WO2017177768A1 - 一种信息处理方法及终端、计算机存储介质 - Google Patents

一种信息处理方法及终端、计算机存储介质 Download PDF

Info

Publication number
WO2017177768A1
WO2017177768A1 PCT/CN2017/074455 CN2017074455W WO2017177768A1 WO 2017177768 A1 WO2017177768 A1 WO 2017177768A1 CN 2017074455 W CN2017074455 W CN 2017074455W WO 2017177768 A1 WO2017177768 A1 WO 2017177768A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
face
area
image
image processing
Prior art date
Application number
PCT/CN2017/074455
Other languages
English (en)
French (fr)
Inventor
吴运声
吴发强
戴阳刚
高雨
时峰
汪倩怡
熊涛
崔凌睿
应磊
Original Assignee
腾讯科技（深圳）有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 腾讯科技（深圳）有限公司 filed Critical 腾讯科技（深圳）有限公司
Publication of WO2017177768A1 publication Critical patent/WO2017177768A1/zh

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/76—Television signal recording
    • H04N5/91—Television signal processing therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/161—Detection; Localisation; Normalisation
    • G06V40/166—Detection; Localisation; Normalisation using acquisition arrangements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30196—Human being; Person
    • G06T2207/30201—Face

Definitions

  • the present invention relates to communication technologies, and in particular, to an information processing method, a terminal, and a computer storage medium.
  • the camera configuration of the terminal is constantly upgraded. It is a trend to use mobile phones, tablets, and notebooks to record video or take high-definition pictures. Users can also share recorded video or high-definition pictures through social applications.
  • the image processing technology (such as the filter technology) for quickly modifying the image quality can be used for image processing.
  • the filter function is single. Since the entire screen contains a plurality of different elements, the brightness and color saturation required for different elements are different, so After adding a filter to the entire screen, the quality of the entire picture will be degraded.
  • the related art there is no effective solution to this problem.
  • the embodiments of the present invention are intended to provide an information processing method, a terminal, and a computer storage medium, which at least solve the problems existing in the prior art and improve the video quality of the recorded video in real time.
  • An information processing method includes:
  • the application is started in the terminal, and the first operation is obtained, and the collection of the first media information is triggered.
  • the terminal identifies the first area according to a preset policy. a first area, where the first area is a local area in each frame of the first media information;
  • the first image processing result and the second image processing result are merged, the complete image fusion information is retrieved, and the complete image fusion information is reused as image information of each frame.
  • the triggering unit is configured to start an application in the terminal, obtain a first operation, and trigger collection of the first media information
  • the identifying unit is configured to: identify, in the process of collecting the first media information, a first area according to a preset policy, where the first area is a partial area in each frame of image information of the first media information;
  • a separating unit configured to separate the first area from the image information of each frame, and record the remaining area of the image information of each frame after separation as a second area
  • the first processing unit is configured to perform processing on the first area by using a first image processing manner to obtain a first image processing result
  • a second processing unit configured to perform processing on the second area by using a second image processing manner to obtain a second image processing result
  • a merging unit configured to fuse the first image processing result and the second image processing result, regenerate the complete image merging information, and re-create the complete image merging information as image information of each frame .
  • the triggering unit, the identifying unit, the separating unit, the first processing unit, the second processing unit, and the merging unit may use a central processing unit (CPU) when performing processing.
  • CPU central processing unit
  • DSP digital signal processor
  • FPGA programmable logic array
  • the embodiment of the invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are configured to execute the information processing method described above.
  • the information processing method of the embodiment of the present invention includes: when the terminal starts the application, the first operation is acquired, and the collection of the first media information is triggered; in the process of collecting the first media information, the terminal identifies the device according to the preset policy. a first area, wherein the first area is a partial area in each frame of the first media information; separating the first area from the image information of each frame, and separating the first area The remaining area of each frame of image information is recorded as a second area; the first area is processed by the first image processing mode to obtain a first image processing result; and the second area is subjected to a second image processing mode.
  • Processing obtaining a second image processing result; performing fusion processing on the first image processing result and the second image processing result, regenerating the complete image fusion information, and re-writing the complete image fusion information as each Image information of one frame.
  • a filter is added to the partial picture in the entire picture. Different local processing is performed to improve the video quality of the recorded video in real time.
  • 1 is a schematic diagram of hardware entities of each party performing information interaction in an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of an implementation process according to Embodiment 1 of the present invention.
  • FIG. 3 is a schematic diagram of a terminal user interface to which an embodiment of the method of the present invention is applied;
  • FIG. 5 is a schematic diagram of local area division by applying an embodiment of the method of the present invention.
  • FIG. 6 is a schematic flowchart of an implementation process of Embodiment 3 of the present invention.
  • FIG. 7 is another schematic diagram of local area division by applying an embodiment of the method of the present invention.
  • FIG. 8 is a schematic structural diagram of a structure according to Embodiment 4 of the present invention.
  • FIG. 9 is a schematic structural diagram of a hardware component according to Embodiment 5 of the present invention.
  • FIG. 1 is a schematic diagram of hardware entities of each party performing information interaction according to an embodiment of the present invention.
  • FIG. 1 includes: a server 11 and a terminal device 21-24.
  • the terminal device 21-24 performs information interaction with a server through a wired network or a wireless network.
  • Terminal equipment includes mobile phones, desktops, PCs, all-in-ones, and the like. Among them, all applications installed in the terminal device or specified applications.
  • the application is started in the terminal (photograph application or recorded video application or image processing application, etc.), and the first operation is obtained (for example, after entering the recorded video application, the camera is turned on to start recording the video.
  • the terminal identifies the first according to the preset policy.
  • An area (which may be a specified area different from other areas, the area may be a face area), the first area being a partial area in each frame of the first media information;
  • An area is separated from the image information of each frame, and the remaining area of the image information of each frame after the separation is recorded as a second area (if the first area is a face area, the second area is a non-human face) a region, or a face-independent region; processing the first region with a first image processing method (such as skin, speckle, blush, etc.) to obtain a first image processing result Processing the second region by using a second image processing mode (such as adjusting filter brightness or color saturation) to obtain a second image processing result; and the first image processing result and the second image Processing results are fused, The complete image fusion information is retrieved and the complete
  • FIG. 1 is only a system architecture example for implementing the embodiment of the present invention.
  • the embodiment of the present invention is not limited to the system structure described in FIG. 1 above, and various embodiments of the present invention are proposed based on the system architecture.
  • Embodiment 1 is a diagrammatic representation of Embodiment 1:
  • FIG. 2 An information processing method according to an embodiment of the present invention is shown in FIG. 2, where the method includes:
  • Step 101 Open an application on the terminal, obtain a first operation, and trigger collection of the first media information.
  • the user is using a terminal (such as the mobile phone 11), and the user interface of the mobile phone 11 includes various types of application icons, as shown in FIG. 3, which is an end user interface including various types of application icons, and the application icons include: The music play icon, the function setting icon, the mail sending and receiving icon, and the like, the user performs the first operation, such as clicking the video processing application icon identified by the A1 with a finger, and entering the video recording processing process, thereby triggering the first media information (such as video). collection. For example, you can record a scene in a room, or you can take a self-portrait and so on.
  • Step 102 The terminal identifies, in the process of collecting the first media information, a first area according to a preset policy, where the first area is a local area in each frame of the first media information.
  • the terminal may capture a local face region in the entire picture in each frame of the first media information through the face recognition and positioning mechanism.
  • the face recognition technology is based on a human face feature, and collects a face image or a video stream in a video recording, first determining whether a face exists in the video stream, if a person exists The face further gives the position and size of the face, and locates the position information of each main facial organ to obtain the respective positions of the facial features in the face.
  • Step 103 Separate the first area from the image information of each frame, and record the remaining area of the image information of each frame after the separation as the second area.
  • the local face region in the entire picture in each frame image information of the identified first media information may be used as the first region, and then the remaining region in the entire screen except the local face region It is the second area. Subsequently, because the characteristics of the first area and the second area are different, the image processing strategies for processing the two are different, that is, different filter technologies are required respectively, as in step 104, the first area is adopted.
  • the first image processing method (such as microdermabrasion, freckle and other filter techniques) performs processing.
  • the second image processing mode is adopted for the second region (such as filter technology such as brightness adjustment and color saturation).
  • the filter performs different local processing, which improves the video quality of the recorded video in real time.
  • Step 104 Perform processing on the first area by using a first image processing manner to obtain a first image processing result.
  • Step 105 Perform processing on the second area by using a second image processing manner to obtain a second image processing result.
  • Step 106 Perform fusion processing on the first image processing result and the second image processing result, regenerate the complete image fusion information, and re-use the complete image fusion information as image information of each frame.
  • a specific implementation process may be: for a video file recorded in real time, the image stream and the audio are respectively acquired from the video, and the image stream is acquired through the camera interface of the Android system, and the video recording interface is used for video recording.
  • the audio is sampled by the microphone; the image of each frame of the image stream is distinguished from the face region and the non-face region, and the face region and the non-face region are separately used by two sets of different different filter technologies respectively.
  • Image processing generating two filter effect image streams, and then using the encoder interface to re-image and encode the two filter effect image streams with filter effects into a video stream, and re-encode the audio into Tone Frequency stream, using audio and video combiner to mix video track and audio track, real-time generation of audio and video recording, partial image processing through different filter technologies, and then re-fusion the image to obtain the final modified real-time recorded video. file.
  • Embodiment 2 is a diagrammatic representation of Embodiment 1:
  • FIG. 4 An information processing method according to an embodiment of the present invention is shown in FIG. 4, where the method includes:
  • Step 201 Open an application on the terminal, obtain a first operation, and trigger collection of the first media information.
  • the user is using a terminal (such as the mobile phone 11), and the user interface of the mobile phone 11 includes various types of application icons, as shown in FIG. 3, which is an end user interface including various types of application icons, and the application icons include: The music play icon, the function setting icon, the mail sending and receiving icon, and the like, the user performs the first operation, such as clicking the video processing application icon identified by the A1 with a finger, and entering the video recording processing process, thereby triggering the first media information (such as video). collection. For example, you can record a scene in a room, or you can take a self-portrait and so on.
  • Step 202 Acquire a face feature value, and determine, according to the face feature value, whether a face is included in each frame of the first media information, and obtain a determination result.
  • the terminal may capture a local face region in the entire picture in each frame of the first media information through the face recognition and positioning mechanism.
  • the face recognition technology is based on a human face feature, and collects a face image or a video stream in a video recording, first determining whether a face exists in the video stream, if a person exists The face further gives the position and size of the face, and locates the position information of each main facial organ to obtain the respective positions of the facial features in the face.
  • Step 203 When the determination result is that the human face is included, the location of the face in the current frame image information is located, and the first area is included in the area corresponding to the location where the face is located.
  • FIG. 5 includes an initial picture on the left side, and the entire picture area of the current frame image information is A1, including a face area and a non-face area, such as a non-person.
  • the face area includes a small cup A3.
  • the position of the face is The corresponding area is A2, and the face area is included in A2.
  • the region is further refined and separated to accurately obtain the face region.
  • Step 204 Separating the first area from the image information of each frame, and recording the remaining area of the image information of each frame after the separation as the second area.
  • the local face region in the entire picture in each frame image information of the identified first media information may be used as the first region, and then the remaining region in the entire screen except the local face region It is the second area. Subsequently, since the characteristics of the first area and the second area are different, the image processing strategies for processing the two are different, that is, different filter technologies are required respectively, as in step 205, the first area is adopted.
  • the first image processing method (such as microdermabrasion, freckle and other filter techniques) performs processing.
  • the second image processing mode is adopted for the second region (such as filter technology such as brightness adjustment and color saturation).
  • the filter performs different local processing, which improves the video quality of the recorded video in real time.
  • Step 205 Perform processing on the first area by using a first image processing manner to obtain a first image processing result.
  • Step 206 Perform processing on the second area by using a second image processing manner to obtain a second image processing result.
  • Step 207 Perform fusion processing on the first image processing result and the second image processing result, regenerate the complete image fusion information, and re-use the complete image fusion information as image information of each frame.
  • a specific implementation process may be: for a video file recorded in real time, the image stream and the audio are respectively acquired from the video, and the image stream is acquired through the camera interface of the Android system, and the video recording interface is used for video recording. Acquire audio through microphone sampling; image Each frame image of the stream determines whether a face is included in each frame image information of the image stream according to the face feature value, so as to distinguish the face region from the non-face region, and respectively face the face region and the non-face region Two sets of targeted different filter technologies are used for partial image processing to generate two filter effect image streams, and then the two filter effect image streams with filter effects are re-image fusion using the encoder interface in real time.
  • the audio video combiner is used to mix the video track and the audio track, and the video image is recorded in real time, and the image processing is performed after performing partial image processing through different filter technologies. Re-converge to get the final modified video file in real time.
  • Embodiment 3 is a diagrammatic representation of Embodiment 3
  • An information processing method is as shown in FIG. 6, and the method includes:
  • Step 301 Open an application on the terminal, obtain a first operation, and trigger collection of the first media information.
  • the user is using a terminal (such as the mobile phone 11), and the user interface of the mobile phone 11 includes various types of application icons, as shown in FIG. 3, which is an end user interface including various types of application icons, and the application icons include: The music play icon, the function setting icon, the mail sending and receiving icon, and the like, the user performs the first operation, such as clicking the video processing application icon identified by the A1 with a finger, and entering the video recording processing process, thereby triggering the first media information (such as video). collection. For example, you can record a scene in a room, or you can take a self-portrait and so on.
  • Step 302 Acquire a face feature value, and determine, according to the face feature value, whether a face of each frame of the first media information includes a face, and obtain a determination result.
  • the terminal may capture a local face region in the entire picture in each frame of the first media information through the face recognition and positioning mechanism.
  • the face recognition technology is based on a human face feature, and collects a face image or a video stream in a video recording, first determining whether a face exists in the video stream, if a person exists The face further gives the position and size of the face, and locates the position information of each main facial organ to obtain the respective positions of the facial features in the face.
  • Step 303 When the determination result is that the face is included, the location of the face in the current frame image information is located, and the first area is included in the area corresponding to the location where the face is located.
  • Step 304 Acquire a location of a face in the current frame image information, and extract face contour information according to the face recognition parameter at the location where the face is located.
  • the face recognition parameters include the size of the face, the relative position of the face and face organs, and the like.
  • FIG. 7 is an example diagram of a region division
  • FIG. 7 includes an initial screen on the left side
  • the entire screen region of the current frame image information is A1, which includes a face region and a non-face region, such as a non-human
  • the face area includes a small cup A3.
  • the area corresponding to the position where the face is located is A2, and the face area A4 is included in the area A2 corresponding to the position where the face is located, specifically according to the face.
  • Identifying the parameters (such as the size of the face, the relative position of the face and face organs) and so on to obtain the contour information of the face, thereby refining the area A2 corresponding to the position where the face is located, and locating the actual face according to the contour information of the face. Area A4, so that the face area is accurately obtained.
  • Step 305 Separating the current frame image information according to the face contour information to obtain a face region and a non-face region, determining the face region as the first region, and determining the non-face region. Is the second area.
  • the local face region in the entire picture in each frame image information of the identified first media information may be used as the first region, and then the remaining region in the entire screen except the local face region It is the second area. Subsequently, since the characteristics of the first area and the second area are different, the image processing strategies for processing the two are different, that is, different filter technologies are required respectively, as in step 306, the first area is adopted.
  • the first image processing method (such as microdermabrasion, freckle and other filter techniques) performs processing.
  • the second image processing mode is adopted for the second region (such as filter technology such as brightness adjustment and color saturation).
  • the filters are added for different local processing, which improves the video quality of the recorded video in real time.
  • Step 306 Perform processing on the face region by using a first image processing manner to obtain a first image processing result.
  • Step 307 Perform processing on the non-face area by using a second image processing manner to obtain a second image processing result.
  • Step 308 Perform fusion processing on the first image processing result and the second image processing result, regenerate the complete image fusion information, and re-use the complete image fusion information as image information of each frame.
  • a specific implementation process may be: for a video file recorded in real time, the image stream and the audio are respectively acquired from the video, and the image stream is acquired through the camera interface of the Android system, and the video recording interface is used for video recording.
  • the face area and the non-face area use two sets of different filter technologies to perform partial image processing, generate two filter effect image streams, and then use the encoder interface to realize two filters with filter effects in real time.
  • the mirror effect image stream is re-image-encoded and encoded into a video stream, and the audio is also re-encoded into an audio stream.
  • the audio video combiner is used to mix the video track and the audio track, and the real-time generation of the audio and video recording is implemented by different filter technologies. After the partial image processing, the image is re-fused to obtain the final modified real-time recorded view. File.
  • the method further includes: before the triggering the collection of the first media information, detecting that the collection module for the first media information collection is enabled and has not yet started. During the collecting operation, the current scene information related to the first media information collection is identified and the current scene information is collected.
  • the method further includes: In the process of collecting the first media information, the terminal performs analysis according to the collected current scene information, and obtains an analysis result; and adaptively selects each frame image for the first media information according to the analysis result.
  • a specific implementation is: when entering the video recording application, the camera is turned on, but only in the corresponding frame of the camera to find the person to be photographed, the external environment or the internal environment, etc., in the process, since the official video recording has not yet begun. Therefore, the CPU is idle.
  • an optional filter can be estimated for the terminal based on the actual situation of the scene displayed by the frame corresponding to the current camera. It is a filter for only the face area, a filter for only the non-face area, or a filter for both the face area and the non-face area (ie 2 filters)
  • the face area and the non-face area can be preprocessed separately in the early stage).
  • the terminal estimation filter may be used according to the history record or the collected user usage habits, etc., for example, the user is a girl, then If it is a self-portrait, then her habit is likely to have the need for make-up and beautification of the facial features, then, you can push the beauty filter, blush filter and so on for the terminal. If the user is continuous shooting, the filter used by the user to record the video last time can be recorded, and when the user continues to record the video next time, the filter used for the last recorded video is pushed in advance for the terminal and the like.
  • Embodiment 4 is a diagrammatic representation of Embodiment 4:
  • the terminal includes:
  • the triggering unit 11 is configured to: open the application in the terminal, obtain the first operation, and trigger the collection of the first media information;
  • the identifying unit 12 is configured to identify the first according to the preset policy in the process of collecting the first media information.
  • a region the first region is a partial region in each frame of the first media information, and the separating unit 13 is configured to: the first region from each of the regions Separating the frame image information, and recording the remaining area of the image information of each frame after the separation as the second area;
  • the first processing unit 14 is configured to process the first area by using the first image processing mode, Obtaining a first image processing result;
  • the second processing unit 15 is configured to process the second region by using a second image processing manner to obtain a second image processing result; and
  • the merging unit 16 is configured to: the first image
  • the processing result and the second image processing result are subjected to fusion processing, and the complete image fusion information is retrieved, and the complete image fusion information is reused as the image information of each frame.
  • the user is using a terminal (such as the mobile phone 11), and the user interface of the mobile phone 11 includes various types of application icons, as shown in FIG. 3, which is a terminal including various types of application icons.
  • the user interface, the application icons include: a music play icon, a function setting icon, a mail sending and receiving icon, etc., the user performs the first operation, such as clicking a video processing application icon identified by the A1 with a finger, and entering a video recording process, thereby triggering the first
  • the collection of a piece of media information (such as video). For example, you can record a scene in a room, or you can take a self-portrait and so on.
  • the terminal may capture a local face region in the entire picture in each frame of the first media information through the face recognition and positioning mechanism.
  • the face recognition technology is based on a human face feature, and collects a face image or a video stream in a video recording, first determining whether a face exists in the video stream, if a person exists The face further gives the position and size of the face, and locates the position information of each main facial organ to obtain the respective positions of the facial features in the face.
  • the remaining region in the entire screen is except for the local face region. Second area.
  • the image processing strategies for processing the two are different, that is, different filter technologies are required respectively, for example, the first image processing mode is adopted for the first area. (such as microdermabrasion, freckle and other filter techniques) for processing, the second region of the second image processing method (such as brightness and color saturation filter technology) Processing, in this way, from the perspective of including a plurality of different elements in the entire picture, the brightness, color saturation and the like required for different elements are different angles, based on this, respectively adding the partial pictures in the entire picture
  • the filter performs different local processing, which improves the video quality of the recorded video in real time.
  • the identifying unit is further configured to: acquire a facial feature value, and determine, according to the facial feature value, whether the image information of each frame of the first media information includes a human face. , get the judgment result;
  • the position of the face in the current frame image information is located, and the first area is included in the area corresponding to the position where the face is located.
  • the separating unit is further configured to: acquire a location of a face in the image information of the current frame, and extract a contour of the face according to the face recognition parameter at a position where the face is located. And separating the current frame image information according to the face contour information to obtain a face region and a non-face region; determining the face region as the first region; determining the non-face region as The second area.
  • the terminal further includes: a detecting unit, configured to: before the triggering the collection of the first media information, detecting that the collection module for the first media information collection is enabled and not yet When the actual collection operation is started, the current scene information related to the first media information collection is identified and the current scene information is collected.
  • a detecting unit configured to: before the triggering the collection of the first media information, detecting that the collection module for the first media information collection is enabled and not yet When the actual collection operation is started, the current scene information related to the first media information collection is identified and the current scene information is collected.
  • the terminal further includes: a selecting unit, configured to: during the process of collecting the first media information, the terminal performs analysis according to the collected current scene information, and obtains an analysis result. And adaptively selecting an image processing mode for performing image processing on each frame of the first media information according to the analysis result; the image processing manner includes: the first image processing mode and/or the Two image processing methods.
  • Embodiment 5 is a diagrammatic representation of Embodiment 5:
  • the above terminal may be an electronic device such as a PC, and may also be as A portable electronic device such as a PAD, a tablet computer or a laptop computer may also be an intelligent mobile terminal such as a mobile phone, and is not limited to the description herein;
  • the server may be constituted by a cluster system and merged into one for realizing functions of each unit.
  • the terminal and the server both include at least a database for storing data and a processor for data processing, or a storage medium provided in the server or a separately set storage medium.
  • a microprocessor for the processor for data processing, a microprocessor, a central processing unit (CPU), a digital signal processor (DSP, Digital Singnal Processor) or programmable logic may be used when performing processing.
  • An FPGA Field-Programmable Gate Array
  • An operation instruction for a storage medium, includes an operation instruction, where the operation instruction may be computer executable code, and the operation instruction is used to implement the information processing method in the foregoing embodiment of the present invention.
  • the apparatus includes a processor 31, a storage medium 32, and at least one external communication interface 33; the processor 31, the storage medium 32, and the external communication interface 33 are all connected by a bus 34.
  • one application scenario is: a variety of filters are added during the video recording process, which can optimize the image quality of the captured image, such as a filter through real-time video recording.
  • the image quality of the skin of the skin Since there are different composition elements in each frame of the entire video recording, the use of a single set of filter technology will lead to a decline in overall image quality, such as adding a filter to the entire image, a single filter, and adding a filter. Will cause the overall picture quality to decline.
  • a composition element (such as a partial landscape part of the entire image) is a problem of poor video recording quality due to insufficient light
  • a composition element (such as The partial character part in the image is a problem of poor video quality caused by the person's skin is not good enough.
  • After a filter is processed if the image quality of the whole image is unsatisfactory, multiple filters are often used for multiple processing, the processing efficiency is low, and adding too many filters causes excessive hardware overhead.
  • the application scenario of the present application includes: 1) collecting current scene information during the period when the user camera is turned on but has not started recording.
  • the current scene is identified by the algorithm; 2)
  • the video recording starts, and the filter style is selected according to the previously identified scene information, and the dim, bright, and normal are optimized respectively. For example: dim style to improve the brightness of the picture, denoising; 3) during the video recording process, tracking the position of the face, targeted to the face area; 4) in the process of video recording, real-time recognition of facial features, on the five senses Optimize targeted makeup, such as: increase blush. You can also make special makeup/filters to add fun and create fun and fun videos.
  • the application scenario adopts an embodiment of the present invention, and a specific implementation is a filter and a dermabrasion algorithm based on precise scenes and face positions, and performing local processing, which can improve the quality of the user's face skin while preserving other location images.
  • the details at the same time, can select the most suitable filter according to different scenes, and the filter is diversified, which greatly improves the image quality of the final video recording.
  • the corresponding processing flow includes the following steps:
  • Step 501 After obtaining each image frame in the real-time recorded video stream, the face detection function detects the position of the face in the image frame, and extracts the contour of the face.
  • Step 502 Separating the image frames according to the contour of the face, and dividing into two parts: a face and a non-human face.
  • Step 503 Perform brightness adjustment on the non-face portion, and remove the filter rendering such as the dry point.
  • step 504 the face part is made into a beauty, and the skin is polished.
  • Step 505 re-mixing the processed face part and the non-face part into a complete image frame.
  • the above process includes: the process of image frame acquisition (getting the entire picture); The process of face detection (recognizing part of the entire picture, such as the face area); the process of image separation (such as separating the face area from the entire picture, ie getting the face area and the non-face area) The process of rendering the filter (such as the rendering function of the filter); the process of using the filter on the face area (such as dermabrasion and freckle, etc.); the process of image fusion (such as after the face area is processed, The face-independent area is re-image-fused, and the processed image is obtained. Since the filter is used only once for each part of the image in the entire process implementation, the above process is used to improve the processing speed and reduce the computational overhead.
  • the embodiment of the invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are configured to execute the information processing method described above.
  • the disclosed apparatus and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner such as: multiple units or components may be combined, or Can be integrated into another system, or some features can be ignored or not executed.
  • the coupling, or direct coupling, or communication connection of the components shown or discussed may be indirect coupling or communication connection through some interfaces, devices or units, and may be electrical, mechanical or other forms. of.
  • the units described above as separate components may or may not be physically separated, and the components displayed as the unit may or may not be physical units, that is, may be located in one place or distributed to multiple network units; Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated into one unit;
  • the unit can be implemented in the form of hardware or in the form of hardware plus software functional units.
  • the foregoing program may be stored in a computer readable storage medium, and the program is executed when executed.
  • the foregoing storage device includes the following steps: the foregoing storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.
  • ROM read-only memory
  • RAM random access memory
  • magnetic disk or an optical disk.
  • optical disk A medium that can store program code.
  • the above-described integrated unit of the present invention may be stored in a computer readable storage medium if it is implemented in the form of a software function module and sold or used as a standalone product.
  • the technical solution of the embodiments of the present invention may be embodied in the form of a software product in essence or in the form of a software product stored in a storage medium, including a plurality of instructions.
  • a computer device (which may be a personal computer, server, or network device, etc.) is caused to perform all or part of the methods described in various embodiments of the present invention.
  • the foregoing storage medium includes various media that can store program codes, such as a mobile storage device, a ROM, a RAM, a magnetic disk, or an optical disk.
  • the information processing method of the embodiment of the present invention includes: when the terminal starts the application, the first operation is acquired, and the collection of the first media information is triggered; in the process of collecting the first media information, the terminal identifies the device according to the preset policy. a first area, wherein the first area is a partial area in each frame of the first media information; separating the first area from the image information of each frame, and separating the first area The remaining area of each frame of image information is recorded as a second area; the first area is processed by the first image processing manner to obtain a first image processing result; Processing the second area by using the second image processing manner to obtain a second image processing result; performing fusion processing on the first image processing result and the second image processing result to obtain complete image fusion information, And the complete image fusion information is re-used as image information of each frame.
  • a filter is added to the partial picture in the entire picture. Different local processing is performed to improve the video quality of the recorded video in real time.

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Physics & Mathematics (AREA)
  • Signal Processing (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Human Computer Interaction (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • General Health & Medical Sciences (AREA)
  • Image Processing (AREA)
  • Image Analysis (AREA)
  • Studio Devices (AREA)

Abstract

本发明实施例公开了一种信息处理方法及终端、计算机存储介质，其中，所述方法包括：触发第一媒体信息的采集；终端在采集所述第一媒体信息的过程中，按照预设策略识别出第一区域，所述第一区域为所述第一媒体信息的每一帧图像信息中的局部区域；将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域；对所述第一区域采用第一图像处理方式进行处理，得到第一图像处理结果；对所述第二区域采用第二图像处理方式进行处理，得到第二图像处理结果；将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息。

Description

一种信息处理方法及终端、计算机存储介质 技术领域
本发明涉及通讯技术，尤其涉及一种信息处理方法及终端、计算机存储介质。
背景技术
随着科技的进步，终端的摄像头配置不断升级，采用手机，平板，笔记本来录制视频或者拍摄高清图片成为一种趋势，用户还可以将录制的视频或者拍摄的高清图片通过社交应用进行信息分享。
以录制的视频的场景为例，在信息分享之前，如果用户对录制的视频画质不满意，可以通过用于对画质进行快速修改美化的图像处理技术(如滤镜技术)进行图像处理。现有技术中，是对整个画面加滤镜，且滤镜功能单一，由于整个画面中包含多种不同元素，不同元素所需的明暗度，色彩饱和度等等画质效果是不同的，因此，对整个画面加滤镜后，会引起整个画面质量的下降。然而，相关技术中，对于该问题，尚无有效解决方案。
发明内容
有鉴于此，本发明实施例希望提供一种信息处理方法及终端、计算机存储介质，至少解决了现有技术存在的问题，提高了实时录制视频的视频画质。
本发明实施例的技术方案是这样实现的：
本发明实施例的一种信息处理方法，所述方法包括：
在终端开启应用，获取第一操作，触发第一媒体信息的采集；
终端在采集所述第一媒体信息的过程中，按照预设策略识别出第一区 域，所述第一区域为所述第一媒体信息的每一帧图像信息中的局部区域；
将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域；
对所述第一区域采用第一图像处理方式进行处理，得到第一图像处理结果；
对所述第二区域采用第二图像处理方式进行处理，得到第二图像处理结果；
将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。
本发明实施例的一种终端，所述终端包括：
触发单元，配置为在终端开启应用，获取第一操作，触发第一媒体信息的采集；
识别单元，配置为在采集所述第一媒体信息的过程中，按照预设策略识别出第一区域，所述第一区域为所述第一媒体信息的每一帧图像信息中的局部区域；
分离单元，配置为将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域；
第一处理单元，配置为对所述第一区域采用第一图像处理方式进行处理，得到第一图像处理结果；
第二处理单元，配置为对所述第二区域采用第二图像处理方式进行处理，得到第二图像处理结果；
融合单元，配置为将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。
所述触发单元、所述识别单元、所述分离单元、所述第一处理单元、所述第二处理单元、所述融合单元在执行处理时，可以采用中央处理器(CPU，Central Processing Unit)、数字信号处理器(DSP，Digital Singnal Processor)或可编程逻辑阵列(FPGA，Field－Programmable Gate Array)实现。
本发明实施例还提供一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，该计算机可执行指令配置为执行上述的信息处理方法。
本发明实施例的信息处理方法，所述方法包括：在终端开启应用，获取第一操作，触发第一媒体信息的采集；终端在采集所述第一媒体信息的过程中，按照预设策略识别出第一区域，所述第一区域为所述第一媒体信息的每一帧图像信息中的局部区域；将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域；对所述第一区域采用第一图像处理方式进行处理，得到第一图像处理结果；对所述第二区域采用第二图像处理方式进行处理，得到第二图像处理结果；将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。采用本发明实施例，针对整个画面中包含多种不同元素，不同元素所需的明暗度，色彩饱和度等等画质效果是不同的，基于此，对整个画面中的局部画面分别加滤镜进行不同的局部处理，从而提高了实时录制视频的视频画质。
附图说明
图1为本发明实施例中进行信息交互的各方硬件实体的示意图；
图2为本发明实施例一的一个实现流程示意图；
图3为应用本发明方法实施例的终端用户界面的一个示意图；
图4为本发明实施例二的一个实现流程示意图；
图5为应用本发明方法实施例进行局部区域划分的一个示意图；
图6为本发明实施例三的一个实现流程示意图；
图7为应用本发明方法实施例进行局部区域划分的又一个示意图；
图8为本发明实施例四的一个组成结构示意图；
图9为本发明实施例五的一个硬件组成结构示意图。
具体实施方式
下面结合附图对技术方案的实施作进一步的详细描述。
图1为本发明实施例中进行信息交互的各方硬件实体的示意图，图1中包括：服务器11、终端设备21-24，终端设备21-24通过有线网络或者无线网络与服务器进行信息交互，终端设备包括手机、台式机、PC机、一体机等类型。其中，终端设备中安装的所有应用或者指定的应用。采用本发明实施例，基于上述图1所示的系统，在终端开启应用(拍照应用或录制视频应用或图像处理应用等)，获取第一操作(如进入录制视频应用后开启摄像头对视频开始录制，或称为录制视频的采集操作)，触发第一媒体信息的采集(如录制一段视频)；终端在采集所述第一媒体信息(如视频)的过程中，按照预设策略识别出第一区域(可以是有别于其他区域的某个指定区域，该区域可以为人脸区域)，所述第一区域为所述第一媒体信息的每一帧图像信息中的局部区域；将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域(如果第一区域为人脸区域，则第二区域为非人脸区域，或称为人脸无关区域)；对所述第一区域采用第一图像处理方式(如皮，去斑，上腮红等滤镜技术)进行处理，得到第一图像处理结果；对所述第二区域采用第二图像处理方式(如调整明暗度或色彩饱和度等滤镜技术)进行处理，得到第二图像处理结果；将所述第一图像处理结果和所述第二图像处理结果进行融合处理， 重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。
上述图1的例子只是实现本发明实施例的一个系统架构实例，本发明实施例并不限于上述图1所述的系统结构，基于该系统架构，提出本发明各个实施例。
实施例一：
本发明实施例的一种信息处理方法，如图2所示，所述方法包括：
步骤101、在终端开启应用，获取第一操作，触发第一媒体信息的采集。
这里，用户正在使用终端(如手机11)，手机11的用户界面上包含各种类型的应用图标，如图3所示为包含各种类型的应用图标的一个终端用户界面，应用图标包括：如音乐播放图标，功能设置图标，邮件收发图标等等，用户执行第一操作，如用手指点击A1标识的视频处理应用图标，进入视频录制的处理过程，从而触发第一媒体信息(如视频)的采集。比如，可以录制一段室内的场景，或者，给自己进行自拍等等。
步骤102、终端在采集所述第一媒体信息的过程中，按照预设策略识别出第一区域，所述第一区域为所述第一媒体信息的每一帧图像信息中的局部区域。
这里，在视频录制的处理过程中，通过人脸识别定位机制，终端可以捕获到所述第一媒体信息的每一帧图像信息中整个画面中的局部人脸区域。具体的，在人脸识别的过程中，人脸识别技术是基于人的脸部特征，对视频录制中的人脸图像或者视频流进行采集，首先判断视频流中是否存在人脸，如果存在人脸，则进一步的给出脸的位置和大小，及定位出各个主要面部器官的位置信息，得到人脸中五官的各自位置。
步骤103、将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域。
这里，可以将识别出来的所述第一媒体信息的每一帧图像信息中整个画面中的局部人脸区域作为第一区域，那么，除局部人脸区域以外，在整个画面中剩下的区域即为第二区域。后续，由于第一区域和第二区域的特征有所不同，对二者进行处理的图像处理策略也不同，即需要分别采用不同的滤镜技术，如步骤104中，对所述第一区域采用第一图像处理方式(如磨皮，祛斑等滤镜技术)进行处理，如步骤105中，对所述第二区域采用第二图像处理方式(如调高亮度和色彩饱和度等滤镜技术)进行处理，这样，从针对整个画面中包含多种不同元素，不同元素所需的明暗度，色彩饱和度等等画质效果是不同的角度出发，基于此，对整个画面中的局部画面分别加滤镜进行不同的局部处理，而不是对整个画面采用单一的一套滤镜技术进行处理，从而提高了实时录制视频的视频画质。
步骤104、对所述第一区域采用第一图像处理方式进行处理，得到第一图像处理结果。
步骤105、对所述第二区域采用第二图像处理方式进行处理，得到第二图像处理结果。
步骤106、将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。
这里，一个具体实现过程可以为：对于实时录制的一段视频文件而言，先从所述视频中分别获取图像流和音频，通过安卓系统的摄像接口获取图像流，通过音频采集接口在视频录制时通过麦克风采样获取音频；对图像流的每一帧图像，区分出人脸区域和非人脸区域，并分别对人脸区域和非人脸区域采用两套针对性的不同滤镜技术分别进行局部的图像处理，生成两个滤镜特效图像流，再使用编码器接口实时将带有滤镜特效的两个滤镜特效图像流重新进行图像融合并编码为视频流，且将音频也重新编码为音 频流，使用音频视频合并器混合视频轨道和音频轨道，在音视频录制的同时实时生成经过不同滤镜技术实现局部图像处理后再将图像进行重新融合，得到最终经过修改后的实时录制的视频文件。
实施例二：
本发明实施例的一种信息处理方法，如图4所示，所述方法包括：
步骤201、在终端开启应用，获取第一操作，触发第一媒体信息的采集。
这里，用户正在使用终端(如手机11)，手机11的用户界面上包含各种类型的应用图标，如图3所示为包含各种类型的应用图标的一个终端用户界面，应用图标包括：如音乐播放图标，功能设置图标，邮件收发图标等等，用户执行第一操作，如用手指点击A1标识的视频处理应用图标，进入视频录制的处理过程，从而触发第一媒体信息(如视频)的采集。比如，可以录制一段室内的场景，或者，给自己进行自拍等等。
步骤202、获取人脸特征值，根据所述人脸特征值判断所述第一媒体信息的每一帧图像信息中是否包含人脸，得到判断结果。
这里，在视频录制的处理过程中，通过人脸识别定位机制，终端可以捕获到所述第一媒体信息的每一帧图像信息中整个画面中的局部人脸区域。具体的，在人脸识别的过程中，人脸识别技术是基于人的脸部特征，对视频录制中的人脸图像或者视频流进行采集，首先判断视频流中是否存在人脸，如果存在人脸，则进一步的给出脸的位置和大小，及定位出各个主要面部器官的位置信息，得到人脸中五官的各自位置。
步骤203、所述判断结果为包含人脸时，则定位出当前帧图像信息中人脸所在的位置，所述第一区域包含在人脸所在的位置对应的区域内。
这里，如图5所示为一个区域划分的示例图，图5中包括左侧的初始画面，当前帧图像信息的整个画面区域为A1，其中包括人脸区域和非人脸区域，如非人脸区域中包括一个小水杯A3，本步骤中，所述人脸所在的位 置对应的区域为A2，人脸区域是包含在A2中的。在后续实施例三中会进一步对该区域进行细化分离，从而精确的得到人脸区域。
步骤204、将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域。
这里，可以将识别出来的所述第一媒体信息的每一帧图像信息中整个画面中的局部人脸区域作为第一区域，那么，除局部人脸区域以外，在整个画面中剩下的区域即为第二区域。后续，由于第一区域和第二区域的特征有所不同，对二者进行处理的图像处理策略也不同，即需要分别采用不同的滤镜技术，如步骤205中，对所述第一区域采用第一图像处理方式(如磨皮，祛斑等滤镜技术)进行处理，如步骤206中，对所述第二区域采用第二图像处理方式(如调高亮度和色彩饱和度等滤镜技术)进行处理，这样，从针对整个画面中包含多种不同元素，不同元素所需的明暗度，色彩饱和度等等画质效果是不同的角度出发，基于此，对整个画面中的局部画面分别加滤镜进行不同的局部处理，而不是对整个画面采用单一的一套滤镜技术进行处理，从而提高了实时录制视频的视频画质。
步骤205、对所述第一区域采用第一图像处理方式进行处理，得到第一图像处理结果。
步骤206、对所述第二区域采用第二图像处理方式进行处理，得到第二图像处理结果。
步骤207、将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。
这里，一个具体实现过程可以为：对于实时录制的一段视频文件而言，先从所述视频中分别获取图像流和音频，通过安卓系统的摄像接口获取图像流，通过音频采集接口在视频录制时通过麦克风采样获取音频；对图像 流的每一帧图像，根据人脸特征值判断图像流的每一帧图像信息中是否包含人脸，以区分出人脸区域和非人脸区域，并分别对人脸区域和非人脸区域采用两套针对性的不同滤镜技术分别进行局部的图像处理，生成两个滤镜特效图像流，再使用编码器接口实时将带有滤镜特效的两个滤镜特效图像流重新进行图像融合并编码为视频流，且将音频也重新编码为音频流，使用音频视频合并器混合视频轨道和音频轨道，在音视频录制的同时实时生成经过不同滤镜技术实现局部图像处理后再将图像进行重新融合，得到最终经过修改后的实时录制的视频文件。
实施例三：
本发明实施例的一种信息处理方法，如图6所示，所述方法包括：
步骤301、在终端开启应用，获取第一操作，触发第一媒体信息的采集。
这里，用户正在使用终端(如手机11)，手机11的用户界面上包含各种类型的应用图标，如图3所示为包含各种类型的应用图标的一个终端用户界面，应用图标包括：如音乐播放图标，功能设置图标，邮件收发图标等等，用户执行第一操作，如用手指点击A1标识的视频处理应用图标，进入视频录制的处理过程，从而触发第一媒体信息(如视频)的采集。比如，可以录制一段室内的场景，或者，给自己进行自拍等等。
步骤302、获取人脸特征值，根据所述人脸特征值判断所述第一媒体信息的每一帧图像信息中是否包含人脸，得到判断结果。
这里，在视频录制的处理过程中，通过人脸识别定位机制，终端可以捕获到所述第一媒体信息的每一帧图像信息中整个画面中的局部人脸区域。具体的，在人脸识别的过程中，人脸识别技术是基于人的脸部特征，对视频录制中的人脸图像或者视频流进行采集，首先判断视频流中是否存在人脸，如果存在人脸，则进一步的给出脸的位置和大小，及定位出各个主要面部器官的位置信息，得到人脸中五官的各自位置。
步骤303、所述判断结果为包含人脸时，则定位出当前帧图像信息中人脸所在的位置，所述第一区域包含在人脸所在的位置对应的区域内。
步骤304、获取当前帧图像信息中人脸所在的位置，在所述人脸所在的位置按照人脸识别参数提取出人脸轮廓信息。
这里，人脸识别参数包括人脸大小，人脸面部器官的相对位置等。
这里，如图7所示为一个区域划分的示例图，图7中包括左侧的初始画面，当前帧图像信息的整个画面区域为A1，其中包括人脸区域和非人脸区域，如非人脸区域中包括一个小水杯A3，本步骤中，所述人脸所在的位置对应的区域为A2，人脸区域A4是包含在人脸所在的位置对应的区域A2中的，具体是根据人脸识别参数(如人脸大小，人脸面部器官的相对位置)等获知人脸轮廓信息，从而对人脸所在的位置对应的区域A2进行细化分离，根据人脸轮廓信息定位出实际的人脸区域A4，从而精确的得到人脸区域。
步骤305、根据所述人脸轮廓信息对当前帧图像信息进行分离，得到人脸区域和非人脸区域，将所述人脸区域确定为所述第一区域，将所述非人脸区域确定为所述第二区域。
这里，可以将识别出来的所述第一媒体信息的每一帧图像信息中整个画面中的局部人脸区域作为第一区域，那么，除局部人脸区域以外，在整个画面中剩下的区域即为第二区域。后续，由于第一区域和第二区域的特征有所不同，对二者进行处理的图像处理策略也不同，即需要分别采用不同的滤镜技术，如步骤306中，对所述第一区域采用第一图像处理方式(如磨皮，祛斑等滤镜技术)进行处理，如步骤307中，对所述第二区域采用第二图像处理方式(如调高亮度和色彩饱和度等滤镜技术)进行处理，这样，从针对整个画面中包含多种不同元素，不同元素所需的明暗度，色彩饱和度等等画质效果是不同的角度出发，基于此，对整个画面中的局部画 面分别加滤镜进行不同的局部处理，而不是对整个画面采用单一的一套滤镜技术进行处理，从而提高了实时录制视频的视频画质。
步骤306、对所述人脸区域采用第一图像处理方式进行处理，得到第一图像处理结果。
步骤307、对所述非人脸区域采用第二图像处理方式进行处理，得到第二图像处理结果。
步骤308、将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。
这里，一个具体实现过程可以为：对于实时录制的一段视频文件而言，先从所述视频中分别获取图像流和音频，通过安卓系统的摄像接口获取图像流，通过音频采集接口在视频录制时通过麦克风采样获取音频；对图像流的每一帧图像，根据人脸特征值判断图像流的每一帧图像信息中是否包含人脸，以区分出人脸区域和非人脸区域，并分别对人脸区域和非人脸区域采用两套针对性的不同滤镜技术分别进行局部的图像处理，生成两个滤镜特效图像流，再使用编码器接口实时将带有滤镜特效的两个滤镜特效图像流重新进行图像融合并编码为视频流，且将音频也重新编码为音频流，使用音频视频合并器混合视频轨道和音频轨道，在音视频录制的同时实时生成经过不同滤镜技术实现局部图像处理后再将图像进行重新融合，得到最终经过修改后的实时录制的视频文件。
基于上述实施例，在本发明实施例一实施方式中，所述方法还包括：所述触发第一媒体信息的采集之前，检测到用于第一媒体信息采集的采集模块已开启且尚未开始实际的采集操作时，识别出与所述第一媒体信息采集相关的当前场景信息并收集所述当前场景信息。
基于上述实施例，在本发明实施例一实施方式中，所述方法还包括： 终端在采集所述第一媒体信息的过程中，根据收集的所述当前场景信息进行分析，得到分析结果；根据所述分析结果自适应选择用于对所述第一媒体信息的每一帧图像信息进行图像处理的图像处理方式；所述图像处理方式包括：所述第一图像处理方式和/或第二图像处理方式。
这里，一个具体实现为：在进入视频录制应用，开启摄像头，但是只是在摄像头对应的取景框寻找需要拍摄的人物，外部环境或内部环境等等，在这个过程中由于还未开始正式的视频录制，因此，CPU是空闲的，此时，在摄像头开启但是并未正式开始录制视频的过程中，可以基于当前摄像头对应的取景框显示的场景实际情况为终端预估一个可选的滤镜，可以是仅针对人脸区域的滤镜，也可以是仅针对非人脸区域的滤镜，还可以是为人脸区域和非人脸区域都分别提供的一个滤镜(即2个滤镜，以便在前期就可以分别对人脸区域和非人脸区域进行预处理)。
这里，除了通过终端空闲时，处理负载小的时候，根据场景预估滤镜之外，还可以根据历史记录或者收集的用户使用习惯等等为终端预估滤镜，比如，用户是个女生，那么如果是自拍照，那么她的习惯很可能是对五官有化妆及美化的需求，那么，可以预先为终端推送美瞳滤镜，腮红滤镜等等。如果用户是连拍这种，可以记录用户上一次录制视频所采用的滤镜，当用户下一次继续录制视频时，预先为终端推送该上一次录制视频所采用的滤镜等等。
实施例四：
本发明实施例的一种终端，如图8所示，所述终端包括：
触发单元11，配置为在终端开启应用，获取第一操作，触发第一媒体信息的采集；识别单元12，配置为在采集所述第一媒体信息的过程中，按照预设策略识别出第一区域，所述第一区域为所述第一媒体信息的每一帧图像信息中的局部区域；分离单元13，配置为将所述第一区域从所述每一 帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域；第一处理单元14，配置为对所述第一区域采用第一图像处理方式进行处理，得到第一图像处理结果；第二处理单元15，配置为对所述第二区域采用第二图像处理方式进行处理，得到第二图像处理结果；及融合单元16，配置为将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。
本发明实施例的一个具体应用中，用户正在使用终端(如手机11)，手机11的用户界面上包含各种类型的应用图标，如图3所示为包含各种类型的应用图标的一个终端用户界面，应用图标包括：如音乐播放图标，功能设置图标，邮件收发图标等等，用户执行第一操作，如用手指点击A1标识的视频处理应用图标，进入视频录制的处理过程，从而触发第一媒体信息(如视频)的采集。比如，可以录制一段室内的场景，或者，给自己进行自拍等等。在视频录制的处理过程中，通过人脸识别定位机制，终端可以捕获到所述第一媒体信息的每一帧图像信息中整个画面中的局部人脸区域。具体的，在人脸识别的过程中，人脸识别技术是基于人的脸部特征，对视频录制中的人脸图像或者视频流进行采集，首先判断视频流中是否存在人脸，如果存在人脸，则进一步的给出脸的位置和大小，及定位出各个主要面部器官的位置信息，得到人脸中五官的各自位置。继续将识别出来的所述第一媒体信息的每一帧图像信息中整个画面中的局部人脸区域作为第一区域，那么，除局部人脸区域以外，在整个画面中剩下的区域即为第二区域。由于第一区域和第二区域的特征有所不同，对二者进行处理的图像处理策略也不同，即需要分别采用不同的滤镜技术，比如，对所述第一区域采用第一图像处理方式(如磨皮，祛斑等滤镜技术)进行处理，对所述第二区域采用第二图像处理方式(如调高亮度和色彩饱和度等滤镜技术) 进行处理，这样，从针对整个画面中包含多种不同元素，不同元素所需的明暗度，色彩饱和度等等画质效果是不同的角度出发，基于此，对整个画面中的局部画面分别加滤镜进行不同的局部处理，而不是对整个画面采用单一的一套滤镜技术进行处理，从而提高了实时录制视频的视频画质。
在本发明实施例一实施方式中，所述识别单元，进一步配置为：获取人脸特征值，根据所述人脸特征值判断所述第一媒体信息的每一帧图像信息中是否包含人脸，得到判断结果；
所述判断结果为包含人脸时，则定位出当前帧图像信息中人脸所在的位置，所述第一区域包含在人脸所在的位置对应的区域内。
在本发明实施例一实施方式中，所所述分离单元，进一步配置为：获取当前帧图像信息中人脸所在的位置，在所述人脸所在的位置按照人脸识别参数提取出人脸轮廓信息；根据所述人脸轮廓信息对当前帧图像信息进行分离，得到人脸区域和非人脸区域；将所述人脸区域确定为所述第一区域；将所述非人脸区域确定为所述第二区域。
在本发明实施例一实施方式中，所所述终端还包括：检测单元，配置为：所述触发第一媒体信息的采集之前，检测到用于第一媒体信息采集的采集模块已开启且尚未开始实际的采集操作时，识别出与所述第一媒体信息采集相关的当前场景信息并收集所述当前场景信息。
在本发明实施例一实施方式中，所所述终端还包括：选择单元，配置为：终端在采集所述第一媒体信息的过程中，根据收集的所述当前场景信息进行分析，得到分析结果；根据所述分析结果自适应选择用于对所述第一媒体信息的每一帧图像信息进行图像处理的图像处理方式；所述图像处理方式包括：所述第一图像处理方式和/或第二图像处理方式。
实施例五：
这里需要指出的是，上述终端可以为PC这种电子设备，还可以为如 PAD，平板电脑，手提电脑这种便携电子设备、还可以为如手机这种智能移动终端，不限于这里的描述；所述服务器可以是通过集群系统构成的，为实现各单元功能而合并为一或各单元功能分体设置的电子设备，终端和服务器都至少包括用于存储数据的数据库和用于数据处理的处理器，或者包括设置于服务器内的存储介质或独立设置的存储介质。
其中，对于用于数据处理的处理器而言，在执行处理时，可以采用微处理器、中央处理器(CPU，Central Processing Unit)、数字信号处理器(DSP，Digital Singnal Processor)或可编程逻辑阵列(FPGA，Field－Programmable Gate Array)实现；对于存储介质来说，包含操作指令，该操作指令可以为计算机可执行代码，通过所述操作指令来实现上述本发明实施例信息处理方法流程中的各个步骤。
该终端和该服务器作为硬件实体S11的一个示例如图9所示。所述装置包括处理器31、存储介质32以及至少一个外部通信接口33；所述处理器31、存储介质32以及外部通信接口33均通过总线34连接。
这里需要指出的是：以上涉及终端和服务器项的描述，与上述方法描述是类似的，同方法的有益效果描述，不做赘述。对于本发明终端和服务器实施例中未披露的技术细节，请参照本发明方法实施例的描述。
以一个现实应用场景为例对本发明实施例阐述如下：
在各种视频类应用的使用过程中，一种应用场景为：在视频录制的过程中增加了多种滤镜，可以优化拍摄的图像画质，比如通过实时视频录制的一种滤镜可以实现磨皮美肤的图像画质。由于整个视频录制的每一帧图像中存在不同的构图元素，采用现有单一的一套滤镜技术反而会导致整体画质下降，比如对整个画面加滤镜，滤镜单一，加入滤镜之后会引起整个画面质量的下降。举例来说，某个构图元素(如整个图像中的局部风景部分)是因光线不足的情况下视频录制质量差的问题，某个构图元素(如整 个图像中的局部人物部分)是因人物皮肤不够好而引起的视频质量差的问题。另外，一次滤镜处理后，如果整个图像画质不如意，通常会启用多次的滤镜进行多次处理，处理效率低下，且添加过多滤镜造成硬件开销过大的问题。
本应用场景采用本发明实施例包括：1)在用户摄像头开启而还未开始录制的这段时间内就开始收集当前场景信息。通过算法识别出当前场景；2)视频录制开始，根据前面识别出的场景信息，选定滤镜风格，分别对昏暗、明亮、正常进行优化。比如：昏暗风格提高画面亮度，去噪点；3)视频录制过程中，跟踪人脸位置，对人脸区域有针对性的做磨皮；4)视频录制过程中，实时识别人脸五官，对五官进行针对性美妆优化，比如：增加腮红。还可以做特殊妆容/滤镜，增加趣味性，打造有趣好玩儿的视频。可见，本应用场景采用本发明实施例，一种具体实现是根据场景和人脸位置精准美化的滤镜和磨皮算法，进行局部处理，可以在提高用户人脸皮肤质量的同时保留其他位置图像细节，同时能根据不同场景选择最合适的滤镜，滤镜多样化，大大提高了视频录制最终呈现的图像画质。
对应的处理流程包括如下步骤：
步骤501、取得实时录制的视频流中的每一个图像帧后，通过人脸检测功能在图像帧中监测到人脸的位置，并提取出人脸轮廓。
步骤502、根据人脸轮廓，对图像帧进行分离，分为人脸和非人脸两个部分。
步骤503、对非人脸部分做亮度调整、去除燥点等滤镜渲染。
步骤504、对人脸部分做美容，磨皮等滤镜渲染。
步骤505、将处理过的人脸部分和非人脸部分重新混合成完整的图像帧。
综上所述，上述处理流程包括：图像帧获取的过程(得到整个画面)； 人脸检测的过程(识别出整个画面中的部分区域，如人脸区域)；图像分离的过程(如将人脸区域从整个画面中分离出来，即：得到人脸区域和非人脸区域)；渲染滤镜的过程(如开启滤镜的渲染功能)；对人脸区域使用滤镜的过程(如磨皮和祛斑等等)；图像融合的过程(如人脸区域处理完后，与人脸无关区域进行重新图像融合，得到处理后的图像)等部分组成。由于在整个流程实现中，对图像的各个部分，均只使用了一次滤镜，因此，采用上述流程提高了处理速度，减少了计算的开销。
本发明实施例还提供一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，该计算机可执行指令配置为执行上述的信息处理方法。
在本申请所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，如：多个单元或组件可以结合，或可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的各组成部分相互之间的耦合、或直接耦合、或通信连接可以是通过一些接口，设备或单元的间接耦合或通信连接，可以是电性的、机械的或其它形式的。
上述作为分离部件说明的单元可以是、或也可以不是物理上分开的，作为单元显示的部件可以是、或也可以不是物理单元，即可以位于一个地方，也可以分布到多个网络单元上；可以根据实际的需要选择其中的部分或全部单元来实现本实施例方案的目的。
另外，在本发明各实施例中的各功能单元可以全部集成在一个处理单元中，也可以是各单元分别单独作为一个单元，也可以两个或两个以上单元集成在一个单元中；上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于一计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：移动存储设备、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
或者，本发明上述集成的单元如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明实施例的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机、服务器、或者网络设备等)执行本发明各个实施例所述方法的全部或部分。而前述的存储介质包括：移动存储设备、ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以所述权利要求的保护范围为准。
工业实用性
本发明实施例的信息处理方法，所述方法包括：在终端开启应用，获取第一操作，触发第一媒体信息的采集；终端在采集所述第一媒体信息的过程中，按照预设策略识别出第一区域，所述第一区域为所述第一媒体信息的每一帧图像信息中的局部区域；将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域；对所述第一区域采用第一图像处理方式进行处理，得到第一图像处理结果； 对所述第二区域采用第二图像处理方式进行处理，得到第二图像处理结果；将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。采用本发明实施例，针对整个画面中包含多种不同元素，不同元素所需的明暗度，色彩饱和度等等画质效果是不同的，基于此，对整个画面中的局部画面分别加滤镜进行不同的局部处理，从而提高了实时录制视频的视频画质。

Claims (11)

  1. 一种信息处理方法，所述方法包括：
    在终端开启应用，获取第一操作，触发第一媒体信息的采集；
    终端在采集所述第一媒体信息的过程中，按照预设策略识别出第一区域，所述第一区域为所述第一媒体信息的每一帧图像信息中的局部区域；
    将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域；
    对所述第一区域采用第一图像处理方式进行处理，得到第一图像处理结果；
    对所述第二区域采用第二图像处理方式进行处理，得到第二图像处理结果；
    将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。
  2. 根据权利要求1所述的方法，其中，所述终端在采集所述第一媒体信息的过程中，按照预设策略识别出第一区域，包括：
    获取人脸特征值，根据所述人脸特征值判断所述第一媒体信息的每一帧图像信息中是否包含人脸，得到判断结果；
    所述判断结果为包含人脸时，则定位出当前帧图像信息中人脸所在的位置，所述第一区域包含在人脸所在的位置对应的区域内。
  3. 根据权利要求2所述的方法，其中，将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域，包括：
    获取当前帧图像信息中人脸所在的位置，在所述人脸所在的位置按照人脸识别参数提取出人脸轮廓信息；
    根据所述人脸轮廓信息对当前帧图像信息进行分离，得到人脸区域和非人脸区域；
    将所述人脸区域确定为所述第一区域；
    将所述非人脸区域确定为所述第二区域。
  4. 根据权利要求1至3任一项所述的方法，其中，所述方法还包括：
    所述触发第一媒体信息的采集之前，检测到用于第一媒体信息采集的采集模块已开启且尚未开始实际的采集操作时，识别出与所述第一媒体信息采集相关的当前场景信息并收集所述当前场景信息。
  5. 根据权利要求4所述的方法，其中，所述方法还包括：
    终端在采集所述第一媒体信息的过程中，根据收集的所述当前场景信息进行分析，得到分析结果；
    根据所述分析结果自适应选择用于对所述第一媒体信息的每一帧图像信息进行图像处理的图像处理方式；
    所述图像处理方式包括：所述第一图像处理方式和/或第二图像处理方式。
  6. 一种终端，所述终端包括：
    触发单元，配置为在终端开启应用，获取第一操作，触发第一媒体信息的采集；
    识别单元，配置为在采集所述第一媒体信息的过程中，按照预设策略识别出第一区域，所述第一区域为所述第一媒体信息的每一帧图像信息中的局部区域；
    分离单元，配置为将所述第一区域从所述每一帧图像信息中分离出来，将分离后所述每一帧图像信息剩下的区域记为第二区域；
    第一处理单元，配置为对所述第一区域采用第一图像处理方式进行处理，得到第一图像处理结果；
    第二处理单元，配置为对所述第二区域采用第二图像处理方式进行处理，得到第二图像处理结果；
    融合单元，配置为将所述第一图像处理结果和所述第二图像处理结果进行融合处理，重新得到完整的图像融合信息，并将所述完整的图像融合信息重新作为每一帧的图像信息。
  7. 根据权利要求6所述的终端，其中，所述识别单元，进一步配置为：
    获取人脸特征值，根据所述人脸特征值判断所述第一媒体信息的每一帧图像信息中是否包含人脸，得到判断结果；
    所述判断结果为包含人脸时，则定位出当前帧图像信息中人脸所在的位置，所述第一区域包含在人脸所在的位置对应的区域内。
  8. 根据权利要求7所述的终端，其中，所述分离单元，进一步配置为：
    获取当前帧图像信息中人脸所在的位置，在所述人脸所在的位置按照人脸识别参数提取出人脸轮廓信息；
    根据所述人脸轮廓信息对当前帧图像信息进行分离，得到人脸区域和非人脸区域；
    将所述人脸区域确定为所述第一区域；
    将所述非人脸区域确定为所述第二区域。
  9. 根据权利要求6至8任一项所述的终端，其中，所述终端还包括：检测单元，配置为：
    所述触发第一媒体信息的采集之前，检测到用于第一媒体信息采集的采集模块已开启且尚未开始实际的采集操作时，识别出与所述第一媒体信息采集相关的当前场景信息并收集所述当前场景信息。
  10. 根据权利要求9所述的终端，其中，所述终端还包括：选择单元，配置为：
    终端在采集所述第一媒体信息的过程中，根据收集的所述当前场景信 息进行分析，得到分析结果；
    根据所述分析结果自适应选择用于对所述第一媒体信息的每一帧图像信息进行图像处理的图像处理方式；
    所述图像处理方式包括：所述第一图像处理方式和/或第二图像处理方式。
  11. 一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，该计算机可执行指令配置为执行权利要求1所述的信息处理方法。
PCT/CN2017/074455 2016-04-13 2017-02-22 一种信息处理方法及终端、计算机存储介质 WO2017177768A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201610232008.X 2016-04-13
CN201610232008.XA CN105847728A (zh) 2016-04-13 2016-04-13 一种信息处理方法及终端

Publications (1)

Publication Number Publication Date
WO2017177768A1 true WO2017177768A1 (zh) 2017-10-19

Family

ID=56597535

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2017/074455 WO2017177768A1 (zh) 2016-04-13 2017-02-22 一种信息处理方法及终端、计算机存储介质

Country Status (2)

Country Link
CN (1) CN105847728A (zh)
WO (1) WO2017177768A1 (zh)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110896465A (zh) * 2018-09-12 2020-03-20 北京嘉楠捷思信息技术有限公司 一种图像处理方法、装置及计算机可读存储介质
CN110933354A (zh) * 2019-11-18 2020-03-27 深圳传音控股股份有限公司 一种可定制的多风格多媒体处理方法及其终端
CN111079520A (zh) * 2019-11-01 2020-04-28 京东数字科技控股有限公司 图像识别方法、设备及存储介质
CN114302190A (zh) * 2021-01-14 2022-04-08 海信视像科技股份有限公司 一种显示设备及画质调整方法

Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105847728A (zh) * 2016-04-13 2016-08-10 腾讯科技（深圳）有限公司 一种信息处理方法及终端
CN106331482A (zh) * 2016-08-23 2017-01-11 努比亚技术有限公司 一种照片处理装置和方法
CN106604147A (zh) * 2016-12-08 2017-04-26 天脉聚源(北京)传媒科技有限公司 一种视频处理方法及装置
CN106971165B (zh) * 2017-03-29 2018-08-10 武汉斗鱼网络科技有限公司 一种滤镜的实现方法及装置
CN107071333A (zh) * 2017-05-19 2017-08-18 深圳天珑无线科技有限公司 视频图像处理方法和视频图像处理装置
CN107316281B (zh) * 2017-06-16 2021-03-02 Oppo广东移动通信有限公司 图像处理方法、装置和终端设备
CN107563962A (zh) * 2017-09-08 2018-01-09 北京奇虎科技有限公司 视频数据实时处理方法及装置、计算设备
CN107820027A (zh) * 2017-11-02 2018-03-20 北京奇虎科技有限公司 视频人物装扮方法、装置、计算设备及计算机存储介质
CN107945188A (zh) * 2017-11-20 2018-04-20 北京奇虎科技有限公司 基于场景分割的人物装扮方法及装置、计算设备
CN108010037B (zh) * 2017-11-29 2019-09-13 腾讯科技（深圳）有限公司 图像处理方法、装置及存储介质
CN108124101A (zh) * 2017-12-18 2018-06-05 北京奇虎科技有限公司 视频采集方法、装置、电子设备和计算机可读存储介质
CN108171716B (zh) * 2017-12-25 2021-11-26 北京奇虎科技有限公司 基于自适应跟踪框分割的视频人物装扮方法及装置
CN108171719B (zh) * 2017-12-25 2021-07-23 北京奇虎科技有限公司 基于自适应跟踪框分割的视频穿越处理方法及装置
CN108683826B (zh) * 2018-05-15 2021-12-14 腾讯科技（深圳）有限公司 视频数据处理方法、装置、计算机设备和存储介质
CN109242802B (zh) * 2018-09-28 2021-06-15 Oppo广东移动通信有限公司 图像处理方法、装置、电子设备及计算机可读介质
CN111200705B (zh) * 2018-11-16 2021-05-25 北京微播视界科技有限公司 图像处理方法和装置
CN109640151A (zh) * 2018-11-27 2019-04-16 Oppo广东移动通信有限公司 视频处理方法、装置、电子设备以及存储介质
CN112132085A (zh) * 2020-09-29 2020-12-25 联想(北京)有限公司 一种图像处理方法、电子设备
CN112991208B (zh) * 2021-03-11 2024-05-07 Oppo广东移动通信有限公司 图像处理方法及装置、计算机可读介质和电子设备
CN113132800B (zh) * 2021-04-14 2022-09-02 Oppo广东移动通信有限公司 视频处理方法、装置、视频播放器、电子设备及可读介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101510957A (zh) * 2008-02-15 2009-08-19 索尼株式会社 图像处理设备、方法、程序、摄像机设备、通信系统
CN103179341A (zh) * 2011-12-21 2013-06-26 索尼公司 图像处理装置、图像处理方法和程序
CN103544718A (zh) * 2012-07-13 2014-01-29 卡西欧计算机株式会社 图像处理装置以及画面风格变换方法
CN104902189A (zh) * 2015-06-24 2015-09-09 小米科技有限责任公司 图片处理方法及装置
CN105847728A (zh) * 2016-04-13 2016-08-10 腾讯科技（深圳）有限公司 一种信息处理方法及终端

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4189467B2 (ja) * 2004-05-27 2008-12-03 コニカミノルタビジネステクノロジーズ株式会社 画像処理装置
CN1808497A (zh) * 2005-01-21 2006-07-26 建兴电子科技股份有限公司 影像处理单元及其影像处理方法
JP2011118842A (ja) * 2009-12-07 2011-06-16 Canon Inc 情報処理装置、表示制御方法及びプログラム
IN2014DN10919A (zh) * 2012-05-22 2015-09-18 Nikon Corp
CN104952036B (zh) * 2015-06-18 2018-11-06 福州瑞芯微电子股份有限公司 一种即时视频中的人脸美化方法和电子设备

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101510957A (zh) * 2008-02-15 2009-08-19 索尼株式会社 图像处理设备、方法、程序、摄像机设备、通信系统
CN103179341A (zh) * 2011-12-21 2013-06-26 索尼公司 图像处理装置、图像处理方法和程序
CN103544718A (zh) * 2012-07-13 2014-01-29 卡西欧计算机株式会社 图像处理装置以及画面风格变换方法
CN104902189A (zh) * 2015-06-24 2015-09-09 小米科技有限责任公司 图片处理方法及装置
CN105847728A (zh) * 2016-04-13 2016-08-10 腾讯科技（深圳）有限公司 一种信息处理方法及终端

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110896465A (zh) * 2018-09-12 2020-03-20 北京嘉楠捷思信息技术有限公司 一种图像处理方法、装置及计算机可读存储介质
CN111079520A (zh) * 2019-11-01 2020-04-28 京东数字科技控股有限公司 图像识别方法、设备及存储介质
CN111079520B (zh) * 2019-11-01 2024-05-21 京东科技控股股份有限公司 图像识别方法、设备及存储介质
CN110933354A (zh) * 2019-11-18 2020-03-27 深圳传音控股股份有限公司 一种可定制的多风格多媒体处理方法及其终端
CN110933354B (zh) * 2019-11-18 2023-09-01 深圳传音控股股份有限公司 一种可定制的多风格多媒体处理方法及其终端
CN114302190A (zh) * 2021-01-14 2022-04-08 海信视像科技股份有限公司 一种显示设备及画质调整方法

Also Published As

Publication number Publication date
CN105847728A (zh) 2016-08-10

Similar Documents

Publication Publication Date Title
WO2017177768A1 (zh) 一种信息处理方法及终端、计算机存储介质
CN105791692B (zh) 一种信息处理方法、终端及存储介质
CN109976506B (zh) 一种电子设备的唤醒方法、存储介质及机器人
TWI751161B (zh) 終端設備、智慧型手機、基於臉部識別的認證方法和系統
US9323979B2 (en) Face recognition performance using additional image features
US10170157B2 (en) Method and apparatus for finding and using video portions that are relevant to adjacent still images
CN108280418A (zh) 脸部图像的欺骗识别方法及装置
KR102045575B1 (ko) 스마트 미러 디스플레이 장치
WO2022116604A1 (zh) 拍摄图像处理方法及电子设备
TW201607314A (zh) 自動生成視訊以適合顯示時間
EP3555799B1 (en) A method for selecting frames used in face processing
JP6413018B2 (ja) ビデオキャプチャの処理方法、システム及び装置
TW201602922A (zh) 自動插入視頻成爲相片故事
US20160034785A1 (en) Generating compositions
CN106815803B (zh) 图片的处理方法及装置
WO2015078240A1 (zh) 一种视频控制方法及用户终端
KR100886489B1 (ko) 영상 통화 시 얼굴의 표정에 따라 꾸미기 효과를 합성하는방법 및 시스템
WO2015179459A1 (en) Editing based on thumbnail images
KR20160105872A (ko) 비디오 회의 강화
WO2020052062A1 (zh) 检测方法和装置
CN113129893B (zh) 一种语音识别方法、装置、设备及存储介质
CN113709545A (zh) 视频的处理方法、装置、计算机设备和存储介质
JP6373446B2 (ja) ビデオフレームを選択するプログラム、システム、装置、及び方法
WO2021190625A1 (zh) 拍摄方法和设备
JP2002199202A (ja) 画像処理装置

Legal Events

Date Code Title Description
NENP Non-entry into the national phase

Ref country code: DE

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17781744

Country of ref document: EP

Kind code of ref document: A1

122 Ep: pct application non-entry in european phase

Ref document number: 17781744

Country of ref document: EP

Kind code of ref document: A1