CN112232287A - Face recognition method and device - Google Patents
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- CN112232287A CN112232287A CN202011229319.3A CN202011229319A CN112232287A CN 112232287 A CN112232287 A CN 112232287A CN 202011229319 A CN202011229319 A CN 202011229319A CN 112232287 A CN112232287 A CN 112232287A
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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Abstract
The invention discloses a face recognition method and a face recognition device, wherein the face recognition method comprises the following steps: controlling a shooting device to circularly acquire a face picture and send the face picture into a message queue, and circularly taking the face picture from the message queue for processing through a picture processing thread; judging whether the number of the face pictures in the message queue reaches a preset threshold value or not; and if the number of the face pictures reaches a preset threshold value, discarding new face pictures circularly acquired by the shooting device. The new face pictures circularly acquired by the shooting device are abandoned after the message queue reaches the preset threshold value, so that the face pictures can be processed in time when a large program or an algorithm with large calculation amount runs on the equipment.
Description
Technical Field
The invention belongs to the field of face recognition, and particularly relates to a face recognition method and device.
Background
Face recognition is a biometric technology for identity recognition based on facial feature information of a person. A series of related technologies, also commonly called face recognition and face recognition, are used to collect images or video streams containing faces by using a camera or a video camera, automatically detect and track the faces in the images, and then perform face recognition on the detected faces.
The research of the face recognition system starts in the 60 s of the 20 th century, the development of the computer technology and the optical imaging technology is improved after the 80 s, and the research really enters the early application stage in the later 90 s and mainly realizes the technology of the United states, Germany and Japan; the key to the success of the face recognition system is whether the face recognition system has a core algorithm with a sharp end or not, and the recognition result has practical recognition rate and recognition speed; the human face recognition system integrates various professional technologies such as artificial intelligence, machine recognition, machine learning, model theory, expert system and video image processing, and meanwhile, the theory and implementation of intermediate value processing need to be combined, so that the human face recognition system is the latest application of biological feature recognition, the core technology of the human face recognition system is implemented, and the conversion from weak artificial intelligence to strong artificial intelligence is shown.
The traditional face recognition technology is mainly based on face recognition of visible light images, which is a familiar recognition mode, and has been developed for over 30 years. However, this method has a defect that it is difficult to overcome, and especially when the ambient light changes, the recognition effect will be rapidly reduced, which cannot meet the needs of the actual system. The scheme for solving the illumination problem comprises three-dimensional image face recognition and thermal imaging face recognition. However, the two technologies are still far from mature and the recognition effect is not satisfactory.
One solution that has rapidly developed is a multi-light source face recognition technique based on active near-infrared images. The method can overcome the influence of light change, has excellent recognition performance, and has overall system performance exceeding that of three-dimensional image face recognition in the aspects of precision, stability and speed. The technology is rapidly developed in two or three years, and the face recognition technology gradually becomes practical.
The human face is inherent like other biological characteristics (fingerprints, irises and the like) of a human body, the uniqueness and the good characteristic that the human face is not easy to copy provide necessary premise for identity identification, and compared with other types of biological identification, the human face identification has the following characteristics:
optional characteristics: the user does not need to be specially matched with face acquisition equipment, and can almost acquire a face image in an unconscious state, and the sampling mode is not mandatory;
non-contact property: the user can obtain the face image without directly contacting with the equipment;
concurrency: the method can be used for sorting, judging and identifying a plurality of faces in an actual application scene;
in addition, the visual characteristics are also met: the characteristic of 'people can be identified by the appearance', and the characteristics of simple operation, visual result, good concealment and the like.
In the related art, Face + + is a commonly used technical scheme in the field of Face recognition, and an inventor discovers that: sdk for Face + + sets the detection interval. The detection time interval of Face + + setting is similar to the original sdk setting, and is an external setting which is a time interval or sampling interval and is used for setting how many pictures are processed per second.
Disclosure of Invention
An embodiment of the present invention provides a face recognition method and apparatus, which are used to solve at least one of the above technical problems.
In a first aspect, an embodiment of the present invention provides a face recognition method, including: controlling a shooting device to circularly acquire a face picture and send the face picture into a message queue, and circularly taking the face picture from the message queue for processing through a picture processing thread; judging whether the number of the face pictures in the message queue reaches a preset threshold value or not; and if the number of the face pictures reaches a preset threshold value, discarding new face pictures circularly acquired by the shooting device.
In a second aspect, an embodiment of the present invention provides a face recognition apparatus, including: the control acquisition processing module is configured to control the shooting device to circularly acquire the face pictures and send the face pictures into a message queue, and the face pictures are circularly taken from the message queue for processing through a picture processing thread; the judging module is configured to judge whether the number of the face pictures in the message queue reaches a preset threshold value; and the first discarding module is configured to discard the new face pictures circularly acquired by the shooting device if the number of the face pictures reaches a preset threshold value.
In a third aspect, there is provided a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the steps of the face recognition method of the first aspect.
In a fourth aspect, an embodiment of the present invention further provides an electronic device, which includes: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of the method of the first aspect.
According to the method provided by the embodiment of the application, the new face picture circularly acquired by the shooting device is abandoned after the message queue reaches the preset threshold value, so that the face picture can be timely processed when a large program or an algorithm with large calculation amount runs on the equipment.
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 description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a flowchart of a face recognition method according to an embodiment of the present invention;
fig. 2 is a flowchart of another face recognition method according to an embodiment of the present invention;
fig. 3 is a flow chart of face recognition according to a specific embodiment of the face recognition scheme of the embodiment of the present invention;
fig. 4 is a block diagram of a face recognition apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to 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.
Referring to fig. 1, a flowchart of an embodiment of a face recognition method according to the invention is shown.
As shown in fig. 1, in step 101, a shooting device is controlled to circularly acquire a face picture and send the face picture into a message queue, and the face picture is circularly taken from the message queue for processing through a picture processing thread;
in step 102, judging whether the number of the face pictures in the message queue reaches a preset threshold value;
in step 103, if the number of the face pictures reaches a preset threshold, discarding new face pictures circularly acquired by the shooting device.
In this embodiment, for step 101, the face recognition apparatus, in response to the face recognition instruction, controls the shooting apparatus to cyclically collect a face picture and send the face picture to the message queue, and cyclically takes the face picture from the message queue via the picture processing thread to process the face picture, for example, cyclically obtains the face picture from the shooting apparatus, and sends the face picture to a message queue, and then the thread processing the face picture cyclically obtains the face picture from the message queue to perform face recognition processing, for example, it can be quickly determined whether the face picture shot by the shooting apparatus and a preset face picture are greater than a preset threshold, for example, processing the face picture includes: the processing procedures of face image acquisition, face detection, face image preprocessing, face image feature extraction, face image matching and identification and the like are not repeated herein.
Then, for step 102, the face recognition device determines whether the number of face pictures in the message queue reaches a preset threshold, for example, a speed of acquiring a face picture and a speed of processing the face picture are preset, the acquired face pictures are put into a message queue, a processing thread acquires the face pictures from the message queue for processing, when the face recognition device is busy, the preset number of face pictures may not be processed, for example, when the preset threshold of the message queue is 2, it can be understood that the processing speed can be determined as a normal processing speed when the number of face pictures in the message queue is less than 2, and when the number of face pictures in the message queue reaches 2, it can be determined that the processing thread is abnormal, and the device is likely to be busy.
Finally, in step 103, if the number of the face pictures reaches the preset threshold, discarding the new face pictures circularly acquired by the shooting device, for example, if the face pictures in the message queue reach the preset threshold, it may indicate that the face picture processing thread cannot process the new face pictures, and discard the new face pictures circularly acquired by the shooting device.
In the scheme of this embodiment, the new face picture cyclically acquired by the photographing device is discarded after the message queue reaches the preset threshold, so that the face picture can be processed in time when some large programs or algorithms with large calculation amount are run on the device.
In the method according to the above embodiment, after the determining whether the number of the face pictures in the message queue reaches a preset threshold, the method further includes:
and if the number of the face pictures does not reach a preset threshold value, continuously sending the face pictures circularly acquired from the shooting device into the message list.
Please refer to fig. 2, which shows a flowchart of another face recognition method according to an embodiment of the present invention, and the flowchart mainly refers to a flowchart of steps further defined after the method of "responding to a face recognition instruction, circularly acquiring a face picture by a shooting device and sending the face picture into a message queue, and circularly acquiring the face picture from the message queue for processing by a picture processing thread" in embodiment 101.
As shown in fig. 2, in step 201, the face pictures in the message queue are obtained to be processed circularly, the utilization rate of a central processing unit is obtained, and whether the utilization rate of the central processing unit is greater than a preset utilization rate threshold is judged;
in step 202, if the usage rate is greater than the preset threshold, discarding the new face pictures circularly acquired by the shooting device.
In this embodiment, for step 201, the face recognition device obtains the face pictures in the message queue to perform loop processing and obtain the utilization rate of the central processing unit, and determines whether the utilization rate of the central processing unit is greater than a preset utilization rate threshold, for example, it may be preset that the device is in a normal state when the utilization rate of the central processing unit does not reach 80%, and the face pictures can be processed normally, or it may be determined that the device is in a busy state when the utilization rate of the central processing unit reaches 80%, and the face pictures cannot be processed effectively.
Then, for step 202, if the usage rate is greater than the preset threshold, discarding the new face picture circularly acquired by the shooting device, for example, when the usage rate of the central processing unit reaches the preset threshold, it may indicate that the device is busy, and the face picture is not processed timely and accurately enough, and may discard the new face picture circularly acquired by the shooting device, for example, when the usage rate of the central processing unit is determined, the message list may also be discarded, and the usage rate of the central processing unit is directly determined, and the face picture processing thread is directly circularly acquired from the shooting device.
In the scheme of this embodiment, the new face picture circularly acquired by the shooting device is discarded after the utilization rate of the central processing unit reaches the preset threshold value, so that the face picture can be processed in time when some large programs or algorithms with large calculation amount are run on the equipment.
In the method according to the above embodiment, the determining whether the usage rate of the central processing unit is greater than a preset usage rate threshold further includes:
and if the utilization rate of the central processing unit is not greater than a preset utilization rate threshold value, continuously sending the user pictures circularly acquired from the shooting device into the message list.
In the method according to any of the above embodiments, if the number of the face pictures reaches the preset threshold, discarding new face pictures that are cyclically acquired by the photographing device includes:
and if the number of the face pictures reaches a preset threshold value, informing the shooting device not to collect new face pictures.
In the method according to the above embodiment, after controlling the photographing device to not collect a new face picture if the number of the face pictures reaches a preset threshold, the method further includes:
and if the number of the face pictures in the message queue does not reach a preset threshold value, continuously acquiring new face pictures through the shooting device and sending the new face pictures into the message queue until the number of the face pictures in the message queue does not reach the preset threshold value.
For example, if the number of face pictures in the message queue reaches the preset threshold, discarding new face pictures circularly acquired by the shooting device, judging whether the message queue reaches the preset threshold again, and if not, continuing to acquire new face pictures through the shooting device and sending the new face pictures into the message queue until the number of face pictures in the message queue does not reach the preset threshold.
It should be noted that, although the above embodiments adopt numbers with definite precedence order such as step 101 and step 102 to define the precedence order of the steps, in an actual application scenario, some steps may be executed in parallel, and the precedence order of some steps is also not defined by the numbers, and this application is not limited herein and is not described herein again.
The following description is provided to enable those skilled in the art to better understand the present disclosure by describing some of the problems encountered by the inventors in implementing the present disclosure and by describing one particular embodiment of the finally identified solution.
The inventors discovered the defects of these similar techniques in the process of implementing the present invention:
the cpu of the device is dynamically used, and the fixed number of processed pictures may not be guaranteed to be processed in time when the device is busy.
The inventors have found in the course of carrying out the invention why the reason is not easily imaginable:
the number of pictures processed per second is set to be fixed, and the set number of pictures may not be processed when the device is actually running busy.
Sdk is a general solution that can also be dynamically taken by sdk users from the outside, which requires sdk users to develop themselves.
The invention has the technical innovation points that:
the pictures to be processed are put in a queue, the pictures are circularly taken from the queue for processing, if more than 1 picture (not containing 1 picture) remains in the queue, the pictures are considered to be processed and the pictures to be put in are discarded.
1. Incoming pictures are placed in a message queue.
2. The thread processing the picture circularly acquires the picture from the message queue.
3. When more than 1 picture in the message queue is not processed, the picture is not processed in time, the picture cannot be put in the message queue again, and the picture is discarded. And if the number of the pictures in the message queue is less than or equal to 1, continuing to put the pictures in the message queue.
The next sampled picture is still processed according to the 1-3 flow.
The technical scheme of the application mainly solves the problem that under the condition that the cpu is insufficient, the vision sdk possibly processes the picture data to cause the picture data to be blocked.
The specific application scenario of the embodiment of the application is that when the visual program and other programs are run on Android devices such as a television, a tablet, a ticket vending machine and the like, if other programs suddenly consume more cpu resources, for example, the television is playing videos, the vision sdk cannot process picture data in time, and the solution can be used.
Beta version formed by the inventor in the process of implementing the invention:
and viewing the utilization rate of the cpu, and when the utilization rate is high, the number of image processing can be reduced. The accuracy of the scheme is not enough, and the cpu reaches 80% or 90% and considers that the number of the processed pictures is not timely reduced when the pictures are not processed, so that the accurate measurement cannot be realized.
The inventor finds that deeper effects are achieved in the process of implementing the invention:
when the scheme is used, a plurality of large programs or algorithms with large calculation amount are operated on the equipment, and the number of the observation pictures is dynamically reduced.
Referring to fig. 4, a block diagram of a face recognition apparatus according to an embodiment of the present invention is shown.
As shown in fig. 4, the control acquisition processing module 410, the determination module 420, and the first discard module 430.
The control acquisition processing module 410 is configured to control the shooting device to circularly acquire a face picture and send the face picture into a message queue, and circularly take the face picture from the message queue for processing through a picture processing thread; a determining module 420 configured to determine whether the number of the face pictures in the message queue reaches a preset threshold; the first discarding module 430 is configured to discard the new face pictures circularly acquired by the photographing device if the number of the face pictures reaches a preset threshold.
It should be understood that the modules depicted in fig. 4 correspond to various steps in the methods described with reference to fig. 1 and 2. Thus, the operations and features described above for the method and the corresponding technical effects are also applicable to the modules in fig. 4, and are not described again here.
It should be noted that the modules in the embodiments of the present application are not limited to the scheme of the present application, for example, the acquisition control processing module may be described as a module that controls the shooting device to cyclically acquire a face picture and send the face picture to a message queue, and cyclically acquire the face picture from the message queue via a picture processing thread to process the face picture.
In other embodiments, an embodiment of the present invention further provides a non-volatile computer storage medium, where the computer storage medium stores computer-executable instructions, and the computer-executable instructions may execute the face recognition method in any of the above method embodiments;
as one embodiment, a non-volatile computer storage medium of the present invention stores computer-executable instructions configured to:
controlling a shooting device to circularly acquire a face picture and send the face picture into a message queue, and circularly taking the face picture from the message queue for processing through a picture processing thread;
judging whether the number of the face pictures in the message queue reaches a preset threshold value or not;
and if the number of the face pictures reaches a preset threshold value, discarding new face pictures circularly acquired by the shooting device.
The non-volatile computer-readable storage medium may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the face recognition apparatus, and the like. Further, the non-volatile computer-readable storage medium may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the non-transitory computer readable storage medium optionally includes memory located remotely from the processor, which may be connected to the face recognition device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Embodiments of the present invention also provide a computer program product, which includes a computer program stored on a non-volatile computer-readable storage medium, where the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes any one of the above-mentioned face recognition methods.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 5, the electronic device includes: one or more processors 510 and memory 520, with one processor 510 being an example in fig. 5. The apparatus for the face recognition method may further include: an input device 530 and an output device 540. The processor 510, the memory 520, the input device 530, and the output device 540 may be connected by a bus or other means, and the bus connection is exemplified in fig. 5. The memory 520 is a non-volatile computer-readable storage medium as described above. The processor 510 executes various functional applications of the server and data processing by running nonvolatile software programs, instructions and modules stored in the memory 520, namely, implements the above method embodiments for the face recognition device method. The input device 530 may receive input numeric or character information and generate key signal inputs related to user settings and function control for the face recognition device. The output device 540 may include a display device such as a display screen.
The product can execute the method provided by the embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the method provided by the embodiment of the present invention.
As an embodiment, the electronic device is applied to a face recognition apparatus, and includes:
at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to:
controlling a shooting device to circularly acquire a face picture and send the face picture into a message queue, and circularly taking the face picture from the message queue for processing through a picture processing thread;
judging whether the number of the face pictures in the message queue reaches a preset threshold value or not;
and if the number of the face pictures reaches a preset threshold value, discarding new face pictures circularly acquired by the shooting device.
The electronic device of the embodiments of the present application exists in various forms, including but not limited to:
(1) a mobile communication device: such devices are characterized by mobile communications capabilities and are primarily targeted at providing voice, data communications. Such terminals include smart phones, multimedia phones, functional phones, and low-end phones, among others.
(2) Ultra mobile personal computer device: the equipment belongs to the category of personal computers, has calculation and processing functions and generally has the characteristic of mobile internet access. Such terminals include: PDA, MID, and UMPC devices, etc.
(3) A portable entertainment device: such devices can display and play multimedia content. The devices comprise audio and video players, handheld game consoles, electronic books, intelligent toys and portable vehicle-mounted navigation devices.
(4) The server is similar to a general computer architecture, but has higher requirements on processing capability, stability, reliability, safety, expandability, manageability and the like because of the need of providing highly reliable services.
(5) And other electronic devices with data interaction functions.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A face recognition method, comprising:
controlling a shooting device to circularly acquire a face picture and send the face picture into a message queue, and circularly taking the face picture from the message queue for processing through a picture processing thread;
judging whether the number of the face pictures in the message queue reaches a preset threshold value or not;
and if the number of the face pictures reaches a preset threshold value, discarding new face pictures circularly acquired by the shooting device.
2. The method of claim 1, wherein after the determining whether the number of face pictures in the message queue reaches a preset threshold, further comprising:
and if the number of the face pictures does not reach a preset threshold value, continuously sending the face pictures circularly acquired from the shooting device into the message list.
3. The method of claim 1, wherein after the cyclically acquiring, in response to the face recognition instruction, the face picture via the camera and sending the face picture into the message queue, and cyclically taking the face picture from the message queue via the picture processing thread for processing, the method further comprises:
acquiring the face pictures in the message queue for cyclic processing, acquiring the utilization rate of a central processing unit, and judging whether the utilization rate of the central processing unit is greater than a preset utilization rate threshold value;
and if the number of the face pictures is larger than the preset threshold value of the utilization rate, discarding new face pictures circularly acquired by the shooting device.
4. The method of claim 3, wherein said determining whether the usage rate of the central processor is greater than a usage rate preset threshold further comprises:
and if the utilization rate of the central processing unit is not greater than a preset utilization rate threshold value, continuously sending the user pictures circularly acquired from the shooting device into the message list.
5. The method according to any one of claims 1 to 4, wherein the discarding the new face pictures collected by the camera in a loop if the number of face pictures reaches a preset threshold comprises:
and if the number of the face pictures reaches a preset threshold value, informing the shooting device not to collect new face pictures.
6. The method of claim 5, after controlling the camera to not collect a new face picture if the number of face pictures reaches a preset threshold, the method further comprising:
and if the number of the face pictures in the message queue does not reach a preset threshold value, continuously acquiring new face pictures through the shooting device and sending the new face pictures into the message queue until the number of the face pictures in the message queue does not reach the preset threshold value.
7. A face recognition apparatus comprising:
the control acquisition processing module is configured to control the shooting device to circularly acquire the face pictures and send the face pictures into a message queue, and the face pictures are circularly taken from the message queue for processing through a picture processing thread;
the judging module is configured to judge whether the number of the face pictures in the message queue reaches a preset threshold value;
and the first discarding module is configured to discard the new face pictures circularly acquired by the shooting device if the number of the face pictures reaches a preset threshold value.
8. A face recognition apparatus, further comprising:
the acquisition judging module is configured to acquire the face pictures in the message queue for cyclic processing, acquire the utilization rate of a central processing unit and judge whether the utilization rate of the central processing unit is greater than a preset utilization rate threshold value;
and the second discarding module is configured to discard the new face picture circularly acquired by the shooting device if the utilization rate is greater than a preset threshold value.
9. A computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the steps of the method of any of claims 1 to 6.
10. An electronic device, comprising: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of the method of any of claims 1 to 6.
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| CN202011229319.3A CN112232287A (en) | 2020-11-06 | 2020-11-06 | Face recognition method and device |
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| CN202011229319.3A CN112232287A (en) | 2020-11-06 | 2020-11-06 | Face recognition method and device |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110163155A (en) * | 2019-05-23 | 2019-08-23 | 北京旷视科技有限公司 | Processing method, device, electronic equipment and the readable storage medium storing program for executing of human face data |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110163155A (en) * | 2019-05-23 | 2019-08-23 | 北京旷视科技有限公司 | Processing method, device, electronic equipment and the readable storage medium storing program for executing of human face data |
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Application publication date: 20210115 |