CN110971891A - Video quality evaluation method and device and electronic equipment - Google Patents
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Abstract
The invention relates to the technical field of video quality assessment, in particular to a video quality assessment method and device and electronic equipment. The video quality evaluation method comprises the following steps: acquiring video resources shot by a vehicle event data recorder; quantifying the quality evaluation factor of the video resource to obtain quality evaluation data of the video resource; and evaluating the quality of the video resources according to the quality evaluation data to obtain a quality evaluation result aiming at the video resources. The quality evaluation data is a quantization result obtained by quantizing the quality evaluation factor of the video resource shot by the automobile data recorder, and the quality of the video resource is evaluated according to the quality evaluation data, so that the quality of the video resource can be accurately evaluated, the interference of human factors on the evaluation result of the video resource is avoided, and the more accurate and reliable quality evaluation of the video shot by the automobile data recorder is realized.
Description
Technical Field
The invention relates to the technical field of automobile data recorder video quality evaluation, in particular to a video quality evaluation method and device and electronic equipment.
Background
The automobile data recorder is used for recording relevant information such as images and sounds during the running of a vehicle. After the automobile data recorder is installed, the video and the audio of the whole automobile driving process can be recorded and stored as video resources and audio resources so as to provide evidence for traffic accidents. Therefore, the quality of the video resource shot by the automobile data recorder becomes one of the necessary factors for judging whether the video resource meets the factory standard or not.
At present, in the production design process of the automobile data recorder, the quality of the video resource shot by the automobile data recorder is evaluated by direct visual sensing of an engineer, and the situation of misjudgment often occurs by direct visual sensing. Therefore, how to accurately and reliably evaluate the quality of the video resource shot by the automobile data recorder becomes a technical problem to be solved urgently in the technical field of automobile data recorder video quality evaluation.
Disclosure of Invention
In view of the above, embodiments of the present invention provide a method, an apparatus and an electronic device for video quality assessment to effectively solve the above problems.
In a first aspect, a method for evaluating video quality provided in an embodiment of the present invention includes:
acquiring video resources shot by a vehicle event data recorder;
quantifying the quality evaluation factor of the video resource to obtain quality evaluation data of the video resource;
and evaluating the quality of the video resources according to the quality evaluation data to obtain a quality evaluation result aiming at the video resources.
Further, the obtaining quality assessment data of the video resource includes:
one or more quality assessment data of the sharpness assessment data, the fluency assessment data, and the brightness assessment data are obtained.
Further, the sharpness evaluation data includes a resolution evaluation value, and the quantizing the quality evaluation factor of the video resource to obtain the quality evaluation data of the video resource includes:
selecting at least one frame of image from a plurality of frames of images included in the video resource as a first sampling image;
and carrying out quantitative analysis on the resolution of the first sampling image to obtain a resolution evaluation value aiming at the video resource.
Further, the sharpness evaluation data includes a sharpness evaluation value, and the quantizing the quality evaluation factor of the video resource to obtain the quality evaluation data of the video resource includes:
selecting at least one frame of image from a plurality of frames of images included in the video resource as a second sampling image;
and carrying out quantitative analysis on the sharpening degree of the second sampling image to obtain a sharpening degree evaluation value aiming at the video resource.
Further, the fluency evaluation data includes a frame rate evaluation value, and the quantifying the quality evaluation factor of the video resource to obtain the quality evaluation data of the video resource includes:
selecting at least one sub-video segment from a plurality of sub-video segments included in the video resource as a sampling sub-video segment;
and carrying out quantitative analysis on the frame rate of the sampling sub-video segment to obtain a frame rate evaluation value of the video resource.
Further, the brightness evaluation data includes a color evaluation value, and the quantizing the quality evaluation factor of the video resource to obtain the quality evaluation data of the video resource includes:
selecting at least one frame of image from a plurality of frames of images included in the video resource as a third sampling image;
selecting at least one pixel point from a plurality of pixel points included in the third sampling image as a sampling pixel point;
and carrying out quantitative analysis on the color value of the sampling pixel point to obtain a color evaluation value of the video resource.
Further, the quality assessment data includes one or more quantitative assessment values for the video resources.
Further, the quality evaluation data includes a plurality of quantitative evaluation values corresponding to image frame orders, and the quality of the video resource is quantitatively evaluated according to the quality evaluation data to obtain a quantitative evaluation result for the video resource, including:
establishing a video quality evaluation chart or a video quality evaluation curve for the video resource based on the plurality of quantitative evaluation values corresponding to the image frame ordering;
and evaluating the quality of the video resources according to the video quality evaluation chart or the video quality evaluation curve to obtain a quality evaluation result aiming at the video resources.
In a second aspect, an embodiment of the present invention further provides a video quality assessment apparatus, including:
the video resource acquisition module is used for acquiring video resources shot by the automobile data recorder;
the quality evaluation data acquisition module is used for quantizing the quality evaluation factors of the video resources to acquire quality evaluation data of the video resources;
and the quality evaluation result acquisition module is used for evaluating the quality of the video resources according to the quality evaluation data to acquire a quality evaluation result aiming at the video resources.
Further, the quality assessment data includes one or more of sharpness assessment data, fluency assessment data, and shading assessment data.
Further, the sharpness evaluation data includes a resolution evaluation value, and the quality evaluation data acquisition module includes:
the first sampling image acquisition unit is used for selecting at least one frame of image from a plurality of frames of images included in the video resource as a first sampling image;
and the resolution evaluation value acquisition unit is used for carrying out quantitative analysis on the resolution of the first sampling image to obtain a resolution evaluation value aiming at the video resource.
Further, the sharpness evaluation data includes a degree of sharpening evaluation value, and the quality evaluation data acquisition module includes:
the second sampling image acquisition unit is used for selecting at least one frame of image from a plurality of frames of images included in the video resource as a second sampling image;
and the sharpening degree evaluation value acquisition unit is used for carrying out quantitative analysis on the sharpening degree of the second sampling image to obtain a sharpening degree evaluation value aiming at the video resource.
Further, the fluency assessment data comprises a frame rate assessment value, and the quality assessment data acquisition module comprises:
a sampling sub-video segment obtaining unit, configured to select at least one sub-video segment from multiple sub-video segments included in the video resource as a sampling sub-video segment;
and the frame rate evaluation value acquisition unit is used for carrying out quantitative analysis on the frame rate of the sampling sub-video segment to acquire the frame rate evaluation value of the video resource.
Further, the brightness evaluation data includes a color evaluation value, and the quality evaluation data acquisition module includes:
the third sampling image acquisition unit is used for selecting at least one frame of image from a plurality of frames of images included in the video resource as a third sampling image;
a sampling pixel point obtaining unit, configured to select at least one pixel point from a plurality of pixel points included in the third sampling image, as a sampling pixel point;
and the color evaluation value acquisition unit is used for carrying out quantitative analysis on the color values of the sampling pixel points to acquire the color evaluation value of the video resource.
Further, the quality assessment data includes one or more quantitative assessment values for the video resources.
Further, the quality estimation data includes a plurality of quantization estimation values corresponding to an order of image frames, and the quality estimation result acquisition module includes:
a quality evaluation tool establishing unit for establishing a video quality evaluation chart or a video quality evaluation curve for the video resource based on the plurality of quantitative evaluation values corresponding to the image frame ordering;
and the quality evaluation result acquisition unit is used for evaluating the quality of the video resources according to the video quality evaluation chart or the video quality evaluation curve to acquire a quality evaluation result aiming at the video resources.
In a third aspect, an embodiment of the present invention further provides an electronic device, which includes a processor, a memory, and the above video quality assessment apparatus, where the video quality assessment apparatus includes one or more software functional modules stored in the memory and executed by the processor.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed, can implement the video quality assessment method described above.
The video quality assessment method, the video quality assessment device and the electronic equipment provided by the embodiment of the invention can acquire video resources shot by a driving recorder, quantize quality assessment factors of the video resources, acquire quality assessment data of the video resources, and assess the quality of the video resources according to the quality assessment data to acquire quality assessment results aiming at the video resources. The quality evaluation data is a quantization result obtained by quantizing the quality evaluation factor of the video resource shot by the automobile data recorder, and then the quality of the video resource is evaluated according to the quality evaluation data, so that the quality of the video resource can be accurately evaluated, the interference of human factors on the evaluation result of the video resource is avoided, and the more accurate and reliable quality evaluation of the video shot by the automobile data recorder is realized.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present disclosure and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic structural block diagram of an electronic device according to an embodiment of the present invention.
Fig. 2 is a schematic flowchart of a video quality evaluation method according to an embodiment of the present invention.
Fig. 3 is a schematic block diagram of a video quality evaluation apparatus according to an embodiment of the present invention.
Icon: 100-an electronic device; 110-video quality assessment means; 111-video resource acquisition module; 112-quality assessment data acquisition module; 113-quality assessment result acquisition module; 120-a processor; 130-memory.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present disclosure, presented in the figures, is not intended to limit the scope of the claimed disclosure, but is merely representative of selected embodiments of the disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the disclosure without making creative efforts, shall fall within the protection scope of the disclosure.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Referring to fig. 1, a schematic block diagram of an electronic device 100 applying a video quality evaluation method and apparatus according to an embodiment of the present invention is shown. The electronic device 100 may be, but is not limited to, a mobile phone, a tablet computer, a PDA (Personal Digital Assistant), or a car recorder itself. Further, in the embodiment of the present invention, the electronic device 100 includes a video quality evaluation apparatus 110, a processor 120, and a memory 130.
The processor 120 and the memory 130 are electrically connected directly or indirectly to enable data transmission or interaction, for example, the components may be electrically connected to each other via one or more communication buses or signal lines. The video quality evaluation device 110 includes at least one software module which can be stored in the memory 130 in the form of software or Firmware (Firmware) or solidified in an Operating System (OS) of the electronic device 100. The processor 120 is used for executing executable modules stored in the memory 130, such as software functional modules and computer programs included in the video quality assessment apparatus 110. The processor 120 may execute the computer program upon receiving the execution instruction.
The processor 120 may be an integrated circuit chip having signal processing capabilities. The processor 120 may also be a general-purpose processor, e.g., a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), discrete gate or transistor logic, discrete hardware components, that may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. Further, a general purpose processor may be a microprocessor or any conventional processor or the like.
The Memory 130 may be, but is not limited to, a Random Access Memory (RAM), 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), and the like. The memory 130 is used for storing a program, and the processor 120 executes the program after receiving the execution instruction.
It should be understood that the configuration shown in fig. 1 is merely illustrative, and that the electronic device 100 provided by the embodiment of the invention may have fewer or more components than those shown in fig. 1, or may have a different configuration than that shown in fig. 1. Further, the components shown in fig. 1 may be implemented by software, hardware, or a combination thereof.
Referring to fig. 2, fig. 2 is a flowchart illustrating a video quality assessment method according to an embodiment of the present invention, where the video quality assessment method is applied to the electronic device shown in fig. 1. The detailed flow and steps of the video quality evaluation method are described in detail below with reference to fig. 2. It should be noted that the method provided by the embodiment of the present invention is not limited by the sequence shown in fig. 2 and the following, and the specific flow and steps of the video quality evaluation method are described in detail below with reference to fig. 2.
And S100, acquiring video resources shot by the automobile data recorder.
In the embodiment of the invention, the video resources can be acquired in various ways. For example, the communication connection may be obtained through a communication connection established between the electronic device and the automobile data recorder, where the communication connection may be a wired communication connection established through a data transmission line, or a wireless communication connection established through a bluetooth communication technology, an NFC communication technology, or the like. For another example, when the driving recorder plays the collected video, the video can be directly captured and acquired by other devices with the shooting function. For example, the video resource shot by the automobile data recorder is obtained through a Bluetooth communication technology, after a video resource obtaining request is received, a Bluetooth starting instruction is generated according to the video resource obtaining request and sent to a Bluetooth module of the electronic equipment so as to control Bluetooth starting of the electronic equipment, wireless communication connection is established with the automobile data recorder, and data transmission is carried out.
Step S200, quantizing the quality evaluation factors of the video resources to obtain quality evaluation data of the video resources.
Specifically, the video quality of the video resource may be evaluated from one or more dimensions, such as sharpness, fluency, shading, and the like, that is, in the embodiment of the present invention, the quality evaluation factor may include one or more quality evaluation factors of sharpness, fluency, and shading. Correspondingly, the various quality assessment factors of the video resources are quantized, that is: and carrying out quantitative analysis on the video resource to obtain one or more quality evaluation data of definition evaluation data, fluency evaluation data and brightness evaluation data of the video resource. Wherein each of the quality assessment data comprises at least one quantitative assessment value, and each of the quantitative assessment values may comprise one or more specific numerical values.
In this embodiment of the present invention, the sharpness evaluation data may include at least one quantization evaluation value of a resolution evaluation value and a sharpening degree evaluation value, that is, the sharpness of the video resource may be evaluated from at least one dimension of the resolution and the sharpening degree.
Based on the above description, for the definition of the video resource, obtaining definition evaluation data of the video resource includes: and obtaining one or two of a resolution evaluation value and a sharpening degree evaluation value of the video resource.
In the embodiment of the present invention, the resolution evaluation value of the video resource may be obtained through the following steps.
Selecting at least one frame of image from a plurality of frames of images included in the video resource as a first sampling image, and carrying out quantitative analysis on the resolution of the first sampling image to obtain a resolution evaluation value aiming at the video resource.
In the embodiment of the present invention, in order to ensure reliability of the obtained resolution evaluation value, at least two frames of images may be selected from the multiple frames of images included in the video resource as the first sampling image. In practical implementation, the image frames of the video resource may be sorted, and at least two frames of images are selected from the multi-frame images included in the video resource at intervals of a first preset number of frames, as a first sampling image, where the first preset number of frames may be 100 frames or 200 frames, which is not limited in this embodiment of the present invention. After at least two frames of images are selected as the first sampling images, the resolution of the selected at least two frames of first sampling images can be respectively subjected to quantitative analysis, at least two reference resolution values corresponding to the selected at least two frames of first sampling images are obtained, and the minimum reference resolution value is selected from the at least two reference resolution values to serve as the resolution evaluation value for the video resource.
In the embodiment of the present invention, the sharpening degree evaluation value of the video resource may be obtained through the following steps.
Selecting at least one frame of image from the multiple frames of images included in the video resource as a second sampling image, and carrying out quantitative analysis on the sharpening degree of the second sampling image to obtain a sharpening degree evaluation value aiming at the video resource.
Also, in the embodiment of the present invention, to ensure reliability of the obtained sharpness degree evaluation value, at least two frames of images may be selected from the multiple frames of images included in the video resource as the second sample image. In practical implementation, the image frames of the video resource may be sorted, and at least two frames of images may be selected from the multi-frame images included in the video resource at intervals of a second preset number of frames, as a second sampling image, where the second preset number of frames may be 100 frames or 200 frames, which is not limited in this embodiment of the present invention. After the at least two frames of images are selected as the second sampling images, the sharpening degrees of the selected at least two frames of second sampling images can be respectively subjected to quantitative analysis, at least two reference sharpening degree values corresponding to the selected at least two frames of second sampling images are obtained, and the minimum reference sharpening degree value is selected from the at least two reference sharpening degree values and is used as the sharpening degree evaluation value for the video resource.
For the fluency of the video resource, obtaining fluency assessment data of the video resource comprises: and obtaining a frame rate evaluation value of the video resource.
In the embodiment of the present invention, the frame rate evaluation value of the video resource may be obtained through the following steps.
Selecting at least one sub-video segment from a plurality of sub-video segments included in the video resource as a sampling sub-video segment, and performing quantitative analysis on the frame rate of the sampling sub-video segment to obtain a frame rate evaluation value of the video resource.
In the embodiment of the present invention, in order to ensure the reliability of the obtained sharpness degree evaluation value, at least two segments of sub-video segments may be selected from the multiple segments of sub-video segments included in the video resource as sampling sub-video segments. In practical implementation, at least two sub-video segments may be selected from multiple sub-video segments included in the video resource as sampling sub-video segments at intervals of a third preset number of frames, where the third preset number of frames may be 100 frames or 200 frames, and this is not limited in this embodiment of the present invention. After at least two segments of sub-video segments are selected as sampling sub-video segments, the frame rates of the selected at least two segments of sampling sub-video segments can be respectively subjected to quantitative analysis, at least two frame rate values corresponding to the selected at least two segments of sampling sub-video segments are obtained, and the minimum frame rate value is selected from the at least two frame rate values and is used as the frame rate evaluation value for the video resource.
For the shading degree of the video resource, obtaining shading degree evaluation data of the video resource comprises: and obtaining the color evaluation value of the video resource.
In the embodiment of the present invention, the color evaluation value of the video resource may be obtained through the following steps.
Selecting at least one frame of image from a plurality of frames of images included in the video resource as a third sampling image, then selecting at least one pixel from a plurality of pixels included in the third sampling image as a sampling pixel, and finally, carrying out quantitative analysis on the color value of the sampling pixel to obtain the color evaluation value of the video resource.
In the embodiment of the present invention, in order to ensure the reliability of the obtained color evaluation value, at least two frames of images may be selected from the multiple frames of images included in the video resource as the third sampling image. In practical implementation, the image frames of the video resource may be sorted, and at least two frames of images may be selected from the multi-frame images included in the video resource at intervals of a fourth preset number of frames, which may be 100 frames or 200 frames, as the third sampling image. After at least two frames of images are selected as third sampling images, at least two pixel points can be selected from a plurality of pixel points included in the third sampling image of each frame as sampling pixel points aiming at each third sampling image, and the selected at least two sampling pixel points are located in different areas of the third sampling image. After at least two sampling pixel points are selected, the color values of the at least two sampling pixel points are respectively subjected to quantitative analysis to obtain at least two color values corresponding to the at least two selected sampling pixel points, the minimum color value of the at least two color values is used as the reference color value of the third sampling image of the frame, and then all color reference values larger than a preset color threshold value are selected and the average value is used as the color evaluation value of the video resource. In the embodiment of the present invention, the preset color threshold may be, but is not limited to, 0 to (96, 96, 96).
And step S300, evaluating the quality of the video resource according to the quality evaluation data to obtain a quality evaluation result aiming at the video resource.
In the embodiment of the present invention, the electronic device stores preset standard evaluation data for evaluating the quality evaluation data in advance, where the preset standard evaluation data may include a preset standard resolution evaluation value, a preset standard sharpening degree evaluation value, a preset standard frame rate evaluation value, and a preset standard color evaluation value. In actual implementation, the evaluation criteria may include evaluation criterion 1, evaluation criterion 2, evaluation criterion 3, and evaluation criterion 4. The evaluation criterion 1 is that the resolution evaluation value of the video resource is greater than the preset standard resolution evaluation value, the evaluation criterion 2 is that the sharpening degree evaluation value of the video resource is greater than the preset standard sharpening degree evaluation value, the evaluation criterion 3 is that the frame rate evaluation value of the video resource is greater than the preset standard frame rate evaluation value, and the evaluation criterion 4 is that the color evaluation value of the video resource is greater than the preset standard color evaluation value. Based on this, step S300 specifically includes: and when the resolution evaluation value of the video resource is greater than the preset standard resolution evaluation value, the sharpening degree evaluation value of the video resource is greater than the preset standard sharpening degree evaluation value, the frame rate evaluation value of the video resource is greater than the preset standard frame rate evaluation value, and the color evaluation value of the video resource is greater than the preset standard color evaluation value, determining that the quality evaluation result aiming at the video resource is qualified, otherwise, determining that the quality evaluation result is unqualified.
In order to further improve the accuracy and reliability of the quality evaluation result for the video resource, in this embodiment, each quantization evaluation value for each quality evaluation factor may be obtained in a plurality of image frame orders of the video resource, that is, a plurality of obtained quantization evaluation values correspond to the image frame orders of the video resource. Based on this, in the embodiment of the present invention, the quality evaluation result of the video resource may be obtained through the following steps.
Establishing a video quality evaluation chart or a video quality evaluation curve aiming at the video resource based on the plurality of quantitative evaluation values corresponding to the image frame sequencing, and evaluating the quality of the video resource according to the video quality evaluation chart or the video quality evaluation curve to obtain a quality evaluation result aiming at the video resource.
Taking the quantization evaluation value as a resolution evaluation value as an example, a video quality evaluation chart or a video quality evaluation curve for the video resource may be established by the following steps.
And sorting the image frames of the video resource, and selecting a plurality of frames of images from the plurality of frames of images included in the video resource at intervals of a fifth preset number of frames as a target reference image, where the fifth preset number of frames may be 100 frames or 200 frames, and the embodiment of the present invention is not limited specifically to this. And then establishing a video quality evaluation chart or a video quality evaluation curve aiming at the video resource based on the resolution evaluation values of the target reference images of the plurality of frames. It is understood that the video quality assessment chart or video quality assessment curve may represent a correspondence between a resolution of the video resource and a time axis of the video resource.
Specifically, the quality of the video resource is evaluated according to the video quality evaluation chart, and a quality evaluation result for the video resource is obtained, which can be specifically realized through the following steps.
And performing statistical analysis on each quantitative evaluation value of the same type in the video quality evaluation chart or the video quality evaluation curve to obtain a qualified proportion of the quantitative evaluation value of each type, judging whether the qualified proportion of the quantitative evaluation value of each type is greater than or equal to a corresponding preset qualified proportion, if so, determining that the video resource is qualified, and otherwise, determining that the video resource is unqualified.
Taking the resolution evaluation value as an example, performing statistical analysis on each resolution evaluation value in the video quality evaluation chart to obtain a qualified ratio of the resolution evaluation values, and judging whether the qualified ratio of the resolution evaluation values is greater than or equal to a corresponding preset qualified ratio. The other processing of the quantized evaluation values may be performed in a similar manner, and for the sake of brevity of the description, the description thereof is omitted.
Based on the same inventive concept as the video quality assessment method, the embodiment of the invention also provides a video quality assessment device. Referring to fig. 3, the video quality assessment apparatus includes a video resource acquisition module 111, a quality assessment data acquisition module 112, and a quality assessment result acquisition module 113.
The video resource obtaining module 111 is configured to obtain video resources shot by the automobile data recorder. In the embodiment of the invention, the video resources can be acquired in various ways. For example, the communication connection may be obtained through a communication connection established between the electronic device and the automobile data recorder, where the communication connection may be a wired communication connection established through a data transmission line, or a wireless communication connection established through a bluetooth communication technology, an NFC communication technology, or the like. For another example, when the driving recorder plays the collected video, the video can be directly captured and acquired by other devices with the shooting function. Taking the example that the video resource acquisition module 111 acquires video resources shot by the automobile data recorder through a bluetooth communication technology, after receiving a video resource acquisition request, the video resource acquisition module 111 generates a bluetooth start instruction according to the video resource acquisition request, and sends the bluetooth start instruction to the bluetooth module of the electronic device so as to control bluetooth start of the electronic device, establish wireless communication connection with the automobile data recorder, and perform data transmission.
The quality assessment data obtaining module 112 is configured to quantize the quality assessment factor of the video resource, so as to obtain quality assessment data of the video resource.
Specifically, the video quality of the video resource may be evaluated from one or more dimensions, such as sharpness, fluency, shading, and the like, that is, in the embodiment of the present invention, the quality evaluation factor may include one or more quality evaluation factors of sharpness, fluency, and shading. Correspondingly, the various quality assessment factors of the video resources are quantized, that is: and carrying out quantitative analysis on the video resource to obtain one or more quality evaluation data of definition evaluation data, fluency evaluation data and brightness evaluation data of the video resource. Wherein each of the quality assessment data comprises at least one quantitative assessment value, and each of the quantitative assessment values may comprise one or more specific numerical values.
In this embodiment of the present invention, the sharpness evaluation data may include at least one quantization evaluation value of a resolution evaluation value and a sharpening degree evaluation value, that is, the sharpness of the video resource may be evaluated from at least one dimension of the resolution and the sharpening degree.
Based on the above description, for the definition of the video resource, obtaining definition evaluation data of the video resource includes: and obtaining one or two of a resolution evaluation value and a sharpening degree evaluation value of the video resource.
In an embodiment of the present invention, the quality estimation data acquisition module 112 may include a first sampling image acquisition unit and a resolution estimation value acquisition unit.
The first sampling image obtaining unit is used for selecting at least one frame of image from a plurality of frames of images included in the video resource as a first sampling image. The resolution evaluation value acquisition unit is used for carrying out quantitative analysis on the resolution of the first sampling image to obtain a resolution evaluation value aiming at the video resource.
In an embodiment of the present invention, to ensure reliability of the obtained resolution evaluation value, the first sampled image obtaining unit may select at least two frames of images from a plurality of frames of images included in the video resource as the first sampled image. In practical implementation, the image frames of the video resource may be sorted, and at least two frames of images are selected from the multi-frame images included in the video resource at intervals of a first preset number of frames, as a first sampling image, where the first preset number of frames may be 100 frames or 200 frames, which is not limited in this embodiment of the present invention. After the first sampled image obtaining unit selects at least two frames of images as the first sampled image, the resolution evaluation value obtaining unit may perform quantization analysis on the resolutions of the selected at least two frames of first sampled images, respectively, to obtain at least two reference resolution values corresponding to the selected at least two frames of first sampled images, and select a minimum reference resolution value from the at least two reference resolution values as a resolution evaluation value for the video resource.
In an embodiment of the present invention, the quality estimation data acquiring module 112 may include a second sampling image acquiring unit and a sharpening degree estimation value acquiring unit.
The second sampling image obtaining unit is used for selecting at least one frame of image from a plurality of frames of images included in the video resource as a second sampling image. The sharpening degree evaluation value acquisition unit is used for carrying out quantitative analysis on the sharpening degree of the second sampling image to obtain a sharpening degree evaluation value aiming at the video resource.
Also, in an embodiment of the present invention, to ensure reliability of the obtained sharpness degree evaluation value, the second sample image obtaining unit may select at least two frame images from the multiple frame images included in the video resource as the second sample image. In practical implementation, the image frames of the video resource may be sorted, and at least two frames of images may be selected from the multi-frame images included in the video resource at intervals of a second preset number of frames, as a second sampling image, where the second preset number of frames may be 100 frames or 200 frames, which is not limited in this embodiment of the present invention. After the second sampled image acquiring unit selects at least two frames of images as the second sampled image, the sharpening degree evaluation value acquiring unit may perform quantization analysis on the sharpening degrees of the selected at least two frames of second sampled images, respectively, to obtain at least two reference sharpening degree values corresponding to the selected at least two frames of second sampled images, and select a minimum reference sharpening degree value from the at least two reference sharpening degree values, as the sharpening degree evaluation value for the video resource.
For the fluency of the video resource, obtaining fluency assessment data of the video resource comprises: and obtaining a frame rate evaluation value of the video resource.
In an embodiment of the present invention, the quality estimation data obtaining module 112 may include a sampling sub-video segment obtaining unit and a frame rate estimation value obtaining unit.
The sampling sub-video segment obtaining unit is used for selecting at least one sub-video segment from a plurality of sub-video segments included in the video resource as a sampling sub-video segment. The frame rate evaluation value acquisition unit is used for carrying out quantitative analysis on the frame rate of the sampling sub-video segment to acquire the frame rate evaluation value of the video resource.
In an embodiment of the present invention, to ensure reliability of the obtained sharpness degree evaluation value, the sampling sub-video segment obtaining unit may select at least two sub-video segments from multiple sub-video segments included in the video resource as sampling sub-video segments. In practical implementation, at least two sub-video segments may be selected from multiple sub-video segments included in the video resource as sampling sub-video segments at intervals of a third preset number of frames, where the third preset number of frames may be 100 frames or 200 frames, and this is not limited in this embodiment of the present invention. After the sampling sub-video segment obtaining unit selects at least two sub-video segments as sampling sub-video segments, the frame rate estimation value obtaining unit may perform quantization analysis on the frame rates of the selected at least two sampling sub-video segments, respectively, to obtain at least two frame rate values corresponding to the selected at least two sampling sub-video segments, and select a minimum frame rate value from the at least two frame rate values as a frame rate estimation value for the video resource.
For the shading of the video resource, obtaining shading assessment data for the video resource comprises: and obtaining the color evaluation value of the video resource.
In an embodiment of the present invention, the quality estimation data obtaining module 112 may include a third sampling image obtaining unit, a sampling pixel point obtaining unit, and a color estimation value obtaining unit.
The third sampling image obtaining unit is used for selecting at least one frame of image from a plurality of frames of images included in the video resource as a third sampling image. The sampling pixel point obtaining unit is used for selecting at least one pixel point from a plurality of pixel points included in the third sampling image as a sampling pixel point. The color evaluation value acquisition unit is used for carrying out quantitative analysis on the color values of the sampling pixel points to acquire the color evaluation value of the video resource.
In an embodiment of the present invention, to ensure reliability of the obtained color evaluation value, the third sampled image obtaining unit may select at least two frames of images from a plurality of frames of images included in the video resource as the third sampled image. In practical implementation, the image frames of the video resource may be sorted, and at least two frames of images may be selected from the multi-frame images included in the video resource at intervals of a fourth preset number of frames, which may be 100 frames or 200 frames, as the third sampling image. The third sampling image obtaining unit selects at least two frames of images, and after the images are used as a third sampling image, the sampling pixel point obtaining unit can select at least two pixel points from a plurality of pixel points included in the third sampling image as sampling pixel points aiming at each frame of the third sampling image, and the selected at least two sampling pixel points are located in different areas of the third sampling image. After the sampling pixel point obtaining unit selects at least two sampling pixel points, the color evaluation value obtaining unit can respectively perform quantitative analysis on the color values of the at least two sampling pixel points to obtain at least two color values corresponding to the selected at least two sampling pixel points, and use the minimum color value of the at least two color values as the reference color value of the third sampling image of the frame, and then select all color reference values larger than a preset color threshold value, and use the average value thereof as the color evaluation value of the video resource. In the embodiment of the present invention, the preset color threshold may be, but is not limited to, O ~ (96, 96, 96).
The quality evaluation result obtaining module 113 is configured to evaluate the quality of the video resource according to the quality evaluation data, and obtain a quality evaluation result for the video resource.
In the embodiment of the present invention, the electronic device stores preset standard evaluation data for evaluating the quality evaluation data in advance, where the preset standard evaluation data may include a preset standard resolution evaluation value, a preset standard sharpening degree evaluation value, a preset standard frame rate evaluation value, and a preset standard color evaluation value. In actual implementation, the evaluation criteria may include evaluation criterion 1, evaluation criterion 2, evaluation criterion 3, and evaluation criterion 4. The evaluation criterion 1 is that the resolution evaluation value of the video resource is greater than the preset standard resolution evaluation value, the evaluation criterion 2 is that the sharpening degree evaluation value of the video resource is greater than the preset standard sharpening degree evaluation value, the evaluation criterion 3 is that the frame rate evaluation value of the video resource is greater than the preset standard frame rate evaluation value, and the evaluation criterion 4 is that the color evaluation value of the video resource is greater than the preset standard color evaluation value. Based on this, step S300 specifically includes: and when the resolution evaluation value of the video resource is greater than the preset standard resolution evaluation value, the sharpening degree evaluation value of the video resource is greater than the preset standard sharpening degree evaluation value, the frame rate evaluation value of the video resource is greater than the preset standard frame rate evaluation value, and the color evaluation value of the video resource is greater than the preset standard color evaluation value, determining that the quality evaluation result aiming at the video resource is qualified, otherwise, determining that the quality evaluation result is unqualified.
In order to further improve the accuracy and reliability of the quality evaluation result for the video resource, in this embodiment, each quantization evaluation value for each quality evaluation factor may be obtained in a plurality of image frame orders of the video resource, that is, a plurality of obtained quantization evaluation values correspond to the image frame orders of the video resource. Based on this, in this embodiment, the quality evaluation result obtaining module 113 includes a quality evaluation tool establishing unit and a quality evaluation result obtaining unit.
The quality evaluation tool establishing unit is used for establishing a video quality evaluation chart or a video quality evaluation curve aiming at the video resource based on the plurality of quantitative evaluation values corresponding to the image frame sequence. The quality evaluation result acquisition unit is used for evaluating the quality of the video resources according to the video quality evaluation chart or the video quality evaluation curve to acquire a quality evaluation result aiming at the video resources.
Taking the quantization evaluation value as a resolution evaluation value as an example, a video quality evaluation chart or a video quality evaluation curve for the video resource may be established by the following steps.
And sorting the image frames of the video resource, and selecting a plurality of frames of images from the plurality of frames of images included in the video resource at intervals of a fifth preset number of frames as a target reference image, where the fifth preset number of frames may be 100 frames or 200 frames, and the embodiment of the present invention is not limited specifically to this. Thereafter, the quality evaluation tool creation unit creates a video quality evaluation chart or a video quality evaluation curve for the video resource based on the resolution evaluation values of the plurality of frames of the target reference image. It is understood that the video quality assessment chart or video quality assessment curve may represent a correspondence between a resolution of the video resource and a time axis of the video resource.
Specifically, the quality of the video resource is evaluated according to the video quality evaluation chart, and a quality evaluation result for the video resource is obtained, which can be specifically realized through the following steps.
And performing statistical analysis on each quantitative evaluation value of the same type in the video quality evaluation chart or the video quality evaluation curve to obtain a qualified proportion of the quantitative evaluation value of each type, judging whether the qualified proportion of the quantitative evaluation value of each type is greater than or equal to a corresponding preset qualified proportion, if so, determining that the video resource is qualified, and otherwise, determining that the video resource is unqualified.
Taking the resolution evaluation value as an example, performing statistical analysis on each resolution evaluation value in the video quality evaluation chart to obtain a qualified ratio of the resolution evaluation values, and judging whether the qualified ratio of the resolution evaluation values is greater than or equal to a corresponding preset qualified ratio. The other processing of the quantized evaluation values may be performed in a similar manner, and for the sake of brevity of the description, the description thereof is omitted.
The video quality assessment method, the video quality assessment device and the electronic equipment provided by the embodiment of the invention can acquire video resources shot by a driving recorder, quantize quality assessment factors of the video resources, acquire quality assessment data of the video resources, and assess the quality of the video resources according to the quality assessment data to acquire quality assessment results aiming at the video resources. The quality evaluation data is a quantization result obtained by quantizing the quality evaluation factor of the video resource shot by the automobile data recorder, and then the quality of the video resource is evaluated according to the quality evaluation data, so that the quality of the video resource can be accurately evaluated, the interference of human factors on the evaluation result of the video resource is avoided, and the more accurate and reliable quality evaluation of the video shot by the automobile data recorder is realized.
In the above embodiments provided by the embodiments of the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present disclosure may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, an electronic device, or a network device) to execute all or part of the steps of the method according to the embodiments of the present disclosure. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk. 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. The term "comprising" is used to specify the presence of stated features, integers, steps, operations, elements, components, and/or groups thereof, but does not exclude the presence of other similar features, integers, steps, operations, components, or groups thereof.
The above are merely alternative embodiments of the present disclosure and are not intended to limit the present disclosure, which may be modified and varied by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
A1. A video quality assessment method, comprising:
acquiring video resources shot by a vehicle event data recorder;
quantifying the quality evaluation factor of the video resource to obtain quality evaluation data of the video resource;
and evaluating the quality of the video resources according to the quality evaluation data to obtain a quality evaluation result aiming at the video resources.
A2. The video quality assessment method of claim a1, the obtaining quality assessment data for the video asset, comprising:
one or more quality assessment data of the sharpness assessment data, the fluency assessment data, and the brightness assessment data are obtained.
A3. The video quality assessment method of claim a2, the sharpness assessment data comprising a resolution assessment value, the quantifying a quality assessment factor for the video asset to obtain quality assessment data for the video asset, comprising:
selecting at least one frame of image from a plurality of frames of images included in the video resource as a first sampling image;
and carrying out quantitative analysis on the resolution of the first sampling image to obtain a resolution evaluation value aiming at the video resource.
A4. The video quality assessment method of claim a2, the sharpness assessment data comprising a degree of sharpness assessment value, the quantifying a quality assessment factor for the video resource to obtain quality assessment data for the video resource, comprising:
selecting at least one frame of image from a plurality of frames of images included in the video resource as a second sampling image;
and carrying out quantitative analysis on the sharpening degree of the second sampling image to obtain a sharpening degree evaluation value aiming at the video resource.
A5. The video quality assessment method of claim a2, the fluency assessment data comprising a frame rate assessment value, the quantifying a quality assessment factor for the video asset to obtain quality assessment data for the video asset, comprising:
selecting at least one sub-video segment from a plurality of sub-video segments included in the video resource as a sampling sub-video segment;
and carrying out quantitative analysis on the frame rate of the sampling sub-video segment to obtain a frame rate evaluation value of the video resource.
A6. The video quality assessment method of claim a2, the shading assessment data comprising a color assessment value, the quantifying a quality assessment factor for the video asset to obtain quality assessment data for the video asset, comprising:
selecting at least one frame of image from a plurality of frames of images included in the video resource as a third sampling image;
selecting at least one pixel point from a plurality of pixel points included in the third sampling image as a sampling pixel point;
and carrying out quantitative analysis on the color value of the sampling pixel point to obtain a color evaluation value of the video resource.
A7. The video quality assessment method of claim a1 or a2, the quality assessment data comprising one or more quantitative assessment values for the video asset.
A8. The video quality assessment method of claim a7, the quality assessment data comprising a plurality of quantitative assessment values corresponding to image frame ordering, the assessing the quality of the video asset from the quality assessment data to obtain quantitative assessment results for the video asset, comprising:
establishing a video quality evaluation chart or a video quality evaluation curve for the video resource based on the plurality of quantitative evaluation values corresponding to the image frame ordering;
and evaluating the quality of the video resources according to the video quality evaluation chart or the video quality evaluation curve to obtain a quality evaluation result aiming at the video resources.
B9. A video quality assessment apparatus comprising:
the video resource acquisition module is used for acquiring video resources shot by the automobile data recorder;
the quality evaluation data acquisition module is used for quantizing the quality evaluation factors of the video resources to acquire quality evaluation data of the video resources;
and the quality evaluation result acquisition module is used for evaluating the quality of the video resources according to the quality evaluation data to acquire a quality evaluation result aiming at the video resources.
B10. The video quality assessment apparatus of claim B9, the quality assessment data comprising one or more of sharpness assessment data, fluency assessment data, and shading assessment data.
B11. The video quality assessment apparatus according to claim B10, the sharpness assessment data comprising a resolution assessment value, the quality assessment data acquisition module comprising:
the first sampling image acquisition unit is used for selecting at least one frame of image from a plurality of frames of images included in the video resource as a first sampling image;
and the resolution evaluation value acquisition unit is used for carrying out quantitative analysis on the resolution of the first sampling image to obtain a resolution evaluation value aiming at the video resource.
B12. The video quality assessment apparatus according to claim B10, the sharpness assessment data comprising a degree of sharpness assessment value, the quality assessment data acquisition module comprising:
the second sampling image acquisition unit is used for selecting at least one frame of image from a plurality of frames of images included in the video resource as a second sampling image;
and the sharpening degree evaluation value acquisition unit is used for carrying out quantitative analysis on the sharpening degree of the second sampling image to obtain a sharpening degree evaluation value aiming at the video resource.
B13. The video quality assessment apparatus of claim B10, the fluency assessment data comprising a frame rate assessment value, the quality assessment data acquisition module comprising:
a sampling sub-video segment obtaining unit, configured to select at least one sub-video segment from multiple sub-video segments included in the video resource as a sampling sub-video segment;
and the frame rate evaluation value acquisition unit is used for carrying out quantitative analysis on the frame rate of the sampling sub-video segment to acquire the frame rate evaluation value of the video resource.
B14. The video quality assessment apparatus of claim B10, the shading assessment data comprising a color assessment value, the quality assessment data acquisition module comprising:
the third sampling image acquisition unit is used for selecting at least one frame of image from a plurality of frames of images included in the video resource as a third sampling image;
a sampling pixel point obtaining unit, configured to select at least one pixel point from a plurality of pixel points included in the third sampling image, as a sampling pixel point;
and the color evaluation value acquisition unit is used for carrying out quantitative analysis on the color values of the sampling pixel points to acquire the color evaluation value of the video resource.
B15. The video quality assessment apparatus of claims B9 or B10, the quality assessment data comprising one or more quantitative assessment values for the video asset.
B16. The video quality assessment apparatus according to claim B15, the quality assessment data comprising a plurality of quantitative assessment values corresponding to image frame ordering, the quality assessment result acquisition module comprising:
a quality evaluation tool establishing unit for establishing a video quality evaluation chart or a video quality evaluation curve for the video resource based on the plurality of quantitative evaluation values corresponding to the image frame ordering;
and the quality evaluation result acquisition unit is used for evaluating the quality of the video resources according to the video quality evaluation chart or the video quality evaluation curve to acquire a quality evaluation result aiming at the video resources.
C17. An electronic device comprising a processor, a memory, and the video quality assessment apparatus of any of claims B9-B16, the video quality assessment apparatus comprising one or more software functional modules stored in the memory and executed by the processor.
D18. A computer-readable storage medium having stored thereon a computer program which, when executed, implements the video quality assessment method of any of claims a 1-A8.
Claims (10)
1. A method for video quality assessment, comprising:
acquiring video resources shot by a vehicle event data recorder;
quantifying the quality evaluation factor of the video resource to obtain quality evaluation data of the video resource;
and evaluating the quality of the video resources according to the quality evaluation data to obtain a quality evaluation result aiming at the video resources.
2. The method of claim 1, wherein the obtaining quality assessment data for the video asset comprises:
one or more quality assessment data of the sharpness assessment data, the fluency assessment data, and the brightness assessment data are obtained.
3. The method according to claim 2, wherein the sharpness evaluation data includes a resolution evaluation value, and the quantizing the quality evaluation factor of the video resource to obtain the quality evaluation data of the video resource includes:
selecting at least one frame of image from a plurality of frames of images included in the video resource as a first sampling image;
and carrying out quantitative analysis on the resolution of the first sampling image to obtain a resolution evaluation value aiming at the video resource.
4. The method according to claim 2, wherein the sharpness evaluation data includes a sharpness evaluation value, and the quantizing the quality evaluation factor of the video resource to obtain the quality evaluation data of the video resource includes:
selecting at least one frame of image from a plurality of frames of images included in the video resource as a second sampling image;
and carrying out quantitative analysis on the sharpening degree of the second sampling image to obtain a sharpening degree evaluation value aiming at the video resource.
5. The method of claim 2, wherein the fluency assessment data comprises a frame rate assessment value, and wherein the quantifying the quality assessment factor of the video resource to obtain the quality assessment data of the video resource comprises:
selecting at least one sub-video segment from a plurality of sub-video segments included in the video resource as a sampling sub-video segment;
and carrying out quantitative analysis on the frame rate of the sampling sub-video segment to obtain a frame rate evaluation value of the video resource.
6. The method according to claim 2, wherein the shading evaluation data comprises a color evaluation value, and the quantifying a quality evaluation factor of the video resource to obtain the quality evaluation data of the video resource comprises:
selecting at least one frame of image from a plurality of frames of images included in the video resource as a third sampling image;
selecting at least one pixel point from a plurality of pixel points included in the third sampling image as a sampling pixel point;
and carrying out quantitative analysis on the color value of the sampling pixel point to obtain a color evaluation value of the video resource.
7. The video quality assessment method according to claim 1 or 2, wherein said quality assessment data comprises one or more quantitative assessment values for said video resources.
8. A video quality assessment apparatus, comprising:
the video resource acquisition module is used for acquiring video resources shot by the automobile data recorder;
the quality evaluation data acquisition module is used for quantizing the quality evaluation factors of the video resources to acquire quality evaluation data of the video resources;
and the quality evaluation result acquisition module is used for evaluating the quality of the video resources according to the quality evaluation data to acquire a quality evaluation result aiming at the video resources.
9. An electronic device comprising a processor, a memory, and the video quality assessment apparatus of claim 8, said video quality assessment apparatus comprising one or more software functional modules stored in said memory and executed by said processor.
10. A computer-readable storage medium on which a computer program is stored, wherein the computer program, when executed, implements the video quality assessment method of any one of claims 1-7.
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