CN111400605A

CN111400605A - Recommendation method and device based on eyeball tracking

Info

Publication number: CN111400605A
Application number: CN202010341523.8A
Authority: CN
Inventors: 方攀
Original assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd
Current assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd
Priority date: 2020-04-26
Filing date: 2020-04-26
Publication date: 2020-07-10

Abstract

The application discloses a recommendation method based on eyeball tracking, which comprises the following steps: when the user is detected to browse the interface, acquiring a fixation point of the user aiming at a plurality of frames of images in the browsing interface according to an eyeball tracking technology; determining at least one target image area according to the fixation point; analyzing the at least one target image area, and determining a plurality of interest point characteristic information; determining a recommendation strategy according to the characteristic information of the interest points and the image information of the current frame image; and recommending information according to the recommendation strategy. According to the method and the device, the interest information of the user can be reflected in real time, information recommendation is accurately carried out, the recommendation accuracy is improved, and then user experience is greatly improved, so that the use habits of the user are adapted to improve the object selection success rate and accuracy.

Description

Recommendation method and device based on eyeball tracking

Technical Field

The present application relates to the field of eye tracking, and in particular, to a recommendation method and related apparatus based on eye tracking.

Background

Most of the current real-time recommendation methods for network platforms are based on big data to analyze past browsing or usage records of a user to obtain user preferences, and then recommend related products or services according to analysis results of the big data after the user opens the corresponding platform again to meet the requirements of the user. In current techniques, big data is used to analyze the user's preferences and then infer the user's current preferences. Although the technology has certain accuracy and can meet the requirements of most scenes, the current requirements of the user are difficult to accurately reflect in real time, so that the recommended products or services are difficult to meet the current expectations of the user; in addition, in terms of accuracy, the technology is inferred based on past records, so that the current technology has a certain development bottleneck and cannot reach a higher level.

Disclosure of Invention

The embodiment of the application provides a recommendation method and device based on eyeball tracking.

In a first aspect, an embodiment of the present application provides a recommendation method based on eye tracking, which is applied to an electronic device, where the electronic device includes a camera module, and the method includes:

when the user is detected to browse the interface, acquiring a fixation point of the user aiming at a plurality of frames of images in the browsing interface according to an eyeball tracking technology; determining at least one target image area according to the fixation point; analyzing the at least one target image area, and determining a plurality of interest point characteristic information; determining a recommendation strategy according to the characteristic information of the interest points and the image information of the current frame image; and recommending information according to the recommendation strategy.

In a second aspect, an embodiment of the present application provides an eyeball tracking-based recommendation apparatus, which is applied to an electronic device, where the electronic device includes a camera module, the apparatus includes:

the processing unit is used for acquiring a fixation point of a user aiming at a plurality of frames of images in a browsing interface according to an eyeball tracking technology when the user is detected to browse the interface; and for determining at least one target image area from the point of regard; the system is used for analyzing the at least one target image area and determining a plurality of interest point characteristic information; the recommendation strategy is determined according to the characteristic information of the interest points and the image information of the current frame image; and the information recommendation module is used for recommending information according to the recommendation strategy.

In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing steps in any method of the first aspect of the embodiment of the present application.

In a fourth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program makes a computer perform part or all of the steps described in any one of the methods of the first aspect of the present application.

In a fifth aspect, the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform some or all of the steps as described in any one of the methods of the first aspect of the embodiments of the present application. The computer program product may be a software installation package.

It can be seen that, in the embodiment of the application, when it is detected that a user browses an interface, the electronic device first obtains a gaze point of the user for a plurality of frames of images in a browsing interface according to an eyeball tracking technology, then determines at least one target image region according to the gaze point, then analyzes the at least one target image region, determines a plurality of interest point feature information, then determines a recommendation policy according to the plurality of interest point feature information and image information of a current frame of image, and finally performs information recommendation according to the recommendation policy. Therefore, the electronic equipment applies the eyeball tracking technology to real-time recommendation, obtains the real-time interest preference of the user through analysis of the user point-of-regard information, further dynamically refreshes recommendation data based on the characteristic information of the real-time interest preference of the user, recommends more accurate information to the user, improves the accuracy and intelligence of recommendation based on eyeball tracking, and further improves user experience.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;

fig. 2 is a schematic diagram of a software structure of an electronic device according to an embodiment of the present application;

fig. 3 is a schematic diagram illustrating a position relationship between an overall eye tracking area and a screen according to an embodiment of the present application;

fig. 4 is a flowchart illustrating a recommendation method based on eye tracking according to an embodiment of the present application;

FIG. 5 is a schematic view of an eye tracking-based interface according to an embodiment of the present disclosure;

fig. 6 is a schematic diagram of an eyeball tracking-based recommendation device according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings.

In order to better understand the scheme of the embodiments of the present application, the following first introduces the related terms and concepts that may be involved in the embodiments of the present application.

1) The electronic device may be a portable electronic device that also includes other functionality such as personal digital assistant and/or music player functionality, such as a cell phone, a tablet computer, a wearable electronic device with wireless communication functionality (e.g., a smart watch), etc. exemplary embodiments of the portable electronic device include, but are not limited to, portable electronic devices that carry an IOS system, an Android system, a Microsoft system, or other operating systems.

2) The interface refers to a functional interface displayed on a screen of the terminal, and the functional interface may be a system desktop, an application interface of any application program, and the like, and is not limited herein.

3) The object refers to various information such as characters, pictures, thumbnails and the like, and in a digital password entry interface, the object refers to numbers 0, 1, 2, 3 and the like.

4) Eyeball tracking, also known as eye tracking, human eye tracking/tracing, gaze point tracking/tracing, and the like, refers to a mechanism for determining a user's gaze direction and gaze point based on fused image acquisition, gaze estimation techniques.

5) The fixation point refers to a point where the line of sight of human eyes falls on the plane where the screen is located.

6) The browsing interface is a plane area formed by an effective human eye gaze point captured by the terminal based on an eyeball tracking function, and the plane area specifically forms an overall eyeball tracking area and an individual eyeball tracking area of a related object, wherein the individual eyeball tracking area can be obtained by an explicit method (for example: display area boundary lines, or thumbnail images of display area boundary lines and associated objects) to indicate the corresponding areas, or may not be explicitly displayed.

In a first section, the software and hardware operating environment of the technical solution disclosed in the present application is described as follows.

Fig. 1 shows a schematic structural diagram of an electronic device 100. The electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a Universal Serial Bus (USB) interface 130, a charge management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a compass 190, a motor 191, a pointer 192, a camera 193, a display screen 194, a Subscriber Identification Module (SIM) card interface 195, and the like.

It is to be understood that the illustrated structure of the embodiment of the present application does not specifically limit the electronic device 100. In other embodiments of the present application, electronic device 100 may include more or fewer components than shown, or some components may be combined, some components may be split, or a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

Processor 110 may include one or more processing units, such as: the processor 110 may include an Application Processor (AP), a modem processor, a Graphics Processor (GPU), an Image Signal Processor (ISP), a controller, a video codec, a Digital Signal Processor (DSP), a baseband processor, and/or a neural-Network Processing Unit (NPU), etc. Wherein the different processing units may be separate components or may be integrated in one or more processors. In some embodiments, the electronic device 101 may also include one or more processors 110. The controller can generate an operation control signal according to the instruction operation code and the time sequence signal to complete the control of instruction fetching and instruction execution. In other embodiments, a memory may also be provided in processor 110 for storing instructions and data. Illustratively, the memory in the processor 110 may be a cache memory. The memory may hold instructions or data that have just been used or recycled by the processor 110. If the processor 110 needs to reuse the instruction or data, it can be called directly from the memory. This avoids repeated accesses and reduces the latency of the processor 110, thereby increasing the efficiency with which the electronic device 101 processes data or executes instructions.

In some embodiments, processor 110 may include one or more interfaces. The interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit audio (I2S) interface, a Pulse Code Modulation (PCM) interface, a universal asynchronous receiver/transmitter (UART) interface, a Mobile Industry Processor Interface (MIPI), a general-purpose input/output (GPIO) interface, a SIM card interface, a USB interface, and/or the like. The USB interface 130 is an interface conforming to the USB standard specification, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, or the like. The USB interface 130 may be used to connect a charger to charge the electronic device 101, and may also be used to transmit data between the electronic device 101 and peripheral devices. The USB interface 130 may also be used to connect to a headset to play audio through the headset.

It should be understood that the interface connection relationship between the modules illustrated in the embodiments of the present application is only an illustration, and does not limit the structure of the electronic device 100. In other embodiments of the present application, the electronic device 100 may also adopt different interface connection manners or a combination of multiple interface connection manners in the above embodiments.

The charging management module 140 is configured to receive charging input from a charger. The charger may be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 may receive charging input from a wired charger via the USB interface 130. In some wireless charging embodiments, the charging management module 140 may receive a wireless charging input through a wireless charging coil of the electronic device 100. The charging management module 140 may also supply power to the electronic device through the power management module 141 while charging the battery 142.

The power management module 141 is used to connect the battery 142, the charging management module 140 and the processor 110. The power management module 141 receives input from the battery 142 and/or the charge management module 140, and supplies power to the processor 110, the internal memory 121, the external memory, the display 194, the camera 193, the wireless communication module 160, and the like. The power management module 141 may also be used to monitor parameters such as battery capacity, battery cycle count, battery state of health (leakage, impedance), etc. In some other embodiments, the power management module 141 may also be disposed in the processor 110. In other embodiments, the power management module 141 and the charging management module 140 may be disposed in the same device.

The wireless communication function of the electronic device 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, a modem processor, a baseband processor, and the like.

The antennas 1 and 2 are used for transmitting and receiving electromagnetic wave signals. Each antenna in the electronic device 100 may be used to cover a single or multiple communication bands. Different antennas can also be multiplexed to improve the utilization of the antennas. For example: the antenna 1 may be multiplexed as a diversity antenna of a wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.

The mobile communication module 150 may provide a solution for wireless communication including 2G/3G/4G/5G applied to the electronic device 100. the mobile communication module 150 may include at least one filter, a switch, a power amplifier, a low noise amplifier (L NA), etc. the mobile communication module 150 may receive an electromagnetic wave from the antenna 1, filter the received electromagnetic wave, amplify, etc., and transmit the processed electromagnetic wave to the modem processor for demodulation.

The wireless communication module 160 may provide solutions for wireless communication including wireless local area networks (W L AN) (e.g., wireless fidelity (Wi-Fi) network), bluetooth (bluetooth), Global Navigation Satellite System (GNSS), Frequency Modulation (FM), Near Field Communication (NFC), infrared (infrared, IR), UWB, etc. applied to the electronic device 100. the wireless communication module 160 may be one or more devices integrating at least one communication processing module, the wireless communication module 160 may receive electromagnetic waves via the antenna 2, frequency modulate and filter the electromagnetic waves, and transmit the processed signals to the processor 110. the wireless communication module 160 may also receive signals from the processor 110, frequency modulate and amplify the signals, and convert the signals into electromagnetic wave radiation via the antenna 2.

The electronic device 100 implements display functions via the GPU, the display screen 194, and the application processor. The GPU is a microprocessor for image processing, and is connected to the display screen 194 and an application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 110 may include one or more GPUs that execute program instructions to generate or alter display information.

The display screen 194 may include a display panel, which may be implemented as a liquid crystal display (L CD), an organic light-emitting diode (O L ED), an active matrix organic light-emitting diode (AMO L ED), a flexible light-emitting diode (F L ED), a mini-light-emitting diode (mini-light-emitting diode, miniled), Micro L ED, Micro-O L ED, a quantum dot light-emitting diode (Q L ED), etc. in some embodiments, the electronic device 100 may include 1 or more display screens 194.

The electronic device 100 may implement a photographing function through the ISP, the camera 193, the video codec, the GPU, the display screen 194, the application processor, and the like.

The ISP is used to process the data fed back by the camera 193. For example, when a photo is taken, the shutter is opened, light is transmitted to the camera photosensitive element through the lens, the optical signal is converted into an electrical signal, and the camera photosensitive element transmits the electrical signal to the ISP for processing and converting into an image visible to naked eyes. The ISP can also carry out algorithm optimization on the noise, brightness and skin color of the image. The ISP can also optimize parameters such as exposure, color temperature and the like of a shooting scene. In some embodiments, the ISP may be provided in camera 193.

The camera 193 is used to capture still images or video. The object generates an optical image through the lens and projects the optical image to the photosensitive element. The photosensitive element may be a Charge Coupled Device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The light sensing element converts the optical signal into an electrical signal, which is then passed to the ISP where it is converted into a digital image signal. And the ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into image signal in standard RGB, YUV and other formats. In some embodiments, the electronic device 100 may include 1 or more cameras 193.

The digital signal processor is used for processing digital signals, and can process digital image signals and other digital signals. For example, when the electronic device 100 selects a frequency bin, the digital signal processor is used to perform fourier transform or the like on the frequency bin energy.

Video codecs are used to compress or decompress digital video. The electronic device 100 may support one or more video codecs. In this way, the electronic device 100 may play or record video in a variety of encoding formats, such as: moving Picture Experts Group (MPEG) 1, MPEG2, MPEG3, MPEG4, and the like.

The NPU is a neural-network (NN) computing processor that processes input information quickly by using a biological neural network structure, for example, by using a transfer mode between neurons of a human brain, and can also learn by itself continuously. Applications such as intelligent recognition of the electronic device 100 can be realized through the NPU, for example: image recognition, face recognition, speech recognition, text understanding, and the like.

The external memory interface 120 may be used to connect an external memory card, such as a Micro SD card, to extend the memory capability of the electronic device 100. The external memory card communicates with the processor 110 through the external memory interface 120 to implement a data storage function. For example, files such as music, video, etc. are saved in an external memory card.

Internal memory 121 may be used to store one or more computer programs, including instructions. The processor 110 may execute the above-mentioned instructions stored in the internal memory 121, so as to enable the electronic device 101 to execute the method for displaying page elements provided in some embodiments of the present application, and various applications and data processing. The internal memory 121 may include a program storage area and a data storage area. Wherein, the storage program area can store an operating system; the storage program area may also store one or more applications (e.g., gallery, contacts, etc.), and the like. The storage data area may store data (such as photos, contacts, etc.) created during use of the electronic device 101, and the like. Further, the internal memory 121 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic disk storage components, flash memory components, Universal Flash Storage (UFS), and the like. In some embodiments, the processor 110 may cause the electronic device 101 to execute the method for displaying page elements provided in the embodiments of the present application, and other applications and data processing by executing instructions stored in the internal memory 121 and/or instructions stored in a memory provided in the processor 110. The electronic device 100 may implement audio functions through the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the earphone interface 170D, and the application processor, etc. Such as music playing, recording, etc.

The sensor module 180 may include a pressure sensor 180A, a gyro sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, and the like.

The pressure sensor 180A is used for sensing a pressure signal, and converting the pressure signal into an electrical signal. In some embodiments, the pressure sensor 180A may be disposed on the display screen 194. The pressure sensor 180A can be of a wide variety, such as a resistive pressure sensor, an inductive pressure sensor, a capacitive pressure sensor, and the like. The capacitive pressure sensor may be a sensor comprising at least two parallel plates having an electrically conductive material. When a force acts on the pressure sensor 180A, the capacitance between the electrodes changes. The electronic device 100 determines the strength of the pressure from the change in capacitance. When a touch operation is applied to the display screen 194, the electronic apparatus 100 detects the intensity of the touch operation according to the pressure sensor 180A. The electronic apparatus 100 may also calculate the touched position from the detection signal of the pressure sensor 180A. In some embodiments, the touch operations that are applied to the same touch position but different touch operation intensities may correspond to different operation instructions. For example: and when the touch operation with the touch operation intensity smaller than the first pressure threshold value acts on the short message application icon, executing an instruction for viewing the short message. And when the touch operation with the touch operation intensity larger than or equal to the first pressure threshold value acts on the short message application icon, executing an instruction of newly building the short message.

The gyro sensor 180B may be used to determine the motion attitude of the electronic device 100. In some embodiments, the angular velocity of electronic device 100 about three axes (i.e., X, Y and the Z axis) may be determined by gyroscope sensor 180B. The gyro sensor 180B may be used for photographing anti-shake. For example, when the shutter is pressed, the gyro sensor 180B detects a shake angle of the electronic device 100, calculates a distance to be compensated for by the lens module according to the shake angle, and allows the lens to counteract the shake of the electronic device 100 through a reverse movement, thereby achieving anti-shake. The gyroscope sensor 180B may also be used for navigation, somatosensory gaming scenes.

The acceleration sensor 180E may detect the magnitude of acceleration of the electronic device 100 in various directions (typically three axes). The magnitude and direction of gravity can be detected when the electronic device 100 is stationary. The method can also be used for recognizing the posture of the electronic equipment, and is applied to horizontal and vertical screen switching, pedometers and other applications.

The ambient light sensor 180L is used for sensing the ambient light brightness, the electronic device 100 can adaptively adjust the brightness of the display screen 194 according to the sensed ambient light brightness, the ambient light sensor 180L can also be used for automatically adjusting the white balance during photographing, and the ambient light sensor 180L can also cooperate with the proximity light sensor 180G to detect whether the electronic device 100 is in a pocket to prevent accidental touch.

The fingerprint sensor 180H is used to collect a fingerprint. The electronic device 100 can utilize the collected fingerprint characteristics to unlock the fingerprint, access the application lock, photograph the fingerprint, answer an incoming call with the fingerprint, and so on.

The temperature sensor 180J is used to detect temperature. In some embodiments, electronic device 100 implements a temperature processing strategy using the temperature detected by temperature sensor 180J. For example, when the temperature reported by the temperature sensor 180J exceeds a threshold, the electronic device 100 performs a reduction in performance of a processor located near the temperature sensor 180J, so as to reduce power consumption and implement thermal protection. In other embodiments, the electronic device 100 heats the battery 142 when the temperature is below another threshold to avoid the low temperature causing the electronic device 100 to shut down abnormally. In other embodiments, when the temperature is lower than a further threshold, the electronic device 100 performs boosting on the output voltage of the battery 142 to avoid abnormal shutdown due to low temperature.

The touch sensor 180K is also referred to as a "touch panel". The touch sensor 180K may be disposed on the display screen 194, and the touch sensor 180K and the display screen 194 form a touch screen, which is also called a "touch screen". The touch sensor 180K is used to detect a touch operation applied thereto or nearby. The touch sensor can communicate the detected touch operation to the application processor to determine the touch event type. Visual output associated with the touch operation may be provided through the display screen 194. In other embodiments, the touch sensor 180K may be disposed on a surface of the electronic device 100, different from the position of the display screen 194.

Fig. 2 shows a block diagram of a software structure of the electronic device 100. The layered architecture divides the software into several layers, each layer having a clear role and division of labor. The layers communicate with each other through a software interface. In some embodiments, the Android system is divided into four layers, an application layer, an application framework layer, an Android runtime (Android runtime) and system library, and a kernel layer from top to bottom. The application layer may include a series of application packages.

As shown in fig. 2, the application package may include applications such as camera, gallery, calendar, phone call, map, navigation, W L AN, bluetooth, music, video, short message, etc.

The application framework layer provides an Application Programming Interface (API) and a programming framework for the application programs of the application layer. The application framework layer includes a number of predefined functions.

As shown in FIG. 2, the application framework layers may include a window manager, content provider, view system, phone manager, resource manager, notification manager, and the like.

The window manager is used for managing window programs. The window manager can obtain the size of the display screen, judge whether a status bar exists, lock the screen, intercept the screen and the like.

The content provider is used to store and retrieve data and make it accessible to applications. The data may include video, images, audio, calls made and received, browsing history and bookmarks, phone books, etc.

The view system includes visual controls such as controls to display text, controls to display pictures, and the like. The view system may be used to build applications. The display interface may be composed of one or more views. For example, the display interface including the short message notification icon may include a view for displaying text and a view for displaying pictures.

The phone manager is used to provide communication functions of the electronic device 100. Such as management of call status (including on, off, etc.).

The resource manager provides various resources for the application, such as localized strings, icons, pictures, layout files, video files, and the like.

The notification manager enables the application to display notification information in the status bar, can be used to convey notification-type messages, can disappear automatically after a short dwell, and does not require user interaction. Such as a notification manager used to inform download completion, message alerts, etc. The notification manager may also be a notification that appears in the form of a chart or scroll bar text at the top status bar of the system, such as a notification of a background running application, or a notification that appears on the screen in the form of a dialog window. For example, prompting text information in the status bar, sounding a prompt tone, vibrating the electronic device, flashing an indicator light, etc.

The Android Runtime comprises a core library and a virtual machine. The Android runtime is responsible for scheduling and managing an Android system.

The core library comprises two parts: one part is a function which needs to be called by java language, and the other part is a core library of android.

The application layer and the application framework layer run in a virtual machine. And executing java files of the application program layer and the application program framework layer into a binary file by the virtual machine. The virtual machine is used for performing the functions of object life cycle management, stack management, thread management, safety and exception management, garbage collection and the like.

The system library may include a plurality of functional modules, such as surface managers (surface managers), media libraries (media libraries), three-dimensional graphics processing libraries (e.g., OpenG L ES), 2D graphics engines (e.g., SG L), and the like.

The surface manager is used to manage the display subsystem and provide fusion of 2D and 3D layers for multiple applications.

The media library supports a variety of commonly used audio, video format playback and recording, and still image files, among others. The media library may support a variety of audio-video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.

The three-dimensional graphic processing library is used for realizing three-dimensional graphic drawing, image rendering, synthesis, layer processing and the like.

The 2D graphics engine is a drawing engine for 2D drawing.

The kernel layer is a layer between hardware and software. The inner core layer at least comprises a display driver, a camera driver, an audio driver and a sensor driver.

In a second section, example application scenarios disclosed in embodiments of the present application are described below.

Fig. 3 exemplarily shows a schematic diagram of a position relationship of the whole eye tracking area of the electronic device 100 and the screen, as shown in (a) of fig. 3, the whole eye tracking area may overlap with the screen area, as shown in (b) of fig. 3, the whole eye tracking area may be larger than the screen area, as shown in (c) of fig. 3, and the whole eye tracking area may be smaller than the screen area.

Wherein the browsing interface is located in the screen.

In the third section, the scope of protection of the claims disclosed in the embodiments of the present application is described below.

Referring to fig. 4, fig. 4 is a flowchart illustrating a recommendation method based on eye tracking according to an embodiment of the present application, and the recommendation method is applied to an electronic device including a camera module.

Step 401: when the user is detected to browse the interface, the fixation point of the user aiming at the multi-frame image in the browsing interface is obtained according to the eyeball tracking technology.

The multi-frame images are a plurality of images with a coherent time relation in a preset time period, namely when the multi-frame images are in a state of browsing and sliding, the multi-frame images are collected, and eyeball tracking is carried out on each image.

Step 402: at least one target image area is determined from the point of regard.

In one possible example, the determining at least one target image region according to the gaze point includes: acquiring the fixation point duration of each image in the multi-frame images; screening out at least one target fixation point with the length of time longer than the preset time length in each image; and determining at least one target image area in the display interface according to the at least one target fixation point.

The gaze point duration may include, but is not limited to, one second, two seconds, three seconds, and the like, and is not limited herein.

As can be seen, in this example, the electronic device determines the interest image region based on the gaze point information of the user, so that the accuracy and intelligence of recommendation based on eye tracking are improved.

Step 403: and analyzing the at least one target image area, and determining a plurality of interest point characteristic information.

In one possible example, the parsing the at least one target image region to determine a plurality of interest point feature information includes: extracting image information of the at least one target image area; inquiring a preset database according to the image information to obtain a first interest point characteristic information set related to the image information; acquiring character information corresponding to each image information in the at least one target image area; obtaining a second interest point characteristic information set associated with the text information according to the text information; and associating the first interest point characteristic information set with the second interest point characteristic information set to obtain a third interest point characteristic information set, wherein the third interest point characteristic information set contains a plurality of target interest point characteristic information.

The preset data may be factory set or obtained according to cloud platform loading, and is not limited uniquely here.

The association may be cross-associated, that is, each feature information of interest point in the first feature information set is associated with each feature information of interest point in the second feature information set, which is not limited herein.

As shown in fig. 5, fig. 5 is an interface schematic diagram based on eyeball tracking, when a user browses a shopping interface, the user detects that a region corresponding to a feature 3 is a target image region through an eyeball tracking technology, the image information of the region is a moon, and obtains a first interest point feature information set related to the moon, where the first interest point feature information set is { white, crescent, circular, mid-autumn moon cake, ChangE, rabbit, ornament, etc }, and if the above feature is a crescent hanging neck, a second interest point feature information set corresponding to the crescent hanging neck is obtained, where the second interest point feature information set is { crescent, jade, white, ornament, bracelet, foot chain, ornament, etc.), so that the first interest point feature information set is associated with the second interest point feature information set to obtain a third interest point feature information set { crescent, white, ornament, hand chain, foot chain, ornament, etc An ornament. Foot chain, bracelet, white, etc.).

Specifically, the associating the first interest point feature information set with the second interest point feature information set includes: calculating the correlation degree of each interest point feature information in the first interest point feature information set and each interest point feature information in the second interest point feature information set; and screening out the interest point characteristic information with the correlation degree larger than the preset correlation degree to obtain a third interest point characteristic information set.

The correlation may be calculated in a one-to-one correspondence manner, or may be calculated as an average value in a one-to-many manner, which is not limited herein.

As can be seen, in this example, when determining a plurality of interest point feature information, the electronic device not only extracts interest features through the image information, but also processes the interest features in combination with the text features corresponding to the image information, that is, the image features and the text features are considered, so that the interest range of the interest point feature information is expanded, the too large error of the interest point feature information is effectively avoided, and the accuracy and the intelligence of recommendation based on eye tracking are improved.

In one possible example, the parsing the at least one target image region to determine a plurality of interest point feature information includes: extracting image information of the at least one target image area; screening out target image information with the number of times greater than the preset similarity number; taking the target image information as an initial characteristic and bringing the target image information into a preset training model to obtain a fourth interest point characteristic information set; acquiring historical viewing information of the target user; extracting historical interest point characteristic information of the historical viewing information; and correcting the fourth interest point characteristic information set according to the historical interest point characteristic information to obtain a plurality of target interest characteristic points.

Therefore, in this example, after extracting the target image information in the real-time interface, the electronic device further accurately corrects the feature information of the interest point by combining the historical viewing information, so as to obtain the recommendation information satisfied by the user.

Optionally, sample training, feature extraction, and feature normalization processing are performed on at least one target image region at the same time, so as to determine feature information of a plurality of interest points.

Step 404: and determining a recommendation strategy according to the characteristic information of the interest points and the image information of the current frame image.

In one possible example, the determining a recommendation policy according to the plurality of interest point feature information and the image information of the current frame image includes: extracting information types in the image information of the current frame image; matching the plurality of interest point characteristic information with the information types, and screening out a plurality of target interest point characteristic information with consistent types; obtaining the click rate of each interest characteristic information in the plurality of target interest characteristic information; and recommending the corresponding interest point characteristic information according to the sequence of the click rate from high to low.

In one possible example, the determining a recommendation policy according to the plurality of interest point feature information and the image information of the current frame image includes: extracting keywords in the image information of the current frame; screening at least one target interest point characteristic information matched with the keywords from the plurality of interest point characteristic information; and recommending the characteristic information of the at least one target interest point randomly.

Optionally, extracting position information in the image information of the current frame, and screening out at least one target interest point feature information located in the position information from the plurality of interest point feature information; and recommending the characteristic information of the at least one target interest point randomly according to the distance of the position.

Therefore, in the example, the electronic device obtains the push strategy according to the image information of the current frame and the historical interest point feature information, namely, the interest features of the user are overlapped and corrected, the recommendation strategy is updated, more accurate information is further recommended to the user, the accuracy and the intelligence of recommendation based on eyeball tracking are improved, and the user experience is further improved.

Step 405: and recommending information according to the recommendation strategy.

When information recommendation is performed, the area amount of the recommendation interface can be adjusted according to the relevance degree of the target interest point feature information in the recommendation strategy.

Optionally, the target interest point feature information with high degree of association is placed in the region of the most central position, and the target interest point feature information with low degree of association is placed in the region of the bottom, which is not limited uniquely here.

It will be appreciated that the electronic device, in order to implement the above-described functions, comprises corresponding hardware and/or software modules for performing the respective functions. The present application is capable of being implemented in hardware or a combination of hardware and computer software in conjunction with the exemplary algorithm steps described in connection with the embodiments disclosed herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, with the embodiment described in connection with the particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In this embodiment, the electronic device may be divided into functional modules according to the above method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module may be implemented in the form of hardware. It should be noted that the division of the modules in this embodiment is schematic, and is only a logic function division, and there may be another division manner in actual implementation.

In the case of dividing each function module according to each function, fig. 6 shows a schematic diagram of the eyeball tracking based recommendation apparatus, as shown in fig. 6, the eyeball tracking based recommendation apparatus 600 is applied to an electronic device, the electronic device includes a camera module, and the eyeball tracking based recommendation apparatus 600 may include: a processing unit 601 and a communication unit 602.

The processing unit 601 is configured to, when it is detected that a user browses an interface, acquire a gaze point of the user for a plurality of frame images in a browsing interface according to an eyeball tracking technology; and for determining at least one target image area from the point of regard; the system is used for analyzing the at least one target image area and determining a plurality of interest point characteristic information; the recommendation strategy is determined according to the characteristic information of the interest points and the image information of the current frame image; and the information recommendation module is used for recommending information according to the recommendation strategy.

Among other things, processing unit 601 may be used to enable the electronic device to perform steps 401-405, etc., described above, and/or other processes for the techniques described herein.

It should be noted that all relevant contents of each step related to the above method embodiment may be referred to the functional description of the corresponding functional module, and are not described herein again.

The electronic device provided by the embodiment is used for executing the recommendation method based on eye tracking, so that the same effect as the implementation method can be achieved.

In case an integrated unit is employed, the electronic device may comprise a processing module, a storage module and a communication module. The processing module may be configured to control and manage actions of the electronic device, and for example, may be configured to support the electronic device to execute steps executed by the processing unit 601 and the communication unit 602. The memory module may be used to support the electronic device in executing stored program codes and data, etc. The communication module can be used for supporting the communication between the electronic equipment and other equipment.

The processing module may be a processor or a controller. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. A processor may also be a combination of computing functions, e.g., a combination of one or more microprocessors, a Digital Signal Processing (DSP) and a microprocessor, or the like. The storage module may be a memory. The communication module may specifically be a radio frequency circuit, a bluetooth chip, a Wi-Fi chip, or other devices that interact with other electronic devices.

In an embodiment, when the processing module is a processor and the storage module is a memory, the electronic device according to this embodiment may be a device having the structure shown in fig. 1.

The present embodiment also provides a computer storage medium, in which computer instructions are stored, and when the computer instructions are run on an electronic device, the electronic device executes the above related method steps to implement the eyeball tracking based recommendation method in the above embodiments.

The present embodiment also provides a computer program product, which when running on a computer, causes the computer to execute the above related steps to implement the eyeball tracking based recommendation method in the above embodiments.

In addition, embodiments of the present application also provide an apparatus, which may be specifically a chip, a component or a module, and may include a processor and a memory connected to each other; the memory is used for storing computer execution instructions, and when the device runs, the processor can execute the computer execution instructions stored in the memory, so that the chip can execute the recommendation method based on eyeball tracking in the above method embodiments.

The electronic device, the computer storage medium, the computer program product, or the chip provided in this embodiment are all configured to execute the corresponding method provided above, so that the beneficial effects achieved by the electronic device, the computer storage medium, the computer program product, or the chip may refer to the beneficial effects in the corresponding method provided above, and are not described herein again.

Through the description of the above embodiments, those skilled in the art will understand that, for convenience and simplicity of description, only the division of the above functional modules is used as an example, and in practical applications, the above function distribution may be completed by different functional modules as needed, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a module or a unit may be divided into only one logic function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another apparatus, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially or partially contributed to by the prior art, or all or part of the technical solutions may be embodied in the form of a software product, where the software product is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. The recommendation method based on eyeball tracking is applied to electronic equipment, wherein the electronic equipment comprises a camera module and comprises the following steps:

when the user is detected to browse the interface, acquiring a fixation point of the user aiming at a plurality of frames of images in the browsing interface according to an eyeball tracking technology;

determining at least one target image area according to the fixation point;

analyzing the at least one target image area, and determining a plurality of interest point characteristic information;

determining a recommendation strategy according to the characteristic information of the interest points and the image information of the current frame image;

and recommending information according to the recommendation strategy.

2. The method of claim 1, wherein the parsing the at least one target image region to determine a plurality of point of interest feature information comprises:

extracting image information of the at least one target image area;

inquiring a preset database according to the image information to obtain a first interest point characteristic information set related to the image information;

acquiring character information corresponding to each image information in the at least one target image area;

obtaining a second interest point characteristic information set associated with the text information according to the text information;

and associating the first interest point characteristic information set with the second interest point characteristic information set to obtain a third interest point characteristic information set, wherein the third interest point characteristic information set contains a plurality of target interest point characteristic information.

3. The method of claim 2, wherein associating the first set of point of interest feature information with the second set of point of interest feature information comprises:

calculating the correlation degree of each interest point feature information in the first interest point feature information set and each interest point feature information in the second interest point feature information set;

and screening out the interest point characteristic information with the correlation degree larger than the preset correlation degree to obtain a third interest point characteristic information set.

4. The method of claim 1, wherein the parsing the at least one target image region to determine a plurality of point of interest feature information comprises:

extracting image information of the at least one target image area;

screening out target image information with the number of times greater than the preset similarity number;

taking the target image information as an initial characteristic and bringing the target image information into a preset training model to obtain a fourth interest point characteristic information set;

acquiring historical viewing information of the target user;

extracting historical interest point characteristic information of the historical viewing information;

and correcting the fourth interest point characteristic information set according to the historical interest point characteristic information to obtain a plurality of target interest characteristic points.

5. The method of claim 1, wherein determining a recommendation strategy according to the plurality of interest point feature information and image information of the current frame image comprises:

extracting information types in the image information of the current frame image;

matching the plurality of interest point characteristic information with the information types, and screening out a plurality of target interest point characteristic information with consistent types;

obtaining the click rate of each interest characteristic information in the plurality of target interest characteristic information;

and recommending the corresponding interest point characteristic information according to the sequence of the click rate from high to low.

6. The method of claim 1, wherein determining a recommendation strategy according to the plurality of interest point feature information and image information of the current frame image comprises:

extracting keywords in the image information of the current frame;

screening at least one target interest point characteristic information matched with the keywords from the plurality of interest point characteristic information;

and recommending the characteristic information of the at least one target interest point randomly.

7. The method of any of claims 1-6, wherein determining at least one target image region from the gaze point comprises:

acquiring the fixation point duration of each image in the multi-frame images;

screening out at least one target fixation point with the length of time longer than the preset time length in each image;

and determining at least one target image area in the display interface according to the at least one target fixation point.

8. An eyeball tracking based recommendation device is characterized by comprising a processing unit and a communication unit, wherein,

9. An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-7.

10. A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to any one of claims 1-7.