CN105516613A - Intelligent exposure method and system based on face recognition - Google Patents
Intelligent exposure method and system based on face recognition Download PDFInfo
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- CN105516613A CN105516613A CN201510891500.3A CN201510891500A CN105516613A CN 105516613 A CN105516613 A CN 105516613A CN 201510891500 A CN201510891500 A CN 201510891500A CN 105516613 A CN105516613 A CN 105516613A
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- brightness average
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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
- H04N23/70—Circuitry for compensating brightness variation in the scene
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- 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
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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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
- H04N23/60—Control of cameras or camera modules
- H04N23/61—Control of cameras or camera modules based on recognised objects
- H04N23/611—Control of cameras or camera modules based on recognised objects where the recognised objects include parts of the human body
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Abstract
The invention provides an intelligent exposure method and system based on face recognition. The method comprises: obtaining a scene type according to a face recognition algorithm, wherein the scene type comprises a scene with a face and a scene without a face; if the scene type is the scene without the face, setting a preset default value as an exposure reference value; if the scene type is the scene with the face, determining a face region, adjusting the exposure reference value according to the magnitudes of the average brightness value TF of the face region and the average brightness value TB of a background region. According to the invention, the scene type and the magnitudes of the average brightness value TF of the face region and the average brightness value TB of the background region are taken as the basis for adjusting the exposure reference value; the important function of the average brightness value TF of the face region in adjusting the exposure reference value is stressed; the phenomenon of influencing the normal exposure of a human body face through taking the whole image as the reference in adjusting the exposure reference value is avoided, and the problem in the prior art that the influence of the environment on exposure of the partial region of the face is relatively great is solved.
Description
Technical field
The present invention relates to a kind of exposure method and system, particularly relate to a kind of intelligent exposure method based on recognition of face and system.
Background technology
Face recognition technology is based on the face feature of people, first the facial image inputted or video flowing are judged whether it exists face, if there is face, then further provide the positional information of the position of each face, size and each major facial organ, and according to these information, the identity characteristic contained in each face of further extraction, and itself and known face are contrasted, thus identify the identity of each face.Face recognition technology can identify individual identity by face feature information and be subject to extensive concern.This technology has the features such as noncontact, non-imposed and concurrency because of it and is widely used in multiple fields such as face verification, safety, monitoring and man-machine interaction.
Along with the extensive use of face recognition technology, therefore the monitoring camera possessing face identification functions also arises at the historic moment.Automatic exposure algorithm is one of the most basic image processing algorithm of monitoring camera.Traditional automatic exposure algorithm calculates a brightness average Y according to current frame image, and presets a desirable brightness average scope Y
l-Y
h, carry out corresponding exposure parameter adjustment by the gap compared between Y to ideal value.
Under uniform light, bright condition, traditional automatic exposure algorithm better to the exposure effect of face; But under special illumination condition, traditional automatic exposure algorithm may cause face regional area to expose abnormal phenomenon, in the backlight situation that such as background is excessively bright, easily occur that face is under-exposed, cause face excessively dark, phenomenon not even not clearly.
Summary of the invention
The invention provides a kind of intelligent exposure method based on recognition of face and system, to solve prior art to face regional area exposure effect larger problem affected by environment.
The invention provides a kind of intelligent exposure method based on recognition of face, the described intelligent exposure method based on recognition of face comprises: obtain scene type according to face recognition algorithms, and described scene type includes face scene and without face scene; If scene type is without face scene, then default default value is set to Expose f iotaducials value; If scene type for there being face scene, then determines human face region, and according to human face region brightness average T
fwith background area brightness average T
bsize adjustment Expose f iotaducials value.
Preferably, described according to human face region brightness average T
fwith background area brightness average T
bsize determination Expose f iotaducials value comprise: obtain human face region brightness average T respectively
fwith background area brightness average T
b, and more described human face region brightness average T
fwith background area brightness average T
bsize; If described human face region brightness average T
fequal background area brightness average T
b, then default default value is set to Expose f iotaducials value; If described human face region brightness average T
fbe less than background area brightness average T
b, then described Expose f iotaducials value is raised; If described human face region brightness average T
fbe greater than background area brightness average T
b, then described Expose f iotaducials value is lowered.
Preferably, described according to human face region brightness average T
fwith background area brightness average T
bsize determination Expose f iotaducials value comprise: according to described human face region brightness average T
fwith background area brightness average T
bcalculate Δ T, described Δ T=T
b-T
f; If | Δ T|≤N, be then set to Expose f iotaducials value by default default value; If Δ T < is-N, then Expose f iotaducials value is default value+Δ T*n; If Δ T > is N, then Expose f iotaducials value is default value+Δ T*n; Wherein, N is relevant parameter, and described relevant parameter is positive integer; N is the area ratio of the relative full figure in background area.
Preferably, describedly determine that human face region comprises: the quantity judging to have face in face scene; Only include a face if having in face scene, then choose described face as human face region; If have in face scene and comprise multiple face, then choose the maximum face of face area as human face region.
Preferably, described human face region is with described face recognition result real-time update.
The invention provides a kind of intelligent exposure system based on recognition of face, the described intelligent exposure system based on recognition of face comprises: scene type acquisition module, described scene type acquisition module is used for obtaining scene type according to face recognition algorithms, and described scene type includes face scene and without face scene; Expose f iotaducials value adjusting module, if scene type is without face scene, then described Expose f iotaducials value adjusting module is used for default default value to be set to Expose f iotaducials value; If scene type is for there being face scene, then described Expose f iotaducials value adjusting module is used for determining human face region, and according to human face region brightness average T
fwith background area brightness average T
bdifference adjustment Expose f iotaducials value.
Preferably, described Expose f iotaducials value adjusting module comprises: T
fand T
bacquisition module, described T
fand T
bacquisition module is used for obtaining human face region brightness average T respectively
fwith background area brightness average T
b, and more described human face region brightness average T
fwith background area brightness average T
bsize; Expose f iotaducials value adjustment submodule, if described Expose f iotaducials value adjustment submodule is used for described human face region brightness average T
fequal background area brightness average T
b, then default default value is set to Expose f iotaducials value; If described human face region brightness average T
fbe less than background area brightness average T
b, then described Expose f iotaducials value is raised; If described human face region brightness average T
fbe greater than background area brightness average T
b, then described Expose f iotaducials value is lowered.
Preferably, described Expose f iotaducials value adjusting module comprises: face quantity judge module, and described face quantity judge module is for judging the quantity having face in face scene; Human face region chooses module, if described human face region chooses module only include a face for having in face scene, then chooses described face as human face region; If have in face scene and comprise multiple face, then choose the maximum face of face area as human face region.
The technical scheme that embodiments of the invention provide can comprise following beneficial effect:
The invention provides a kind of intelligent exposure method based on recognition of face, the described intelligent exposure method based on recognition of face comprises: obtain scene type according to face recognition algorithms, and described scene type includes face scene and without face scene; If scene type is without face scene, then default default value is set to Expose f iotaducials value; If scene type for there being face scene, then determines human face region, and according to human face region brightness average T
fwith background area brightness average T
bsize adjustment Expose f iotaducials value.The present invention is with scene type and human face region brightness average T
fwith background area brightness average T
bsize as the foundation of adjustment Expose f iotaducials value, outstanding human face region brightness average T
fimportant function in the adjustment of Expose f iotaducials value, when avoiding occurring with full figure being benchmark adjustment Expose f iotaducials value, affects the phenomenon of human body face normal exposure, can solve prior art to face regional area exposure effect larger problem affected by environment.
Should be understood that, it is only exemplary and explanatory that above general description and details hereinafter describe, and can not limit the present invention.
Accompanying drawing explanation
Fig. 1 is the flow chart of a kind of intelligent exposure method based on recognition of face provided in the embodiment of the present invention;
Fig. 2 be provide in the embodiment of the present invention according to human face region brightness average T
fwith background area brightness average T
bthe flow chart of size determination Expose f iotaducials value;
Fig. 3 is the structural representation of a kind of intelligent exposure system based on recognition of face provided in the embodiment of the present invention;
Fig. 4 is the structural representation of a kind of Expose f iotaducials value adjusting module provided in the embodiment of the present invention;
Fig. 5 is the structural representation of a kind of Expose f iotaducials value adjustment submodule provided in the embodiment of the present invention.
Embodiment
Here will be described exemplary embodiment in detail, its sample table shows in the accompanying drawings.When description below relates to accompanying drawing, unless otherwise indicated, the same numbers in different accompanying drawing represents same or analogous key element.Execution mode described in following exemplary embodiment does not represent all execution modes consistent with the present invention.On the contrary, they only with as in appended claims describe in detail, the example of device that aspects more of the present invention are consistent.
Each embodiment in this specification all adopts the mode of going forward one by one to describe, between each embodiment identical similar part mutually see, what each embodiment stressed is the difference with other embodiment.
Please refer to Fig. 1, be depicted as a kind of flow chart of the intelligent exposure method based on recognition of face.
As shown in Figure 1, the invention provides a kind of intelligent exposure method based on recognition of face, the described intelligent exposure method based on recognition of face comprises: obtain scene type according to face recognition algorithms, and described scene type includes face scene and without face scene; If scene type is without face scene, then default default value is set to Expose f iotaducials value; If scene type for there being face scene, then determines human face region, and according to human face region brightness average T
fwith background area brightness average T
bsize adjustment Expose f iotaducials value.Default value sets according to user's request, general, and default value gets middle gray scale 128.
Face recognition algorithms of the present invention is existing general-purpose algorithm, the concrete coordinate position whether containing human body face feature and human body face feature in scene can be judged, namely obtain exposure scene type, comprise without face scene and have face scene and the coordinate position of human body face feature in above scene.
When scene type is for there being a face scene, in scene, may existence anduniquess face, also may there is multiple face simultaneously, therefore, first need determine human face region.Concrete defining method is: judge the quantity having face in face scene; Only include a face if having in face scene, then choose described face as human face region; If have in face scene and comprise multiple face, then choose the maximum face of face area as human face region.After determining human face region, then ask for human face region brightness average T
f, by comparing T
fand T
bsize, adjustment Expose f iotaducials value.
The present invention is with scene type and human face region brightness average T
fwith background area brightness average T
bsize as the foundation of adjustment Expose f iotaducials value, outstanding human face region brightness average T
fimportant function in the adjustment of Expose f iotaducials value, when avoiding occurring with full figure being benchmark adjustment Expose f iotaducials value, affects the phenomenon of human body face normal exposure, can solve prior art to face regional area exposure effect larger problem affected by environment.
Please refer to Fig. 2, be depicted as provide in the embodiment of the present invention according to human face region brightness average T
fwith background area brightness average T
bthe flow chart of size determination Expose f iotaducials value.
As shown in Figure 2, described according to human face region brightness average T
fwith background area brightness average T
bsize determination Expose f iotaducials value comprise: obtain human face region brightness average T respectively
fwith background area brightness average T
b, and more described human face region brightness average T
fwith background area brightness average T
bsize; If described human face region brightness average T
fequal background area brightness average T
b, then default default value is set to Expose f iotaducials value; If described human face region brightness average T
fbe less than background area brightness average T
b, then described Expose f iotaducials value is raised; If described human face region brightness average T
fbe greater than background area brightness average T
b, then described Expose f iotaducials value is lowered.
Further, according to described human face region brightness average T
fwith background area brightness average T
bcalculate Δ T, described Δ T=T
b-T
f; If | Δ T|≤N, be then set to Expose f iotaducials value by default default value; If Δ T < is-N, then Expose f iotaducials value is default value+Δ T*n; If Δ T > is N, then Expose f iotaducials value is default value+Δ T*n; Wherein, N is relevant parameter, and described relevant parameter is positive integer; N is the area ratio of the relative full figure in background area.That is, Expose f iotaducials value and human face region brightness average T
fwith background area brightness average T
bdifference, background area relevant relative to the area ratio of full figure.Human face region brightness average T
fwith background area brightness average T
bdifference is larger, and the area ratio of the relative full figure in background area is larger, then the dynamics of Expose f iotaducials value adjustment is larger.
Further, human face region, with the concrete coordinate position change real-time update of human body face feature, improves the accuracy of human body face exposure, solves prior art further to face regional area exposure effect larger problem affected by environment.
Please refer to Fig. 3, be depicted as the structural representation of a kind of intelligent exposure system based on recognition of face that the embodiment of the present invention provides.
As shown in Figure 3, the described intelligent exposure system based on recognition of face comprises: scene type acquisition module, and described scene type acquisition module is used for obtaining scene type according to face recognition algorithms, and described scene type includes face scene and without face scene; Expose f iotaducials value adjusting module, if scene type is without face scene, then described Expose f iotaducials value adjusting module is used for default default value to be set to Expose f iotaducials value; If scene type is for there being face scene, then described Expose f iotaducials value adjusting module is used for determining human face region, and according to human face region brightness average T
fwith background area brightness average T
bdifference adjustment Expose f iotaducials value.
Please refer to Fig. 4, be depicted as the structural representation of a kind of Expose f iotaducials value adjusting module that the embodiment of the present invention provides.
As shown in Figure 4, described Expose f iotaducials value adjusting module comprises: T
fand T
bacquisition module, described T
fand T
bacquisition module is used for obtaining human face region brightness average T respectively
fwith background area brightness average T
b, and more described human face region brightness average T
fwith background area brightness average T
bsize; Expose f iotaducials value adjustment submodule, if described Expose f iotaducials value adjustment submodule is used for described human face region brightness average T
fequal background area brightness average T
b, then default default value is set to Expose f iotaducials value; If described human face region brightness average T
fbe less than background area brightness average T
b, then described Expose f iotaducials value is raised; If described human face region brightness average T
fbe greater than background area brightness average T
b, then described Expose f iotaducials value is lowered.
Please refer to Fig. 5, be depicted as the structural representation of a kind of Expose f iotaducials value adjustment submodule that the embodiment of the present invention provides.
As shown in Figure 5, described Expose f iotaducials value adjusting module comprises: face quantity judge module, and described face quantity judge module is for judging the quantity having face in face scene; Human face region chooses module, if described human face region chooses module only include a face for having in face scene, then chooses described face as human face region; If have in face scene and comprise multiple face, then choose the maximum face of face area as human face region.
This programme analyses the illumination particularity of current environment by the brightness mean difference analyzing human face region and background area, and then dynamic conditioning Expose f iotaducials value, thus guarantees the Correct exposure in varying environment illumination human face region.Meanwhile, dynamic conditioning Expose f iotaducials value-based algorithm of the present invention also can be amplified for the exposure algorithm in local window.
Above-described embodiment of the present invention, does not form limiting the scope of the present invention.Any amendment done within the spirit and principles in the present invention, equivalent replacement and improvement etc., all should be included within protection scope of the present invention.
The above is only the specific embodiment of the present invention, those skilled in the art is understood or realizes the present invention.To be apparent to one skilled in the art to the multiple amendment of these embodiments, General Principle as defined herein can without departing from the spirit or scope of the present invention, realize in other embodiments.Therefore, the present invention can not be restricted to these embodiments shown in this article, but will meet the widest scope consistent with principle disclosed herein and features of novelty.
Claims (8)
1. based on an intelligent exposure method for recognition of face, it is characterized in that, the described intelligent exposure method based on recognition of face comprises:
Obtain scene type according to face recognition algorithms, described scene type includes face scene and without face scene;
If scene type is without face scene, then default default value is set to Expose f iotaducials value;
If scene type for there being face scene, then determines human face region, and according to human face region brightness average T
fwith background area brightness average T
bsize adjustment Expose f iotaducials value.
2. the intelligent exposure method based on recognition of face according to claim 1, is characterized in that, described according to human face region brightness average T
fwith background area brightness average T
bsize determination Expose f iotaducials value comprise:
Obtain human face region brightness average T respectively
fwith background area brightness average T
b, and more described human face region brightness average T
fwith background area brightness average T
bsize;
If described human face region brightness average T
fequal background area brightness average T
b, then default default value is set to Expose f iotaducials value;
If described human face region brightness average T
fbe less than background area brightness average T
b, then described Expose f iotaducials value is raised;
If described human face region brightness average T
fbe greater than background area brightness average T
b, then described Expose f iotaducials value is lowered.
3. the intelligent exposure method based on recognition of face according to claim 2, is characterized in that, described according to human face region brightness average T
fwith background area brightness average T
bsize determination Expose f iotaducials value comprise:
According to described human face region brightness average T
fwith background area brightness average T
bcalculate Δ T, described Δ T=T
b-T
f;
If | Δ T|≤N, be then set to Expose f iotaducials value by default default value;
If Δ T < is-N, then Expose f iotaducials value is default value+Δ T*n;
If Δ T > is N, then Expose f iotaducials value is default value+Δ T*n;
Wherein, N is relevant parameter, and described relevant parameter is positive integer; N is the area ratio of the relative full figure in background area.
4. the intelligent exposure method based on recognition of face according to claim 1, is characterized in that, describedly determines that human face region comprises:
Judge the quantity having face in face scene;
Only include a face if having in face scene, then choose described face as human face region;
If have in face scene and comprise multiple face, then choose the maximum face of face area as human face region.
5. the intelligent exposure method based on recognition of face according to claim 1, is characterized in that, described human face region is with described face recognition result real-time update.
6. based on an intelligent exposure system for recognition of face, it is characterized in that, the described intelligent exposure system based on recognition of face comprises:
Scene type acquisition module, described scene type acquisition module is used for obtaining scene type according to face recognition algorithms, and described scene type includes face scene and without face scene;
Expose f iotaducials value adjusting module, if scene type is without face scene, then described Expose f iotaducials value adjusting module is used for default default value to be set to Expose f iotaducials value; If scene type is for there being face scene, then described Expose f iotaducials value adjusting module is used for determining human face region, and according to human face region brightness average T
fwith background area brightness average T
bdifference adjustment Expose f iotaducials value.
7. the intelligent exposure system based on recognition of face according to claim 6, is characterized in that, described Expose f iotaducials value adjusting module comprises:
T
fand T
bacquisition module, described T
fand T
bacquisition module is used for obtaining human face region brightness average T respectively
fwith background area brightness average T
b, and more described human face region brightness average T
fwith background area brightness average T
bsize;
Expose f iotaducials value adjustment submodule, if described Expose f iotaducials value adjustment submodule is used for described human face region brightness average T
fequal background area brightness average T
b, then default default value is set to Expose f iotaducials value; If described human face region brightness average T
fbe less than background area brightness average T
b, then described Expose f iotaducials value is raised; If described human face region brightness average T
fbe greater than background area brightness average T
b, then described Expose f iotaducials value is lowered.
8. the intelligent exposure system based on recognition of face according to claim 6, is characterized in that, described Expose f iotaducials value adjusting module comprises:
Face quantity judge module, described face quantity judge module is for judging the quantity having face in face scene;
Human face region chooses module, if described human face region chooses module only include a face for having in face scene, then chooses described face as human face region; If have in face scene and comprise multiple face, then choose the maximum face of face area as human face region.
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