CN112383713B - Driving method for automatically loading human face MIPI or human face USB camera - Google Patents
Driving method for automatically loading human face MIPI or human face USB camera Download PDFInfo
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- CN112383713B CN112383713B CN202011270196.8A CN202011270196A CN112383713B CN 112383713 B CN112383713 B CN 112383713B CN 202011270196 A CN202011270196 A CN 202011270196A CN 112383713 B CN112383713 B CN 112383713B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
- H04N23/815—Camera processing pipelines; Components thereof for controlling the resolution by using a single image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F13/00—Interconnection of, or transfer of information or other signals between, memories, input/output devices or central processing units
- G06F13/38—Information transfer, e.g. on bus
- G06F13/42—Bus transfer protocol, e.g. handshake; Synchronisation
- G06F13/4282—Bus transfer protocol, e.g. handshake; Synchronisation on a serial bus, e.g. I2C bus, SPI bus
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4014—Identity check for transactions
- G06Q20/40145—Biometric identity checks
Abstract
The invention relates to the field of Android equipment camera driving, and discloses a driving method for automatically loading a human face MIPI or a human face USB camera, which comprises the following steps: starting the Android device, and powering on a plurality of pins of the MIPI through GPIO driving; reading the value of the sensor register through a camera i2c bus to inquire the in-place state of the MIPI camera, and judging whether the MIPI camera exists or not; loading a human face MIPI camera drive and ISP chromatix image effect parameters to obtain corresponding MIPI camera human face algorithm identification parameters; loading a face USB camera drive, and acquiring face algorithm identification parameters of the USB camera; activating a face algorithm license and initializing the face algorithm. The invention provides a driving method for automatically loading MIPI or USB face binocular and 3D cameras by Android equipment, so that various face brushing hardware equipment is compatible, and bottom layer support is provided for financial-level non-matching face brushing safety payment.
Description
Technical Field
The invention relates to the field of Android equipment camera driving, in particular to a driving method for automatically loading a human face MIPI or a human face USB camera.
Background
Ordinary Android smart machine, the loaded monocular camera drive that all is, functions such as ordinary shooing can only be done to the camera drive of this kind of mode loading for can only plane detection when the biopsy, need the action cooperation, can't satisfy the face payment requirement of brushing of financial security level.
For example, the national patent publication "CN 105354551A" discloses a "gesture recognition method based on a monocular camera", and the invention includes: shooting a video by using a monocular camera to obtain a video frame collected by the monocular camera; carrying out image characteristic analysis on the video frame; if the palm region picture exists, storing each moment and the corresponding palm region position into a global cache; analyzing the positions of the palm region at multiple moments, acquiring the relative position of the palm region within a preset duration, and recognizing corresponding gesture operation according to the relative position of the palm region; and comparing the recognized gesture operation with a plurality of predefined gestures to obtain the matched predefined gestures, and calling callback functions corresponding to the matched predefined gestures to complete corresponding control actions. The invention performs plane detection, requires gesture action matching and cannot meet the face brushing payment requirement of financial security level.
Disclosure of Invention
The invention provides a driving method for automatically loading a human face MIPI or a human face USB camera, thereby solving the problems in the prior art.
The driving method for automatically loading the human face MIPI or the human face USB camera comprises the following steps:
s1) starting the Android device, entering a kernel core of the Android device, and electrifying a plurality of pins of an MIPI (Mobile Industry Processor interface) interface through GPIO (general purpose input/output) drive;
s2) reading the value of the sensor register through a camera i2c bus to inquire the in-place state of the MIPI camera, judging whether the MIPI camera exists or not, and if yes, entering the step S3); if not, go to step S4);
s3) loading the human face MIPI camera drive and the ISP chromatix image effect parameters, and acquiring corresponding MIPI camera human face algorithm identification parameters;
s4) loading a face USB camera driver, and acquiring face algorithm identification parameters of the corresponding USB camera;
s5) activating the face algorithm license and initializing the face algorithm according to the face algorithm identification parameter of the corresponding USB camera or the face algorithm identification parameter of the corresponding MIPI camera.
Further, several pins of the MIPI interface include VIO, VANA, VDIG, and MCLK.
Further, in step S3), loading the human face MIPI camera driver and the ISP chromamatix image effect parameter, and acquiring the corresponding MIPI camera human face algorithm identification parameter, including the following steps:
s31) acquiring the driving names and the number of the front camera and the rear camera;
s32) writing a register list of the initialized cameras into the cameras corresponding to the drive names of the front cameras in sequence through a camera i2c bus according to the drive names of the front cameras;
s33), after writing in a register list of an initialization camera, loading an ISP chromatix image effect parameter on the camera corresponding to the drive name of the front camera;
s34) loading the face algorithm identification parameters of the camera corresponding to the drive name of the front camera according to the drive name of the front camera.
Further, the front camera comprises a front RGB camera, a front IR camera and a front depth camera.
Further, in step S4), loading a face USB camera driver, and obtaining a face algorithm identification parameter of a corresponding USB camera, includes the following steps:
s41) powering on the USB camera through GPIO drive, and loading a human face USB camera drive corresponding to the USB camera through a USB host after the powering on is successful;
s42) obtaining the type and name of the USB camera, and loading the face algorithm identification parameters of the USB camera corresponding to the type and name of the USB camera.
Because the leading RGB camera in people's face, leading IR camera and leading depth camera use MIPI or USB camera, after confirming leading face MIPI camera state in place, need load different drive and algorithm according to MIPI camera state in place: if the face front MIPI camera does not exist, a face USB binocular or 3D camera drive and algorithm need to be loaded; if the face-front MIPI camera exists, the face MIPI camera drive and the algorithm need to be loaded. According to the face algorithm identification parameters, license corresponding to the face algorithm is deactivated, the face algorithm is initialized, and preparation is made for next binocular or 3D face living body detection.
Further, in step S42), polling the USB camera by the android UsbManager to obtain the VID and PID of the USB camera in use, and determining the type and name of the USB camera according to the VID and PID of the USB camera in use; VID is supplier ID and PID is product identification code.
The invention has the beneficial effects that: go to polling respectively and load people's face MIPI or people's face USB camera drive through camera i2c bus and USB host line, realized the live body discernment of people's face binocular and 3D, solved the android device can only load people's face MIPI monocular camera drive before, can't realize the problem of financial level brush face payment. The invention provides a driver and an algorithm for automatically loading MIPI or USB face binocular and a 3D camera by Android equipment, so that various face brushing hardware equipment is compatible, and finally, bottom layer support is provided for financial-level non-matching face brushing safety payment.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments are briefly described 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 without creative efforts.
Fig. 1 is a schematic flowchart of a driving method for automatically loading a human face MIPI or a human face USB camera according to this embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
In a first embodiment, a driving method for automatically loading a human face MIPI or a human face USB camera, as shown in fig. 1, includes the following steps:
s1) starting the Android device, entering a kernel core of the Android device, and electrifying a plurality of pins of an MIPI (Mobile Industry Processor interface) interface through GPIO (general purpose input/output) drive;
s2) reading the value of the sensor register through a camera i2c bus to inquire the in-place state of the MIPI camera, judging whether the MIPI camera exists or not, and if yes, entering the step S3); if not, go to step S4);
s3) loading the human face MIPI camera drive and the ISP chromatix image effect parameters, and acquiring the corresponding MIPI camera human face algorithm identification parameters, wherein the method comprises the following steps:
s31) acquiring the driving names and the number of the front camera and the rear camera; the front camera comprises a front RGB camera, a front IR camera and a front depth camera.
S32) writing the register list of the initialization cameras in order to the cameras corresponding to the drive names of the front cameras through the camera i2c bus according to the drive names of the front cameras. The register list is used for registering initialization data of the cameras, acquiring the initialization data of the cameras according to the driving names of the front cameras, and writing the initialization data of the cameras into the register list in sequence.
S33), after the register list of the initialized camera is written, loading ISP chromatix image effect parameters on the camera corresponding to the drive name of the front camera;
s34) loading the face algorithm identification parameters of the camera corresponding to the drive name of the front camera according to the drive name of the front camera.
S4) loading a face USB camera drive, and acquiring the face algorithm identification parameters of the corresponding USB camera, wherein the method comprises the following steps:
s41) loading a face USB camera drive, namely, electrifying the USB camera through the GPIO drive, and loading the face USB camera drive corresponding to the USB camera through a USB host after the electrification is successful;
s42) obtaining the type and name of the USB camera, and loading the face algorithm identification parameters of the USB camera corresponding to the type and name of the USB camera.
Step S42), polling the USB camera through the android UsbManager to obtain the VID and PID of the USB camera in use, and determining the type and name of the USB camera according to the VID and PID of the USB camera in use; VID is supplier ID and PID is product identification code.
S5) activating the face algorithm license and initializing the face algorithm according to the face algorithm identification parameter of the corresponding USB camera or the face algorithm identification parameter of the corresponding MIPI camera.
Several pins of the MIPI interface include VIO, VANA, VDIG, and MCLK.
VIO is an IO power supply pin, VANA is an analog power supply pin, VDIG is a digital power supply pin, and MCLK is a main clock pin.
Because the leading RGB camera in people's face, leading IR camera and leading depth camera use MIPI or USB camera, after confirming leading face MIPI camera state in place, need load different drive and algorithm according to MIPI camera state in place: if the face front MIPI camera does not exist, a face USB binocular or 3D camera drive and algorithm need to be loaded; if the face-front MIPI camera exists, the face MIPI camera drive and the algorithm need to be loaded. According to the face algorithm identification parameters, license corresponding to the face algorithm is deactivated, the face algorithm is initialized, and preparation is made for next binocular or 3D face living body detection.
By adopting the technical scheme disclosed by the invention, the following beneficial effects are obtained:
go to polling respectively and load people's face MIPI or people's face USB camera drive through camera i2c bus and USB host line, realized the live body discernment of people's face binocular and 3D, solved the android device can only load people's face MIPI monocular camera drive before, can't realize the problem of financial level brush face payment. The invention provides a driver and an algorithm for automatically loading MIPI or USB face binocular and a 3D camera by Android equipment, so that various face brushing hardware equipment is compatible, and finally, bottom layer support is provided for financial-level non-matching face brushing safety payment.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements should also be considered within the scope of the present invention.
Claims (5)
1. The driving method for automatically loading the human face MIPI or the human face USB camera is characterized by comprising the following steps of:
s1) starting the Android device, entering a kernel core of the Android device, and powering on a plurality of pins of the MIPI through GPIO driving;
s2) reading the value of the sensor register through a camera i2c bus to inquire the in-place state of the MIPI camera, judging whether the MIPI camera exists or not, and if yes, entering the step S3); if not, go to step S4);
s3) loading the human face MIPI camera drive and the ISP chromatix image effect parameters, and acquiring corresponding MIPI camera human face algorithm identification parameters;
s4) loading a face USB camera driver, and acquiring face algorithm identification parameters of the corresponding USB camera;
s5) activating a face algorithm license and initializing a face algorithm according to the face algorithm identification parameter of the corresponding USB camera or the face algorithm identification parameter of the corresponding MIPI camera;
step S3), loading the human face MIPI camera drive and ISP chromatix image effect parameters, and acquiring corresponding MIPI camera human face algorithm identification parameters, wherein the method comprises the following steps:
s31) acquiring the driving names and the number of the front camera and the rear camera;
s32) writing a register list of the initialized cameras into the cameras corresponding to the drive names of the front cameras in sequence through a camera i2c bus according to the drive names of the front cameras;
s33) loading ISP chromatix image effect parameters to the camera corresponding to the drive name of the front camera;
s34) loading the face algorithm identification parameters of the camera corresponding to the drive name of the front camera according to the drive name of the front camera.
2. The driving method for automatically loading the human face MIPI or the human face USB camera according to the claim 1, wherein, a plurality of pins of the MIPI interface comprise VIO, VANA, VDIG and MCLK.
3. The driving method for automatically loading the human face MIPI or human face USB camera according to claim 1, wherein the front camera comprises a front RGB camera, a front IR camera and a front depth camera.
4. The driving method for automatically loading the human face MIPI or the human face USB camera according to the claim 1 or 3, in the step S4), the step of loading the human face USB camera driver to obtain the human face algorithm identification parameter of the corresponding USB camera comprises the following steps:
s41) powering on the USB camera through GPIO drive, and loading a human face USB camera drive corresponding to the USB camera through a USB host after the powering on is successful;
s42) obtaining the type and name of the USB camera, and loading the face algorithm identification parameters of the USB camera corresponding to the type and name of the USB camera.
5. The driving method for automatically loading the human face MIPI or the human face USB camera according to the claim 4, in the step S42), polling the USB camera by the android UsbManager to obtain the VID and PID of the camera in use, and determining the type and name of the USB camera according to the VID and PID of the camera in use; the VID is a supplier ID and the PID is a product identification code.
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