CN112487946A

CN112487946A - Human body moving target removing method and device, mobile terminal and storage medium

Info

Publication number: CN112487946A
Application number: CN202011354010.7A
Authority: CN
Inventors: 徐爱辉; 王�琦
Original assignee: Nubia Technology Co Ltd
Current assignee: Nubia Technology Co Ltd
Priority date: 2020-11-26
Filing date: 2020-11-26
Publication date: 2021-03-12

Abstract

The invention discloses a method and a device for removing a human body moving target, a mobile terminal and a storage medium, wherein the method comprises the following steps: previewing a shooting scene in a mobile terminal; extracting a human body moving target in the shooting scene, and acquiring key point characteristics of the human body moving target; identifying key point characteristics of the human body moving target, and matching corresponding human body posture characteristic types; and activating a photographing function of automatically removing the human body moving target matched with the human body posture characteristic type. According to the embodiment of the invention, the irrelevant human body moving target can be automatically removed from the mobile terminal during shooting preview, so that a special shooting effect is achieved, different shooting functions of the mobile terminal are added, and the user experience is improved.

Description

Human body moving target removing method and device, mobile terminal and storage medium

Technical Field

The invention relates to the field of mobile terminals, in particular to a method and a device for removing a human body moving target, a mobile terminal and a storage medium.

Background

Currently, the increasing popularity of mobile terminals, users using mobile terminals are increasing, and users use mobile terminals more and more frequently in daily life, so that the mobile terminal has become one of the mobile devices indispensable to the users.

At present, the shooting function of the mobile terminal is getting stronger, and the user can take various photos by using the shooting function. When a person travels outside, when taking a picture, the person and a certain scene are wanted to be taken, but at the moment, if irrelevant passerby appears in a shooting interface of a camera, irrelevant passerby appears in the shot picture, and the shot picture may not be wanted by the user, which affects user experience.

Disclosure of Invention

In view of this, the method and the device for removing the human body moving object, the mobile terminal and the storage medium provided in the embodiments of the present invention can automatically remove an irrelevant human body moving object in the mobile terminal during shooting preview, so as to achieve a special shooting effect, increase different shooting functions of the mobile terminal, and improve user experience.

The technical scheme adopted by the invention for solving the technical problems is as follows:

according to an aspect of the present invention, there is provided a method for removing a moving object of a human body, the method comprising:

previewing a shooting scene in a mobile terminal;

extracting a human body moving target in the shooting scene, and acquiring key point characteristics of the human body moving target;

identifying key point characteristics of the human body moving target, and matching corresponding human body posture characteristic types;

and activating a photographing function of automatically removing the human body moving target matched with the human body posture characteristic type.

In one possible design, the extracting of the human moving object in the shooting scene includes:

extracting a human body moving target in the shooting scene through face detection;

acquiring the central position of the human body moving target through motion detection;

and segmenting the image of the human body moving target according to the central position of the human body moving target, so that the segmented image only contains the human body moving target as much as possible.

In one possible design, the obtaining key point features of the human motion target includes:

estimating the image which is divided and only comprises the human body moving target by adopting a first preset algorithm, obtaining two-dimensional key point coordinates of the human body moving target as key point characteristics of the human body moving target, and recording the positions of the key point coordinates.

In one possible design, the first preset algorithm includes a deep learning algorithm.

In one possible design, before the identifying the key point features of the human motion target and matching the corresponding human posture category, the method further includes: the human body posture characteristic types are defined in advance, preset human body posture characteristic types are formed, and human body posture characteristics corresponding to the human body posture characteristic types are stored.

In one possible design, the identifying key point features of the human motion target and matching corresponding human posture feature types include:

and matching the key point characteristics of the human motion target with the human posture characteristics in the preset human posture characteristic types by adopting a second preset algorithm, and identifying the human posture characteristic type which is most matched with the key point characteristics of the human motion target.

In one possible design, the second predetermined algorithm is a nearest neighbor algorithm.

According to another aspect of the present invention, there is provided an apparatus for removing a moving object of a human body, the apparatus comprising: the device comprises a preview module, an extraction module, an identification module and an excitation module; wherein:

the preview module is used for previewing a shooting scene in the mobile terminal;

the extraction module is used for extracting a human body moving target in the shooting scene and acquiring key point characteristics of the human body moving target;

the recognition module is used for recognizing the key point characteristics of the human body moving target and matching the corresponding human body posture characteristic types;

the excitation module is used for exciting the photographing function of automatically removing the human body moving target matched with the human body posture characteristic type.

According to an aspect of the present invention, there is provided a mobile terminal including: the human body moving object removing method comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the computer program realizes the steps of the human body moving object removing method provided by the embodiment of the invention when being executed by the processor.

According to an aspect of the present invention, there is provided a storage medium having stored thereon a program of a method of human moving object removal, the program of the method of human moving object removal implementing the steps of the method of human moving object removal provided by the embodiments of the present invention when executed by a processor.

Compared with the related art, the method and the device for removing the human body moving target, the mobile terminal and the storage medium provided by the embodiment of the invention comprise the following steps: previewing a shooting scene in a mobile terminal; extracting a human body moving target in the shooting scene, and acquiring key point characteristics of the human body moving target; identifying key point characteristics of the human body moving target, and matching corresponding human body posture characteristic types; and activating a photographing function of automatically removing the human body moving target matched with the human body posture characteristic type. According to the embodiment of the invention, the shooting scene is previewed in the mobile terminal, the human body moving target is extracted from the shooting scene, the key point characteristics of the human body moving target are obtained, the key point characteristics of the human body moving target are identified, the corresponding human body posture characteristic types are matched, and the shooting function of automatically removing the human body moving target matched with the human body posture characteristic types is excited, so that the irrelevant human body moving target is automatically removed in the mobile terminal during shooting preview, the shooting special effect is achieved, different shooting functions of the mobile terminal are increased, and the user experience is improved.

Drawings

Fig. 1 is a schematic diagram of a hardware structure of a mobile terminal implementing various embodiments of the present invention;

fig. 2 is a diagram of a communication network system architecture according to an embodiment of the present invention;

fig. 3 is a schematic flowchart of a method for removing a moving object of a human body according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of removing a human motion object matching with a human pose feature type according to an embodiment of the present invention;

FIG. 5 is a schematic structural diagram of a human body moving object removing device according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of a mobile terminal according to an embodiment of the present invention.

The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.

Detailed Description

In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in itself. Thus, "module", "component" or "unit" may be used mixedly.

It should be noted that the terms first, second and the like in the description and in the claims, and in the drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.

The terminal may be implemented in various forms. For example, the terminal described in the present invention may include a mobile terminal such as a mobile phone, a tablet computer, a notebook computer, a palmtop computer, a Personal Digital Assistant (PDA), a Portable Media Player (PMP), a navigation device, a wearable device, a smart band, a pedometer, and the like, and a fixed terminal such as a Digital TV, a desktop computer, and the like.

The following description will be given by way of example of a mobile terminal, and it will be understood by those skilled in the art that the construction according to the embodiment of the present invention can be applied to a fixed type terminal, in addition to elements particularly used for mobile purposes.

Referring to fig. 1, which is a schematic diagram of a hardware structure of a mobile terminal for implementing various embodiments of the present invention, the mobile terminal 100 may include: RF (Radio Frequency) unit 101, WiFi module 102, audio output unit 103, a/V (audio/video) input unit 104, sensor 105, display unit 106, user input unit 107, interface unit 108, memory 109, processor 110, and power supply 111. Those skilled in the art will appreciate that the mobile terminal architecture shown in fig. 1 is not intended to be limiting of mobile terminals, which may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.

The following describes each component of the mobile terminal in detail with reference to fig. 1:

the radio frequency unit 101 may be configured to receive and transmit signals during information transmission and reception or during a call, and specifically, receive downlink information of a base station and then process the downlink information to the processor 110; in addition, the uplink data is transmitted to the base station. Typically, radio frequency unit 101 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. In addition, the radio frequency unit 101 can also communicate with a network and other devices through wireless communication. The wireless communication may use any communication standard or protocol, including but not limited to GSM (Global System for Mobile communications), GPRS (General Packet Radio Service), CDMA2000(Code Division Multiple Access 2000), WCDMA (Wideband Code Division Multiple Access), TD-SCDMA (Time Division-Synchronous Code Division Multiple Access), FDD-LTE (Frequency Division duplex Long Term Evolution), and TDD-LTE (Time Division duplex Long Term Evolution).

WiFi belongs to short-distance wireless transmission technology, and the mobile terminal can help a user to receive and send e-mails, browse webpages, access streaming media and the like through the WiFi module 102, and provides wireless broadband internet access for the user. Although fig. 1 shows the WiFi module 102, it is understood that it does not belong to the essential constitution of the mobile terminal, and may be omitted entirely as needed within the scope not changing the essence of the invention.

The audio output unit 103 may convert audio data received by the radio frequency unit 101 or the WiFi module 102 or stored in the memory 109 into an audio signal and output as sound when the mobile terminal 100 is in a call signal reception mode, a call mode, a recording mode, a voice recognition mode, a broadcast reception mode, or the like. Also, the audio output unit 103 may also provide audio output related to a specific function performed by the mobile terminal 100 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 103 may include a speaker, a buzzer, and the like.

The a/V input unit 104 is used to receive audio or video signals. The a/V input Unit 104 may include a Graphics Processing Unit (GPU) 1041 and a microphone 1042, the Graphics processor 1041 Processing image data of still pictures or video obtained by an image capturing device (e.g., a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 106. The image frames processed by the graphic processor 1041 may be stored in the memory 109 (or other storage medium) or transmitted via the radio frequency unit 101 or the WiFi module 102. The microphone 1042 may receive sounds (audio data) via the microphone 1042 in a phone call mode, a recording mode, a voice recognition mode, or the like, and may be capable of processing such sounds into audio data. The processed audio (voice) data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 101 in case of a phone call mode. The microphone 1042 may implement various types of noise cancellation (or suppression) algorithms to cancel (or suppress) noise or interference generated in the course of receiving and transmitting audio signals.

The mobile terminal 100 also includes at least one sensor 105, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 1061 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 1061 and/or a backlight when the mobile terminal 100 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally, three axes), can detect the magnitude and direction of gravity when stationary, and can be used for applications of recognizing the posture of a mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer and tapping), and the like; as for other sensors such as a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which can be configured on the mobile phone, further description is omitted here.

The display unit 106 is used to display information input by a user or information provided to the user. The Display unit 106 may include a Display panel 1061, and the Display panel 1061 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.

The user input unit 107 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the mobile terminal. Specifically, the user input unit 107 may include a touch panel 1071 and other input devices 1072. The touch panel 1071, also referred to as a touch screen, may collect a touch operation performed by a user on or near the touch panel 1071 (e.g., an operation performed by the user on or near the touch panel 1071 using a finger, a stylus, or any other suitable object or accessory), and drive a corresponding connection device according to a predetermined program. The touch panel 1071 may include two parts of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 110, and can receive and execute commands sent by the processor 110. In addition, the touch panel 1071 may be implemented in various types, such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to the touch panel 1071, the user input unit 107 may include other input devices 1072. In particular, other input devices 1072 may include, but are not limited to, one or more of a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, a joystick, and the like, and are not limited to these specific examples.

Further, the touch panel 1071 may cover the display panel 1061, and when the touch panel 1071 detects a touch operation thereon or nearby, the touch panel 1071 transmits the touch operation to the processor 110 to determine the type of the touch event, and then the processor 110 provides a corresponding visual output on the display panel 1061 according to the type of the touch event. Although the touch panel 1071 and the display panel 1061 are shown in fig. 1 as two separate components to implement the input and output functions of the mobile terminal, in some embodiments, the touch panel 1071 and the display panel 1061 may be integrated to implement the input and output functions of the mobile terminal, and is not limited herein.

The interface unit 108 serves as an interface through which at least one external device is connected to the mobile terminal 100. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 108 may be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within the mobile terminal 100 or may be used to transmit data between the mobile terminal 100 and external devices.

The memory 109 may be used to store software programs as well as various data. The memory 109 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 109 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The processor 110 is a control center of the mobile terminal, connects various parts of the entire mobile terminal using various interfaces and lines, and performs various functions of the mobile terminal and processes data by operating or executing software programs and/or modules stored in the memory 109 and calling data stored in the memory 109, thereby performing overall monitoring of the mobile terminal. Processor 110 may include one or more processing units; preferably, the processor 110 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 110.

The mobile terminal 100 may further include a power supply 111 (e.g., a battery) for supplying power to various components, and preferably, the power supply 111 may be logically connected to the processor 110 via a power management system, so as to manage charging, discharging, and power consumption management functions via the power management system.

Although not shown in fig. 1, the mobile terminal 100 may further include a bluetooth module or the like, which is not described in detail herein.

In order to facilitate understanding of the embodiments of the present invention, a communication network system on which the mobile terminal of the present invention is based is described below.

Referring to fig. 2, fig. 2 is an architecture diagram of a communication Network system according to an embodiment of the present invention, where the communication Network system is an LTE system of a universal mobile telecommunications technology, and the LTE system includes a UE (User Equipment) 201, an E-UTRAN (Evolved UMTS Terrestrial Radio Access Network) 202, an EPC (Evolved Packet Core) 203, and an IP service 204 of an operator, which are in communication connection in sequence.

Specifically, the UE201 may be the terminal 100 described above, and is not described herein again.

The E-UTRAN202 includes eNodeB2021 and other eNodeBs 2022, among others. Among them, the eNodeB2021 may be connected with other eNodeB2022 through backhaul (e.g., X2 interface), the eNodeB2021 is connected to the EPC203, and the eNodeB2021 may provide the UE201 access to the EPC 203.

The EPC203 may include an MME (Mobility Management Entity) 2031, an HSS (Home Subscriber Server) 2032, other MMEs 2033, an SGW (Serving gateway) 2034, a PGW (PDN gateway) 2035, and a PCRF (Policy and Charging Rules Function) 2036, and the like. The MME2031 is a control node that handles signaling between the UE201 and the EPC203, and provides bearer and connection management. HSS2032 is used to provide registers to manage functions such as home location register (not shown) and holds subscriber specific information about service characteristics, data rates, etc. All user data may be sent through SGW2034, PGW2035 may provide IP address assignment for UE201 and other functions, and PCRF2036 is a policy and charging control policy decision point for traffic data flow and IP bearer resources, which selects and provides available policy and charging control decisions for a policy and charging enforcement function (not shown).

The IP services 204 may include the internet, intranets, IMS (IP Multimedia Subsystem), or other IP services, among others.

Although the LTE system is described as an example, it should be understood by those skilled in the art that the present invention is not limited to the LTE system, but may also be applied to other wireless communication systems, such as GSM, CDMA2000, WCDMA, TD-SCDMA, and future new network systems.

Based on the above mobile terminal hardware structure and communication network system, the present invention provides various embodiments of the method.

In one embodiment, as shown in fig. 3 and 4, the present invention provides a method of human motion object removal based on human posture, the method comprising:

s1, the mobile terminal previews the shooting scene. The shooting scene is required to be as simple as possible, and cannot be interfered by too many complex objects, otherwise, the accuracy of human body posture estimation can be influenced.

And S2, extracting the human motion target in the shooting scene, and acquiring the key point characteristics of the human motion target.

And S3, recognizing the key point characteristics of the human motion target, and matching the corresponding human posture characteristic types.

And S4, activating a photographing function for automatically removing the human body moving object matched with the human body posture characteristic type.

In the embodiment, a shooting scene is previewed in the mobile terminal, the human body moving target is extracted from the shooting scene, the key point characteristics of the human body moving target are obtained, the key point characteristics of the human body moving target are identified, the corresponding human body posture characteristic types are matched, and the shooting function of automatically removing the human body moving target matched with the human body posture characteristic types is stimulated, so that the unrelated human body moving target is automatically removed in the mobile terminal when the shooting preview is carried out, the shooting special effect is achieved, different shooting functions of the mobile terminal are increased, and the user experience is improved.

In one embodiment, in step S2, the extracting a human moving object in the shooting scene and acquiring a key point feature of the human moving object includes:

and S21, extracting a human body moving target in the shooting scene through human face detection.

For a shooting scene in which a human body faces a lens, the human body can be kept in a static state and also can be kept in a moving state.

If the human body posture of a single person is recognized, only one person can be in the shooting view field. When shooting, the distance between the human body and the lens cannot be too large, and the human body can be kept still or moved when shooting.

If human body gestures of multiple persons are recognized, multiple persons can be in the shooting field of view. When shooting, the human body can not be too big away from the lens. The shooting can be kept still or in a moving state.

Preferably, a face detection method of MTCNN (Multi-Task Convolutional Neural Network) is adopted to perform fast and efficient face detection so as to extract a human moving object in the shooting scene.

And S22, acquiring the central position of the human body moving target through motion detection.

Preferably, the central position of the human body moving target is rapidly acquired by adopting a motion detection method of Gaussian background modeling. When the Gaussian background modeling is adopted for motion detection, when a human body faces away from a lens, the human body needs to keep a motion state for a period of time so that the lens can determine the approximate position of the human body, and then the human body can keep a static state.

The gaussian background modeling is a background representation method based on pixel sample statistical information in the prior art, and can be used for modeling a complex dynamic background by representing the background by using statistical information (such as mode quantity, mean value and standard deviation of each mode) such as probability density of a large number of sample values of a pixel in a long time and then judging a target pixel by using statistical difference (such as 3 sigma principle).

And S23, segmenting the image of the human body moving target according to the central position of the human body moving target, so that the segmented image only contains the human body moving target as much as possible.

S24, estimating the image which is divided and only comprises the human motion target by adopting a first preset algorithm, obtaining two-dimensional (2D) key point coordinates of the human motion target as key point characteristics of the human motion target, and recording the position of the key point coordinates.

Preferably, the first preset algorithm comprises a deep learning algorithm.

In one embodiment, before the step S3 of identifying the key point features of the human motion target and matching the corresponding human pose category, the method further includes: the human body posture characteristic types are defined in advance, preset human body posture characteristic types are formed, and human body posture characteristics corresponding to the human body posture characteristic types are stored.

The human body posture characteristic category at least comprises one of the following characteristic categories: standing (e.g., open hands standing), running, and jumping.

In one embodiment, in step S3, the identifying key point features of the human motion target and matching corresponding human pose feature categories include:

Preferably, the second preset algorithm comprises a Nearest Neighbor algorithm (k-Nearest Neighbor algorithm, k-Nearest Neighbor, kNN algorithm). The kNN algorithm is that most of k nearest neighbor samples of a sample in the feature space are in a class, and then the sample also belongs to the class and has the features of the samples on the class. In the method, the classification decision is determined according to the classification of one or more samples in the nearest neighbor.

In one embodiment, in the step S4, the activating the photographing function of automatically removing the human moving object matched with the human posture feature category includes:

and according to the matched human body posture characteristic types, the photographing function of automatically removing the human body moving target matched with the human body posture characteristic types is excited, and the automatically photographed photos are stored. As shown in fig. 4, the human moving object in the box is removed.

In this embodiment, when a human body is captured to make a certain human body posture action (for example, standing with both hands open), the mobile terminal automatically recognizes the human body posture action, recognizes a human body posture characteristic type most matched with the human body posture action characteristic, and activates a photographing function of automatically removing the human body moving target matched with the human body posture characteristic type.

The human body moving object removing method based on the human body posture provided by the embodiment of the invention has more application scenes, for example, when a person travels outside, the person wants to shoot the person and a certain scene. However, no other person helps at this time, and no other person is wanted to be in the shot picture, so that the image processing method based on the human body posture provided by the embodiment of the invention can remove the irrelevant passerby in the shooting preview through the specific posture recognition.

In one embodiment, as shown in fig. 5, the present invention provides an apparatus for human moving object removal based on human posture, the apparatus comprising: the device comprises a preview module 10, an extraction module 20, a recognition module 30 and an excitation module 40; wherein:

the preview module 10 is configured to preview a shooting scene in the mobile terminal. The shooting scene is required to be as simple as possible, and cannot be interfered by too many complex objects, otherwise, the accuracy of human body posture estimation can be influenced.

The extraction module 20 is configured to extract a human moving object in the shooting scene, and obtain a key point feature of the human moving object.

The recognition module 30 is configured to recognize the key point features of the human motion target, and match the corresponding human posture feature types.

The excitation module 40 is configured to excite a photographing function of automatically removing the human motion object matched with the human posture feature type.

In an embodiment, the extracting module 20 is specifically configured to:

Preferably, the first preset algorithm comprises a deep learning algorithm.

In one embodiment, the apparatus further includes a storage module, configured to store predefined human posture feature types, form preset human posture feature types, and store human posture features corresponding to the human posture feature types.

In an embodiment, the identification module 30 is specifically configured to:

In one embodiment, the storage module is further configured to store the automatically photographed photo.

It should be noted that the device embodiment and the method embodiment belong to the same concept, and specific implementation processes thereof are described in detail in the method embodiment, and technical features in the method embodiment are correspondingly applicable in the device embodiment, which is not described herein again.

In addition, an embodiment of the present invention further provides a mobile terminal, as shown in fig. 6, where the mobile terminal 900 includes: a memory 902, a processor 901 and one or more computer programs stored in the memory 902 and executable on the processor 901, the memory 902 and the processor 901 being coupled together by a bus system 903, the one or more computer programs being executed by the processor 901 to implement the following steps of a method for human body posture-based human body moving object removal provided by an embodiment of the present invention:

The method disclosed in the above embodiments of the present invention may be applied to the processor 901, or implemented by the processor 901. The processor 901 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be implemented by an integrated logic circuit of hardware or an instruction in the form of software in the processor 901. The processor 901 may be a general purpose processor, a DSP, or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The processor 901 may implement or perform the methods, steps and logic blocks disclosed in the embodiments of the present invention. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed by the embodiment of the invention can be directly implemented by a hardware decoding processor, or can be implemented by combining hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 902, and the processor 901 reads the information in the memory 902 and performs the steps of the foregoing method in combination with the hardware thereof.

It is to be understood that the memory 902 of embodiments of the present invention may be either volatile memory or nonvolatile memory, and may include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic Random Access Memory (FRAM), a magnetic Random Access Memory (Flash Memory) or other Memory technologies, a Compact disc Read-Only Memory (CD-ROM), a Digital Versatile Disc (DVD), or other optical disc storage, magnetic cartridge, magnetic tape, magnetic Disk storage, or other magnetic storage devices; volatile Memory can be Random Access Memory (RAM), and by way of exemplary and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Double Data Rate Synchronous Random Access Memory (ESDRAM), Synchronous Link Dynamic Random Access Memory (SLDRAM), Direct Memory bus Random Access Memory (DRRAM). The described memory for embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.

It should be noted that the above-mentioned embodiment of the mobile terminal and the embodiment of the method belong to the same concept, and the specific implementation process is described in detail in the embodiment of the method, and the technical features in the embodiment of the method are correspondingly applicable in the embodiment of the mobile terminal, which is not described herein again.

In addition, in an exemplary embodiment, the embodiment of the present invention further provides a computer storage medium, specifically a computer readable storage medium, for example, a memory 902 storing a computer program, where the computer storage medium stores one or more programs of a method for human body moving object removal based on human body gesture, and when the one or more programs of the method for human body moving object removal based on human body gesture are executed by a processor 901, the following steps of the method for human body moving object removal based on human body gesture provided by the embodiment of the present invention are implemented:

It should be noted that, the embodiment of the method program for removing the human body moving object based on the human body posture on the computer-readable storage medium and the embodiment of the method belong to the same concept, and the specific implementation process thereof is described in detail in the embodiment of the method, and the technical features in the embodiment of the method are correspondingly applicable in the embodiment of the computer-readable storage medium, which is not described herein again.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.

While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims

1. A method of human motion object removal, the method comprising:

previewing a shooting scene in a mobile terminal;

2. The method of claim 1, wherein the extracting of the human moving object in the shooting scene comprises:

3. The method of claim 2, wherein the obtaining key point features of the human moving object comprises:

4. The method of claim 3, wherein the first pre-set algorithm comprises a deep learning algorithm.

5. The method of claim 1, wherein prior to said identifying keypoint features of the human moving object matching corresponding human pose categories, the method further comprises: the human body posture characteristic types are defined in advance, preset human body posture characteristic types are formed, and human body posture characteristics corresponding to the human body posture characteristic types are stored.

6. The method of claim 5, wherein the identifying key point features of the human motion target, matching corresponding human pose feature classes, comprises:

7. The method of claim 6, wherein the second predetermined algorithm is a nearest neighbor algorithm.

8. An apparatus for removing a moving object of a human body, which is applied to the method for removing the moving object of the human body as claimed in any one of claims 1 to 7, wherein the apparatus comprises: the device comprises a preview module, an extraction module, an identification module and an excitation module; wherein:

9. A mobile terminal, comprising: memory, processor and computer program stored on the memory and executable on the processor, the computer program when executed by the processor implementing the steps of a method of human motion object removal as claimed in any one of claims 1 to 7.

10. A storage medium, characterized in that the storage medium has stored thereon a program of a method of human moving object removal, which when executed by a processor implements the steps of a method of human moving object removal as recited in any one of claims 1 to 7.