CN113837128A - Emotion recognition method, system and storage medium - Google Patents
Emotion recognition method, system and storage medium Download PDFInfo
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Abstract
The invention discloses a method, a system and a storage medium for emotion recognition, wherein the method comprises the following steps: extracting emotional characteristics of the human face according to externally input video stream information to obtain a vibration image; performing pixel microseismic analysis according to the vibration image to form a vibration light ring; and recognizing the emotional state according to the vibration halo. The recognition method extracts the emotional characteristics of the human face to form a vibration image, and can directly reflect the emotional state; meanwhile, the vibration image is subjected to pixel microseismic analysis to obtain a vibration halo, the accuracy of emotion judgment can be improved by adopting a pixel microseismic analysis technology, the judgment error is reduced, and finally, the motion of the object and the emotional state of the object is described through the vibration halo, so that the corresponding emotional state diagram is displayed more visually. Therefore, by implementing the method and the device, more reasonable and accurate characteristic data values are provided for emotion recognition, the error of an emotion recognition result is reduced, the accuracy of emotion recognition is improved, and effective judgment basis is provided for emotion prediction.
Description
Technical Field
The invention relates to the technical field of intelligent recognition, in particular to an emotion recognition method, system and storage medium.
Background
Micro-expressions are the mental effluence and masking of a person, are psychological terms, and are a branch of human behaviours. People express the feeling of mind to the other side to see by doing some expressions, and other information is often revealed by the face between different expressions or in a certain expression which people do. "microexpressions" last 1/25 seconds at the shortest, although a subconscious expression may last only a moment, it is an annoying property and it is easy to expose the mood. The duration of the micro-expressions is short, the capture by a machine is easier than the capture by human eyes, and the application of the deep learning algorithm makes the recognition of the micro-expressions very accurate.
In the prior art, a method for recognizing emotion of a person relies on contact detection to obtain pulse pulses of a person to be tested and then measure changes of psychophysiological signals generated by the person to be tested, or non-contact detection is adopted to obtain the psychophysiological signals of the person to be tested, and then the psychophysiological signals are compared with a set standard signal to recognize emotion.
However, the emotion recognition result obtained in the prior art is often large in deviation, and an effective judgment basis cannot be provided for emotion prediction.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method, a system, and a storage medium for emotion recognition, so as to solve the technical problems in the prior art that an effective judgment basis cannot be provided for emotion prediction and advance security control cannot be implemented due to deviation of an emotion recognition result.
The technical scheme provided by the invention is as follows:
a first aspect of an embodiment of the present invention provides an emotion recognition method, where the emotion recognition method includes: extracting emotional characteristics of the human face according to externally input video stream information to obtain a vibration image; performing pixel microseismic analysis according to the vibration image to form a vibration light ring; and recognizing the emotional state according to the vibration halo.
Optionally, extracting emotional features of the human face according to externally input video stream information to obtain a vibration image, including: acquiring video stream information of a tested person; acquiring the amplitude and vibration frequency of each pixel point on the face of the detected person according to the video stream information; and determining a vibration image according to the vibration frequency and the vibration amplitude.
Optionally, performing pixel microseismic analysis according to the vibration image to form a vibration halo, and performing emotional state recognition according to the vibration halo, including: determining a vibration color level according to the vibration range of the vibration frequency of each pixel point of the vibration image; determining the size of the vibration halo according to the average amplitude of the vibration image within a preset range; obtaining a vibration halo according to the vibration color level and the vibration halo size; and recognizing the emotional state according to the vibration halo.
Optionally, the emotion recognition method further includes: generating an emotion analysis report according to the emotion state recognition result, wherein the emotion analysis report comprises: a comprehensive emotion analysis result table and an emotion-energy change chart; and sending an emotion early warning signal according to the emotion state recognition result.
A second aspect of an embodiment of the present invention provides an emotion recognition system, including: the camera is used for acquiring video stream information of a tested person; a microprocessor, comprising: the characteristic extraction module is used for extracting the emotion characteristics of the human face according to externally input video stream information to obtain a vibration image; the analysis module is used for carrying out pixel microseismic analysis according to the vibration image to form a vibration light ring; and the identification module is used for carrying out emotion state identification according to the vibration halo.
Optionally, the feature extraction module includes: the vibration parameter acquisition module is used for acquiring the amplitude and the vibration frequency of each pixel point on the face of the detected person according to the video stream information; and the vibration image determining module is used for determining a vibration image according to the vibration frequency and the vibration amplitude.
Optionally, the analysis module comprises: the vibration color gradation determining module is used for determining a vibration color gradation according to the vibration range of the vibration frequency of each pixel point of the vibration image; the halo size determining module is used for determining the size of the vibration halo according to the average amplitude of the vibration image within a preset range;
optionally, the microprocessor further comprises: a report generation module, configured to generate an emotion analysis report according to the emotion state recognition result, where the emotion analysis report includes: a comprehensive emotion analysis result table and an emotion-energy change chart; and the result sending module is used for sending the emotion early warning signal according to the emotion state recognition result.
A third aspect of embodiments of the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the emotion recognition method according to any one of the first aspect and the first aspect of the embodiments of the present invention.
The technical scheme provided by the invention has the following effects:
according to the emotion recognition method, the emotion recognition system and the storage medium, the emotion characteristics of the face are extracted according to the externally input video stream information to obtain a vibration image; performing pixel microseismic analysis according to the vibration image to form a vibration light ring; and recognizing the emotional state according to the vibration halo. The recognition method extracts the emotional characteristics of the human face to form a vibration image, and can directly reflect the emotional state; meanwhile, the vibration image is subjected to pixel microseismic analysis to obtain a vibration halo, the accuracy of emotion judgment can be improved by adopting a pixel microseismic analysis technology, the judgment error is reduced, and finally, the motion of the object and the emotional state of the object is described through the vibration halo, so that the corresponding emotional state diagram is displayed more visually. Therefore, by implementing the method and the device, more reasonable and accurate characteristic data values are provided for emotion recognition, the error of an emotion recognition result is reduced, the accuracy of emotion recognition is improved, and effective judgment basis is provided for emotion prediction.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of an emotion recognition method according to an embodiment of the present invention;
fig. 2 is a block diagram of the structure of an emotion recognition system according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a computer-readable storage medium provided in accordance with an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
An embodiment of the present invention provides an emotion recognition method, as shown in fig. 1, the method including the steps of:
step S101: and extracting the emotional characteristics of the human face according to the externally input video stream information to obtain a vibration image. In particular, the video stream information may be acquired by an external input device prior to feature extraction, wherein the external input device may be a video camera. In addition, external input device can also be intelligent individual soldier's equipment, like wireless law enforcement record appearance, on-vehicle intelligence equip, portable intelligence equip, police unmanned aerial vehicle, other intelligent wearable equipment etc.. Or when emotion recognition is needed in law enforcement, the external input device can also be an intelligent technical device with the functions of real-time video and audio recording, image snapshot recognition, data communication, position acquisition and the like. The external input device is not particularly limited in the embodiments of the present invention.
After the video stream information is obtained, the face features can be extracted according to the video stream information, and the amplitude and the frequency of each pixel point of the face are obtained. When the amplitude and the frequency of each pixel point are determined, a human body thermodynamic observation method can be adopted, the vibration times of the human face in the video stream information are analyzed through the method, and the amplitude and the vibration period are calculated, so that the vibration frequency is obtained. Since the difference between slightly moving frames is an image moving relative to the object, the amplitude of each pixel point can reflect the pixel of the relative motion. And then, respectively displaying in the vibration parameter-frequency and amplitude forms of all the pixel points to form a vibration image.
Step S102: and carrying out pixel microseismic analysis according to the vibration image to form a vibration light ring. Specifically, after a vibration image is formed, pixel microseismic analysis is carried out on the vibration frequency and the amplitude parameter of each pixel point on the face, and a vibration halo is formed.
In one embodiment, the forming of the vibrating light ring is realized according to the following steps: determining a vibration color level according to the vibration range of the vibration frequency of each pixel point of the vibration image; determining the size of the vibration halo according to the average amplitude of the vibration image within a preset range; and obtaining the vibration halo according to the vibration color level and the vibration halo.
Specifically, after the vibration image is acquired, pixel microseismic analysis is performed on the vibration image, wherein each pixel point amplitude of the vibration image reflects a pixel of relative motion because a small moving frame-to-frame difference is an image moving relative to an object. And then determining a vibration color level according to the vibration range of the vibration frequency of each pixel point of the vibration image. The frequency of each pixel point is used as the signal change of the real display frequency, and each element of the image has the physical dimension frequency.
In one embodiment, the relationship between the vibration tone scale and the vibration frequency range may be predetermined. For example, violet indicates a vibration frequency range of 0-1 Hz, deep blue indicates a vibration frequency range of 1-4 Hz, green indicates a vibration frequency range of 4-8 Hz, and red indicates a vibration frequency range of 8-10 Hz. Therefore, after the vibration frequency range of the face image is determined, the corresponding vibration color level can be determined according to the preset corresponding relation.
And after the vibration color gradation is determined, determining the size of the vibration halo according to the average amplitude of the vibration image in the preset range. Specifically, the halo is first defined to show the average amplitude for the maximum frequency of external (around the head of the person being tested) motion. Then obtaining a vibration image within a preset range, counting the amplitude and vibration frequency of each pixel point in the vibration image, calculating the average amplitude and the maximum frequency of the vibration image, determining the maximum frequency display average amplitude as the size of a vibration halo within the preset range, and changing the size of the halo according to the change of the average amplitude.
Therefore, the vibration halo corresponding to the vibration image can be obtained through the process of determining the vibration color level and the vibration halo size of the vibration image.
Step S103: and recognizing the emotional state according to the vibration halo. In particular, after acquiring the vibrating halo, the motion of the object and its emotional state may be depicted according to the color and size of the halo. For example, the human state under normal conditions is more uniform in space and color. Thus, after determining the vibrating halo, the corresponding emotional state may be determined therefrom.
As an optional implementation manner of the embodiment of the present invention, emotional state recognition is performed according to the vibration halo. Specifically, since any non-uniform halo with color and size depicts the motion of the object and its emotional state, after obtaining the vibration halo, it is necessary to determine the halo color and size of the vibration halo, identify the emotional state according to the color of the vibration halo, and determine the degree of the emotional state according to the size of the vibration halo.
Specifically, the form of the vibrating halo includes: any asymmetric halo (morphology, color) is a deviation from the normal specification of psychology or physiology; the color irregularity of the vibration halo is the expression of psychophysiological imbalance; the ideal light ring has the characteristics of single color, symmetry, uniformity and the like. Wherein, the color of the vibration halo is used to represent the frequency of the vibration, and since the vibration frequency is the change of the vibration image within the preset range, i.e. the vibration color scale, the color of the vibration halo within the preset range is consistent with the color of the vibration color scale.
In one embodiment, the normal human features are more uniform, i.e., the vibrating halo is uniform, and the tense human state has a vibrating halo with non-uniform space and color. Therefore, the emotion is recognized according to the color and the size of the vibration halo.
Specifically, when the vibration halo is red, the emotional state is represented as activity and aggressiveness; when the vibrating halo is yellow, the emotional state is worried and tensed; when the vibration halo is green, the emotional state is normal; when the vibrating halo is blue, the emotional state is rest and calm.
After the emotional state is determined, the degree of the emotional state is determined according to the size of the vibration halo, specifically, the average amplitude of the vibration image reflects the emotional fluctuation of the tested person, the larger the average amplitude is, the larger the emotional fluctuation is, and the size of the vibration halo changes according to the change of the average amplitude, so that the degree of the emotional state can be determined according to the size of the vibration halo.
In one embodiment, the larger the vibration halo is, the larger the average amplitude of the vibration image is, and the larger the emotional fluctuation is; also, when the average amplitude graph tends to be stable, the smaller the fluctuation of emotion, the more stable the emotional state tends to be.
Therefore, after the vibration halo is obtained according to the vibration image, the specific emotional state of the vibration halo is determined according to the color of the vibration halo, and the degree of the emotional state in the emotional state is determined according to the size of the vibration halo.
According to the emotion recognition method provided by the embodiment of the invention, the emotion characteristics of the face are extracted according to the externally input video stream information to obtain a vibration image; performing pixel microseismic analysis according to the vibration image to form a vibration light ring; and recognizing the emotional state according to the vibration halo. The recognition method extracts the emotional characteristics of the human face to form a vibration image, and can directly reflect the emotional state; meanwhile, the vibration image is subjected to pixel microseismic analysis to obtain a vibration halo, the accuracy of emotion judgment can be improved by adopting a pixel microseismic analysis technology, the judgment error is reduced, and finally, the motion of the object and the emotional state of the object is described through the vibration halo, so that the corresponding emotional state diagram is displayed more visually. Therefore, by implementing the method and the device, more reasonable and accurate characteristic data values are provided for emotion recognition, the error of an emotion recognition result is reduced, the accuracy of emotion recognition is improved, and effective judgment basis is provided for emotion prediction.
According to the emotion recognition method provided by the embodiment of the invention, when the vibration image is formed, the amplitude and the vibration frequency of each pixel point of video stream information are extracted to form the vibration image, the emotion recognition degree can be improved by adopting the characteristic extraction value, and the formed vibration image can directly reflect the emotion state.
In one embodiment, before acquiring the video stream information of the person to be tested, firstly, parameters of the external input device are set, and it is determined that the person to be tested is uniformly illuminated and the image of the person is clear. The external input device parameters include video camera video Proc Amp (brightness, contrast, saturation, etc.), camera control (exposure, etc.), data stream format (video standard, frame rate, output size, etc.). And then acquiring the video stream information of the tested person according to external input equipment, and extracting human face emotion characteristics according to the video stream information to further obtain a vibration image. Specifically, after the video stream information of the person to be tested is acquired, if the acquired video stream information of a certain person is acquired, the emotional characteristics of the person to be tested can be determined according to the amplitude and the frequency of the facial pixel points of the person to be tested, and then the corresponding vibration image can be further obtained. The vibration images are respectively displayed in the vibration parameter-frequency and amplitude forms of all pixel points of the face of the tested person.
As an optional implementation manner of the embodiment of the present invention, after determining an emotional state recognition result, an emotional analysis report may be generated according to the emotional state recognition result, where the emotional analysis report includes: a comprehensive emotion analysis result table and a emotion-energy change chart. Specifically, the emotion comprehensive analysis result table comprises basic information of the tested person, a comprehensive inspection result, brain fatigue, a mental state table and the like; the emotion-energy change map comprises basic information of a tested person, an emotion-energy change map, emotion-energy correlation, a mental state distribution and the like.
As an optional implementation manner of the embodiment of the present invention, after determining the emotional state recognition result, sending an emotional early warning signal according to the result. Specifically, when the emotional state is not a normal state, an emotional early warning signal is transmitted.
In one embodiment, the emotional early warning signal is sent when the vibration color level is red, that is, the tested person shows an offensive emotional state.
An embodiment of the present invention further provides an emotion recognition system, as shown in fig. 2, the system includes:
the camera is used for acquiring video stream information of a tested person; for details, refer to the related description of step S101 in the above method embodiment.
A microprocessor, comprising:
the characteristic extraction module is used for extracting the emotion characteristics of the human face according to externally input video stream information to obtain a vibration image; for details, refer to the related description of step S101 in the above method embodiment.
The analysis module is used for carrying out pixel microseismic analysis according to the vibration image to form a vibration light ring; for details, refer to the related description of step S102 in the above method embodiment.
And the identification module is used for carrying out emotion state identification according to the vibration halo. For details, refer to the related description of step S103 in the above method embodiment.
In one embodiment, the feature extraction module comprises:
the vibration parameter acquisition module is used for acquiring the amplitude and the vibration frequency of each pixel point on the face of the detected person according to the video stream information; for details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
And the vibration image determining module is used for determining a vibration image according to the vibration frequency and the vibration amplitude. For details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
In one embodiment, the analysis module includes:
the vibration color gradation determining module is used for determining a vibration color gradation according to the vibration range of the vibration frequency of each pixel point of the vibration image; for details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
The halo size determining module is used for determining the size of the vibration halo according to the average amplitude of the vibration image within a preset range; for details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
And the light ring determining module is used for obtaining the vibration light ring according to the vibration color level and the vibration light ring size. For details, reference is made to the corresponding parts of the above method embodiments, which are not described herein again.
According to the emotion recognition system provided by the embodiment of the invention, the emotion characteristics of the face are extracted according to the externally input video stream information to obtain a vibration image; performing pixel microseismic analysis according to the vibration image to form a vibration light ring; and recognizing the emotional state according to the vibration halo. The recognition method extracts the emotional characteristics of the human face to form a vibration image, and can directly reflect the emotional state; meanwhile, the vibration image is subjected to pixel microseismic analysis to obtain a vibration halo, the accuracy of emotion judgment can be improved by adopting a pixel microseismic analysis technology, the judgment error is reduced, and finally, the motion of the object and the emotional state of the object is described through the vibration halo, so that the corresponding emotional state diagram is displayed more visually. Therefore, by implementing the method and the device, more reasonable and accurate characteristic data values are provided for emotion recognition, the error of an emotion recognition result is reduced, the accuracy of emotion recognition is improved, and effective judgment basis is provided for emotion prediction.
The functional description of the emotion recognition system provided by the embodiment of the invention refers to the description of the emotion recognition method in the above embodiment in detail.
An embodiment of the present invention further provides a storage medium, as shown in fig. 3, on which a computer program 601 is stored, where the instructions are executed by a processor to implement the steps of the emotion recognition method in the above-mentioned embodiment. The storage medium is also stored with audio and video stream data, characteristic frame data, an interactive request signaling, encrypted data, preset data size and the like. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD) or a Solid State Drive (SSD), etc.; the storage medium may also comprise a combination of memories of the kind described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.
Claims (10)
1. A method of emotion recognition, comprising the steps of:
extracting emotional characteristics of the human face according to externally input video stream information to obtain a vibration image;
performing pixel microseismic analysis according to the vibration image to form a vibration light ring;
and recognizing the emotional state according to the vibration halo.
2. The emotion recognition method of claim 1,
extracting the emotion characteristics of the human face according to the video stream information to obtain a vibration image, wherein the vibration image comprises the following steps:
acquiring video stream information of a tested person;
acquiring the amplitude and vibration frequency of each pixel point on the face of the detected person according to the video stream information;
and determining a vibration image according to the vibration frequency and the vibration amplitude.
3. The emotion recognition method according to claim 2,
carrying out pixel microseismic analysis according to the vibration image to form a vibration halo, comprising:
determining a vibration color level according to the vibration range of the vibration frequency of each pixel point of the vibration image;
determining the size of the vibration halo according to the average amplitude of the vibration image within a preset range;
and obtaining the vibration halo according to the vibration color level and the vibration halo.
4. The emotion recognition method according to claim 1, further comprising:
generating an emotion analysis report according to the emotion state recognition result, wherein the emotion analysis report comprises: a comprehensive emotion analysis result table and a emotion-energy change chart.
5. The emotion recognition method according to claim 1, further comprising:
and sending an emotion early warning signal according to the emotion state recognition result.
6. An emotion recognition system, comprising:
the camera is used for acquiring video stream information of a tested person;
a microprocessor, comprising:
the characteristic extraction module is used for extracting the emotion characteristics of the human face according to externally input video stream information to obtain a vibration image;
the analysis module is used for carrying out pixel microseismic analysis according to the vibration image to form a vibration light ring;
and the identification module is used for carrying out emotion state identification according to the vibration halo.
7. The emotion recognition system of claim 6,
the feature extraction module includes:
the vibration parameter acquisition module is used for acquiring the amplitude and the vibration frequency of each pixel point on the face of the detected person according to the video stream information;
and the vibration image determining module is used for determining a vibration image according to the vibration frequency and the vibration amplitude.
8. The emotion recognition system of claim 6,
the analysis module comprises:
the vibration color gradation determining module is used for determining a vibration color gradation according to the vibration range of the vibration frequency of each pixel point of the vibration image;
the halo size determining module is used for determining the size of the vibration halo according to the average amplitude of the vibration image within a preset range;
and the light ring determining module is used for obtaining the vibration light ring according to the vibration color level and the vibration light ring size.
9. The emotion recognition system of claim 6, wherein the microprocessor further comprises:
a report generation module, configured to generate an emotion analysis report according to the emotion state recognition result, where the emotion analysis report includes: a comprehensive emotion analysis result table and an emotion-energy change chart;
and the result sending module is used for sending the emotion early warning signal according to the emotion state recognition result.
10. A computer-readable storage medium storing computer instructions for causing a computer to perform the emotion recognition method according to any one of claims 1 to 5.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20150117614A (en) * | 2014-04-10 | 2015-10-20 | 주식회사 바이브라시스템 | A Method for Emotional classification using vibraimage technology |
| RU2017109920A3 (en) * | 2017-03-24 | 2018-09-24 | ||
| CN111631735A (en) * | 2020-04-26 | 2020-09-08 | 华东师范大学 | Abnormal emotion monitoring and early warning method based on video data vibration frequency |
| CN112957042A (en) * | 2021-01-29 | 2021-06-15 | 特路（北京）科技有限公司 | Non-contact target emotion recognition method and system |
-
2021
- 2021-09-28 CN CN202111147949.0A patent/CN113837128A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20150117614A (en) * | 2014-04-10 | 2015-10-20 | 주식회사 바이브라시스템 | A Method for Emotional classification using vibraimage technology |
| RU2017109920A3 (en) * | 2017-03-24 | 2018-09-24 | ||
| US20200085362A1 (en) * | 2017-03-24 | 2020-03-19 | Obshchestvo S Ogranichennoj Otvetstvennost`Yu "Mnogoprofilnoe Predpriyatie "Elsys" | Method of evaluating a psychophysiological state of a person |
| CN111631735A (en) * | 2020-04-26 | 2020-09-08 | 华东师范大学 | Abnormal emotion monitoring and early warning method based on video data vibration frequency |
| CN112957042A (en) * | 2021-01-29 | 2021-06-15 | 特路（北京）科技有限公司 | Non-contact target emotion recognition method and system |
Non-Patent Citations (1)
| Title |
|---|
| VIKTOR MINKIN: "Vibraimage", pages: 1 - 100 * |
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