wearing action occurs, it is determined that someone is wearing smart glasses.

6. The method according to claim 1, characterized in that, Also includes: Acquire motion data from smart glasses; Based on the motion data, determine whether the smart glasses have been put on or taken off. If the data from the contact sensor is within the wear threshold range, the eye data acquisition device is activated, including: If the data from the contact sensor is within the wearing threshold range and no glasses are being put on or taken off, the human eye data acquisition device is activated.

7. The method according to claim 1, characterized in that, The human eye data acquisition device includes: an eye-tracking camera; The step of determining whether someone is wearing smart glasses based on collected human eye data includes: Based on the eye-tracking images captured by the eye-tracking camera, it can be determined whether someone is wearing smart glasses.

8. The method according to claim 1, characterized in that, The human eye data acquisition device includes: an infrared light source and an infrared signal receiving device; The step of determining whether someone is wearing smart glasses based on collected human eye data includes: Based on the infrared reflection signal from the eye received by the infrared signal receiving device, it can be determined whether someone is wearing smart glasses.

9. The method according to claim 1, characterized in that, The human eye data acquisition device includes: an eye image acquisition device; The step of determining whether someone is wearing smart glasses based on collected human eye data includes: Based on the eye images acquired by the eye image acquisition device, pupil detection or eyelid detection is performed; If a pupil or eyelid is detected from the eye image, it is determined that someone is wearing smart glasses.

10. The method according to claim 8 or 9, characterized in that, Also includes: If it is determined based on the aforementioned human eye data that someone is wearing smart glasses, then it is determined whether the wearer is a real person; If the wearer is a real person, then it is determined that someone is wearing smart glasses.

11. A method for detecting the wearing of smart glasses, characterized in that, include: Acquire motion data from smart glasses; Based on the motion data, determine whether the smart glasses have been put on or taken off. If the aforementioned removal / wearing action is detected, the human eye data acquisition device is activated; Based on the collected human eye data, it can be determined whether someone is wearing smart glasses; The human eye data acquisition device is turned off.

12. A smart glasses wearing detection device, characterized in that, include: A sensor data acquisition unit is used to acquire data from contact sensors. The first judgment unit is used to determine whether the data of the contact sensor is within the wear threshold range; The first activation unit is used to activate the human eye data acquisition device if the data of the contact sensor is within the wear threshold range. The second judgment unit is used to determine whether someone is wearing smart glasses based on the collected human eye data; The shut-off unit is used to shut down the human eye data acquisition device.

13. A smart glasses wearing detection device, characterized in that, include: The glasses motion data acquisition unit is used to acquire motion data from the smart glasses. The first judgment unit is used to determine whether the action of putting on or taking off smart glasses has occurred based on the motion data; The activation unit is used to activate the human eye data acquisition device if the removal / wearing action is determined to have occurred. The second judgment unit is used to determine whether someone is wearing smart glasses based on the collected human eye data; The shut-off unit is used to shut down the human eye data acquisition device.

14. An electronic device, characterized in that, include: processor; as well as A memory for storing a program for implementing the method according to any one of claims 1 to 11, wherein the device is powered on and the program for running the method is executed by the processor.

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