CN114253612B - Control method and control system - Google Patents
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- CN114253612B CN114253612B CN202111410583.1A CN202111410583A CN114253612B CN 114253612 B CN114253612 B CN 114253612B CN 202111410583 A CN202111410583 A CN 202111410583A CN 114253612 B CN114253612 B CN 114253612B
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/4401—Bootstrapping
- G06F9/4418—Suspend and resume; Hibernate and awake
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- G06F18/22—Matching criteria, e.g. proximity measures
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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Abstract
The invention provides a control method for controlling the awakening of electronic equipment, which comprises the steps of acquiring video stream data, then carrying out face detection on the video stream data to obtain a face frame, carrying out face recognition on images in the face frame to determine the matching degree of the images in the face frame and preset user images, starting voice recognition when the matching degree of the images in the face frame and the preset user images reaches a preset threshold value, judging whether to control the electronic equipment to awaken, timely controlling the electronic equipment to awaken in a video stream mode, improving the starting speed of the electronic equipment, and improving the safety of the electronic equipment when the electronic equipment is started in a mode of combining face recognition and voice recognition. The invention also provides a control system for realizing the control method.
Description
Technical Field
The present invention relates to the field of control systems, and in particular, to a control method and a control system.
Background
At present, the electronic equipment needs to be manually awakened before and after the operator arrives at the front of the electronic equipment, so that the operator cannot immediately use the electronic equipment, and the electronic equipment is inconvenient for the operator to use.
Therefore, it is necessary to provide a novel control method and control system to solve the above-mentioned problems in the prior art.
Disclosure of Invention
The invention aims to provide a control method and a control system which are convenient for automatically controlling the awakening of electronic equipment, improving the starting speed of the electronic equipment and improving the safety of the electronic equipment during starting.
In order to achieve the above object, the control method of the present invention is used for controlling the wake-up of an electronic device, and includes the following steps:
s1: acquiring video stream data, and then performing face detection on the video stream data to obtain a face frame;
S2: performing face recognition on the images in the face frame to determine the matching degree of the images in the face frame and the preset user image;
S3: and when the matching degree of the image in the face frame and the preset user image reaches a preset threshold, starting voice recognition to judge whether to control the electronic equipment to wake up.
The control method has the beneficial effects that: and when the matching degree of the image in the face frame and the preset user image reaches a preset threshold value, voice recognition is started to judge whether to control the electronic equipment to wake up, the electronic equipment is timely controlled to wake up in a video stream mode, the starting speed of the electronic equipment is improved, and the safety of the electronic equipment during starting is improved in a mode of combining face recognition and voice recognition.
Optionally, before executing the step S2, a first face frame comparing step is further included, where the first face frame comparing step includes:
comparing the face frame with a first preset face frame to judge whether the face frame is larger than the first preset face frame or not;
And if the face frame is judged to be larger than the first preset face frame, executing the step S2. The beneficial effects are that: as the starting condition of face recognition, useless face recognition is avoided, and the face recognition efficiency is improved.
Optionally, before executing the step S2, a frame counting step is further included, where the frame counting step includes:
If the face frame is judged to be smaller than or equal to a first preset face frame, adding 1 to the frame count to obtain a new frame count, and then replacing the frame count with the new frame count;
Comparing the new frame count with a preset frame count to determine whether the new frame count is greater than the preset frame count;
and if the new frame count is judged to be larger than the preset frame count, obtaining the movement trend of the target according to the change trend of the face frame.
Optionally, before executing the step S2, a second face frame comparing step is further included, where the second face frame comparing step includes:
judging whether the movement trend of the target is close to the electronic equipment or not;
If the motion trend of the target is judged to be close to the electronic equipment, comparing the latest obtained face frame with a second preset face frame to judge whether the latest obtained face frame is larger than the second preset face frame or not;
and if the latest obtained face frame is judged to be larger than a second preset face frame, executing the step S2. The beneficial effects are that: as the starting condition of the face recognition, useless face recognition is avoided, the face recognition efficiency is improved, and the fact that the face recognition cannot be started for a long time can be avoided.
Optionally, the acquiring video stream data and then performing face detection on the video stream data to obtain a face frame includes:
And acquiring each frame of image in the video stream data, and then carrying out face detection on each frame of image according to the sequence of each frame of image in the video stream data so as to obtain a face frame.
Optionally, if face detection is performed on the image of the same frame to obtain at least two face frames, only the face frame closest to the center point of the image is obtained. The beneficial effects are that: and acquiring a unique face frame, and ensuring the correct processing of the subsequent process.
Optionally, the starting the voice recognition to determine whether to control the electronic device to wake up includes:
Collecting sound information, and comparing the sound information with pre-stored sound information to judge whether the sound information is matched with the pre-stored sound information or not;
and if the sound information is judged to be matched with the pre-stored sound information, controlling the electronic equipment to wake up.
The invention also provides a control system, which comprises a video stream data acquisition unit, a face detection unit, a face recognition unit, a voice recognition unit and a wake-up unit, wherein the video stream data acquisition unit is used for acquiring video stream data; the face detection unit is used for receiving the video stream data acquired by the video stream data acquisition unit, and then carrying out face detection on the video stream data to acquire a face frame; the face recognition unit is used for recognizing the images in the face frame to determine the matching degree of the images in the face frame and the preset user images, and after the matching degree of the images in the face frame and the preset user images reaches a preset threshold, voice recognition is started to judge whether to control the electronic equipment to wake up; the wake-up unit is used for waking up the electronic equipment.
The control system has the beneficial effects that: the video stream data acquisition unit is used for acquiring video stream data; the face detection unit is used for receiving the video stream data acquired by the video stream data acquisition unit, then carrying out face detection on the video stream data to obtain a face frame, the face recognition unit is used for carrying out face recognition on images in the face frame to determine the matching degree of the images in the face frame and preset user images, and after the matching degree of the images in the face frame and the preset user images reaches a preset threshold value, voice recognition is started to judge whether to control the electronic equipment to wake up, the wake-up unit is used for waking up the electronic equipment, the electronic equipment is timely controlled to wake up in a video stream mode, the starting speed of the electronic equipment is improved, and the safety of the electronic equipment during starting is improved in a mode of combining face recognition and voice recognition.
Optionally, the control system further includes a first face frame comparing unit, where the first face frame comparing unit is configured to compare the face frame with a first preset face frame, so as to determine whether the face frame is greater than the first preset face frame.
Optionally, the control system further comprises a frame counting unit for adding 1 to the frame count to obtain a new frame count, and then replacing the frame count with the new frame count.
Optionally, the control system further includes a frame count comparing unit, where the frame count comparing unit is configured to determine whether the new frame count is greater than a preset frame count, and if it is determined that the new frame count is greater than the preset frame count, obtain a movement trend of the target according to a change trend of the face frame.
Optionally, the control system further includes a second face frame comparing unit, where the second face frame comparing unit is configured to determine whether the motion trend of the target is close to the electronic device, and if it is determined that the motion trend of the target is close to the electronic device, compare the newly obtained face frame with a second preset face frame, so as to determine whether the newly obtained face frame is greater than the second preset face frame.
Drawings
FIG. 1 is a block diagram of a control system of the present invention;
FIG. 2 is a flow chart of a control method of the present invention;
fig. 3 is a schematic diagram showing two face frames appearing in one frame image according to the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention. Unless otherwise defined, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs. As used herein, the word "comprising" and the like means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof without precluding other elements or items.
In view of the problems existing in the prior art, an embodiment of the present invention provides a control system, referring to fig. 1, the control system 100 includes a video stream data obtaining unit 101, a face detection unit 102, a face recognition unit 103, a voice recognition unit 104, and a wake-up unit 105, where the video stream data obtaining unit 101 is configured to obtain video stream data; the face detection unit 102 is configured to receive the video stream data acquired by the video stream data acquisition unit 101, and then perform face detection on the video stream data to obtain a face frame; the face recognition unit 103 is configured to perform face recognition on the image in the face frame to determine a matching degree between the image in the face frame and a preset user image, and start speech recognition after the matching degree between the image in the face frame and the preset user image reaches a preset threshold value, so as to determine whether to control the electronic device to wake up; the wake-up unit 105 is configured to wake up an electronic device.
In some embodiments, the control system may further include a first face frame comparing unit, where the first face frame comparing unit is configured to compare the face frame with a first preset face frame to determine whether the face frame is greater than the first preset face frame.
In some embodiments, the control system may further include a frame count unit for adding n to the frame count to obtain a new frame count, and then replacing the frame count with the new frame count, where n is greater than 0.
In some embodiments, the control system may further include a frame count comparing unit, where the frame count comparing unit is configured to determine whether the new frame count is greater than a preset frame count, and if it is determined that the new frame count is greater than the preset frame count, obtain a movement trend of the target according to a change trend of the face frame.
In some embodiments, the control system may further include a second face frame comparing unit, where the second face frame comparing unit is configured to determine whether the movement trend of the target is close to the electronic device, and if it is determined that the movement trend of the target is close to the electronic device, compare the latest obtained face frame with a second preset face frame, so as to determine whether the latest obtained face frame is greater than the second preset face frame.
In some embodiments, the control system may further include a frame count selection unit for selecting or inputting a preset frame count.
FIG. 2 is a flow chart of a control method according to some embodiments of the invention. Referring to fig. 2, the control method is implemented by the control system and is used for controlling the wake-up of the electronic device, and the control method includes the following steps:
s1: acquiring video stream data, and then performing face detection on the video stream data to obtain a face frame;
S2: performing face recognition on the images in the face frame to determine the matching degree of the images in the face frame and the preset user image;
S3: and when the matching degree of the image in the face frame and the preset user image reaches a preset threshold, starting voice recognition to judge whether to control the electronic equipment to wake up.
In some embodiments, the face detection and face recognition are performed through a trained neural network model, and the training method of the neural network model includes: collecting a custom data set, wherein the custom data set comprises a face picture; carrying out normalization pretreatment on the face picture in the RGB format; acquiring a self-defined training network model, wherein the self-defined training network model performs model compression based on YOLOV < 4 >; inputting the face picture subjected to normalization pretreatment into the custom training network model for training; obtaining training loss of the face picture through loss function calculation, carrying out back propagation on the training loss to update a training network model, and finishing training when the performance of the training network model on the verification set accords with a preset threshold value; and carrying out network pruning on the trained network model, and training all data in the network model after pruning for at least ten times to obtain a trained neural network model for face detection or face recognition. The face detection and face recognition may also be performed by other methods, and the methods of face detection and face recognition are not particularly limited herein.
In some embodiments, the step S2 may be further performed before the step S2 is performed, where the step of comparing a first face frame includes: comparing the face frame with a first preset face frame to judge whether the face frame is larger than the first preset face frame or not; and if the face frame is judged to be larger than the first preset face frame, executing the step S2.
In some embodiments, the step S2 may be further performed before the step S2 is performed, where the step of counting frames includes: if the face frame is judged to be smaller than or equal to a first preset face frame, adding 1 to the frame count to obtain a new frame count, and then replacing the frame count with the new frame count; comparing the new frame count with a preset frame count to determine whether the new frame count is greater than the preset frame count; and if the new frame count is judged to be larger than the preset frame count, obtaining the movement trend of the target according to the change trend of the face frame.
In some embodiments, taking a frame count of 1, a length of the first preset face frame of 6, and a height of the first preset face frame of 7 as examples:
Four vertex coordinates of a face frame in a ninth frame image of the video stream data are (10, 11), (15, 11), (10, 6) and (15, 6) respectively, four vertex coordinates of a face frame in a tenth frame image of the video stream data are (9.75, 11.25), (15.25, 11.25), (9.75,5.75) and (15.25,5.75) respectively, four vertex coordinates of a face frame in an eleventh frame image of the video stream data are (9.5, 11.5), (15.5, 11.5), (9.5,5.5) and (15.5,5.5) respectively, namely the length of a face frame in the ninth image is 5, the height of a face frame in the ninth image is 5, the length of a face frame in the tenth frame image of the video stream data is 5.5, the height of a face frame in the tenth frame image of the video stream data is 5.5, the length of a face frame in the eleventh frame image of the video stream data is 6, and the height of a face frame in the eleventh frame image of the video stream data is 6;
Judging that the length of a face frame in the ninth frame image is smaller than that of the first preset face frame, judging that the height of the face frame in the ninth frame image is smaller than that of the first preset face frame, judging that the face frame in the ninth frame image is smaller than that of the first preset face frame, wherein the frame count is 1, and after adding 1, the frame count is 2, namely, a new frame count is 2, then replacing the frame count with the new frame count, and the frame count is also 2;
judging that the length of a face frame in the tenth frame image is smaller than that of the first preset face frame, judging that the height of the face frame in the tenth frame image is smaller than that of the first preset face frame, judging that the face frame in the tenth frame image is smaller than that of the first preset face frame, wherein the frame count is 2, and after 1 is added, the frame count is 3, namely, a new frame count is 3, then replacing the frame count with the new frame count, and the frame count is also 3;
Judging that the length of the face frame in the eleventh frame image is equal to the length of the first preset face frame, judging that the height of the face frame in the eleventh frame image is smaller than the height of the first preset face frame, judging that the face frame in the eleventh frame image is smaller than the first preset face frame, wherein the frame count is 3, and after adding 1, the frame count is equal to 4, namely, the new frame count is 4, then replacing the frame count with the new frame count, and the frame count is also 4.
In some embodiments, a second face frame comparing step may be further included before the step S2 is performed, where the second face frame comparing step includes: judging whether the movement trend of the target is close to the electronic equipment or not; if the motion trend of the target is judged to be close to the electronic equipment, comparing the latest obtained face frame with a second preset face frame to judge whether the latest obtained face frame is larger than the second preset face frame or not; and if the latest obtained face frame is judged to be larger than a second preset face frame, executing the step S2.
In some embodiments, the obtaining the movement trend of the target according to the change trend of the face frame includes: sequentially comparing the sizes of the adjacent face frames according to the acquisition sequence of the face frames; multiplying a first calculated value by a first amplification threshold or a first reduction threshold according to a comparison result of the sizes of the adjacent face frames to obtain a new first calculated value, and then replacing the first calculated value with the new first calculated value; and comparing the new first calculated value with a first judgment threshold value to obtain the change trend of the face frame, and further obtaining the target movement trend. Wherein the first calculated value is greater than 0.
In some embodiments, the first magnification threshold is greater than 1 and less than 2, the first reduction threshold is less than 1 and greater than 0, and the sum of the first magnification threshold and the first reduction threshold is 2. For example, the first magnification threshold is 1.2, and the first reduction threshold is 0.8; for another example, the first enlargement threshold is 1.1 and the first reduction threshold is 0.9.
In some embodiments, comparing the new first calculated value with a first judgment threshold value to obtain a variation trend of the face frame, and further obtaining a target movement trend, including: comparing the new first calculated value with a first judgment threshold value to obtain the change trend of the face frame; if the new first calculated value is larger than the first judgment threshold value, judging that the change trend of the face frame is larger and larger, and further obtaining that the target movement trend is close to the electronic equipment; if the new first calculated value is smaller than the first judgment threshold value, judging that the change trend of the face frame is smaller and smaller, and further obtaining that the target movement trend is far away from the electronic equipment.
In some embodiments, the first decision threshold is equal to the first calculated value.
In some embodiments, the method further includes a frame count selecting step before performing step S1, where the frame count selecting step includes: a preset frame count is selected or entered.
In some embodiments, the obtaining video stream data and then performing face detection on the video stream data to obtain a face frame includes: and acquiring each frame of image in the video stream data, and then carrying out face detection on each frame of image according to the sequence of each frame of image in the video stream data so as to obtain a face frame.
In some embodiments, if face detection is performed on the image of the same frame to obtain at least two face frames, only the face frame closest to the center point of the image is obtained.
Fig. 3 is a schematic diagram showing two face frames appearing in one frame image according to the present invention. Referring to fig. 3, the image includes a center point 201 of the image, a left face frame 202 and a right face frame 203, the center point 201 is an intersection point of diagonal lines of the image, a distance between the left face frame 202 and the center point 201 is smaller than a distance between the right face frame 203 and the center point 201, and only the left face frame 202 is acquired when acquiring the face frames in the image.
In some embodiments, the initiating speech recognition to determine whether to control the electronic device to wake up includes: collecting sound information, and comparing the sound information with pre-stored sound information to judge whether the sound information is matched with the pre-stored sound information or not; and if the sound information is judged to be matched with the pre-stored sound information, controlling the electronic equipment to wake up. For example, the pre-stored sound information is "hello computer", if the collected sound information is "hello computer", the sound information is judged to be matched with the pre-stored sound information, and the electronic equipment is controlled to wake up; for another example, the pre-stored sound information is "hello computer", if the collected sound information is "hello computer", the sound information is judged to be matched with the pre-stored sound information, the electronic device is not controlled to wake up, and the sound information is continuously collected.
In some embodiments, the initiating speech recognition to determine whether to control the electronic device to wake up may further include: starting timing while starting voice recognition, and if the timing exceeds the preset time, not controlling the electronic equipment to wake up, emptying all the acquired face frames and re-executing the step S1.
While embodiments of the present invention have been described in detail hereinabove, it will be apparent to those skilled in the art that various modifications and variations can be made to these embodiments. It is to be understood that such modifications and variations are within the scope and spirit of the present invention as set forth in the following claims. Moreover, the invention described herein is capable of other embodiments and of being practiced or of being carried out in various ways.
Claims (12)
1. A control method for controlling wake-up of an electronic device, comprising the steps of:
S1: acquiring video stream data, and then performing face detection on the video stream data to obtain a face frame; s2: sequentially comparing the sizes of the adjacent face frames according to the acquisition sequence of the face frames; multiplying a first calculated value by a first amplification threshold or a first reduction threshold according to a comparison result of the sizes of the adjacent face frames to obtain a new first calculated value, and then replacing the first calculated value with the new first calculated value; comparing the new first calculated value with a first judgment threshold value to obtain a change trend of a face frame, and further obtaining a target movement trend, wherein the first calculated value is larger than 0;
If the new first calculated value is larger than the first judgment threshold value, judging that the change trend of the face frame is larger and larger, and further obtaining that the target movement trend is close to the electronic equipment; if the new first calculated value is smaller than the first judgment threshold value, judging that the change trend of the face frame is smaller and smaller, and further obtaining that the target movement trend is far away from the electronic equipment;
performing face recognition on the images in the face frame to determine the matching degree of the images in the face frame and the preset user image; s3: when the matching degree of the image in the face frame and the preset user image reaches a preset threshold, starting voice recognition to judge whether to control the electronic equipment to wake up; starting timing while starting voice recognition, and if the timing exceeds the preset time, not controlling the electronic equipment to wake up, emptying all the acquired face frames and re-executing the step S1.
2. The control method according to claim 1, characterized in that the step S2 is performed further comprising a first face box comparison step, the first face box comparison step comprising:
comparing the face frame with a first preset face frame to judge whether the face frame is larger than the first preset face frame or not;
and if the face frame is judged to be larger than the first preset face frame, executing the step S2.
3. The control method according to claim 2, characterized by further comprising a frame counting step before performing said step S2, said frame counting step comprising:
If the face frame is judged to be smaller than or equal to a first preset face frame, adding 1 to the frame count to obtain a new frame count, and then replacing the frame count with the new frame count;
Comparing the new frame count with a preset frame count to determine whether the new frame count is greater than the preset frame count;
and if the new frame count is judged to be larger than the preset frame count, obtaining the movement trend of the target according to the change trend of the face frame.
4. A control method according to claim 3, further comprising a second face box comparison step prior to performing step S2, the second face box comparison step comprising:
judging whether the movement trend of the target is close to the electronic equipment or not;
If the motion trend of the target is judged to be close to the electronic equipment, comparing the latest obtained face frame with a second preset face frame to judge whether the latest obtained face frame is larger than the second preset face frame or not;
And if the latest obtained face frame is judged to be larger than a second preset face frame, executing the step S2.
5. The control method according to claim 1, wherein the acquiring video stream data and then performing face detection on the video stream data to obtain a face frame includes:
And acquiring each frame of image in the video stream data, and then carrying out face detection on each frame of image according to the sequence of each frame of image in the video stream data so as to obtain a face frame.
6. The control method according to claim 5, wherein if face detection is performed on the image of the same frame to obtain at least two face frames, only the face frame closest to the center point of the image is acquired.
7. The control method according to claim 1, wherein the enabling speech recognition to determine whether to control the electronic device to wake up comprises:
Collecting sound information, and comparing the sound information with pre-stored sound information to judge whether the sound information is matched with the pre-stored sound information or not;
and if the sound information is judged to be matched with the pre-stored sound information, controlling the electronic equipment to wake up.
8. A control system for implementing the control method according to any one of claims 1 to 7, the control system comprising a video stream data acquisition unit, a face detection unit, a face recognition unit, a voice recognition unit, and a wake-up unit, wherein the video stream data acquisition unit is configured to acquire video stream data; the face detection unit is used for receiving the video stream data acquired by the video stream data acquisition unit, and then carrying out face detection on the video stream data to acquire a face frame; the face recognition unit is used for recognizing the images in the face frame to determine the matching degree of the images in the face frame and the preset user images, and after the matching degree of the images in the face frame and the preset user images reaches a preset threshold, voice recognition is started to judge whether to control the electronic equipment to wake up; the wake-up unit is used for waking up the electronic equipment.
9. The control system of claim 8, further comprising a first face frame comparison unit configured to compare the face frame with a first preset face frame to determine whether the face frame is greater than the first preset face frame.
10. The control system of claim 9, further comprising a frame count unit for incrementing a frame count by 1 to obtain a new frame count, and then replacing the frame count with the new frame count.
11. The control system according to claim 10, further comprising a frame count comparing unit configured to determine whether the new frame count is greater than a preset frame count, and if the new frame count is determined to be greater than the preset frame count, obtain a movement trend of the target according to a change trend of the face frame.
12. The control system according to claim 11, further comprising a second face frame comparing unit, wherein the second face frame comparing unit is configured to determine whether the movement trend of the target is close to the electronic device, and if the movement trend of the target is determined to be close to the electronic device, compare the latest obtained face frame with a second preset face frame to determine whether the latest obtained face frame is greater than the second preset face frame.
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| CN109976506A (en) * | 2017-12-28 | 2019-07-05 | 深圳市优必选科技有限公司 | Awakening method of electronic equipment, storage medium and robot |
| CN108876998A (en) * | 2018-06-13 | 2018-11-23 | 上海快鱼电子有限公司 | Gate inhibition's method and system of testimony of a witness unification based on living things feature recognition |
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