CN105120149A - An automatic focusing method and terminal - Google Patents
An automatic focusing method and terminal Download PDFInfo
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- CN105120149A CN105120149A CN201510500687.XA CN201510500687A CN105120149A CN 105120149 A CN105120149 A CN 105120149A CN 201510500687 A CN201510500687 A CN 201510500687A CN 105120149 A CN105120149 A CN 105120149A
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Abstract
The embodiment of the invention discloses an automatic focusing method comprising the following steps of changing the focus distance of a camera and collecting images under various focus distances, identifying the facial feature points in the images, calculating focus evaluation values of the images with regard to the facial feature points, and adjusting the focus distance of the camera to be the focus distance corresponding to the largest focus evaluation value. Correspondingly, the embodiment of the invention also discloses the terminal. Through adoption of the embodiment of the invention, the camera is enabled to accurately focus on the face in a motion or a non-motion scene, thereby enhancing a shooting effect and improving user usage experience.
Description
Technical field
The present invention relates to camera technique field, particularly relate to a kind of self-focusing method and terminal.
Background technology
Along with the development of electronic product, the terminal of band shoot function is more and more universal, and the requirement of user to its shooting effect is also more and more higher.In order to shoot portrait clearly, require that the camera lens of terminal can focus on portrait (especially face), this depends on Techniques of Automatic Focusing.At present, common Techniques of Automatic Focusing is: obtain the human face region (rectangular area at face place) in image by face recognition technology; The image sharpness value of the human face region in computed image; By the focusing of camera from focusing corresponding to the more excellent image sharpness value being adjusted to this human face region image from.
Such as, but in above-mentioned Techniques of Automatic Focusing, when comprising high-contrast background in human face region, the object etc. of sunlight, high reflective thing or texture-rich, camera lens may focus in the background beyond face, causes shooting effect undesirable.As can be seen here, existing Techniques of Automatic Focusing is not perfect, reduces the experience of user.
Summary of the invention
The embodiment of the present invention provides a kind of self-focusing method and terminal, can realize exactly camera being focused on face, improves shooting effect.
The self-focusing method of the one that the embodiment of the present invention provides, comprising:
Change camera focusing from and gather each focusing under image;
Identify the human face characteristic point in image described in each;
Calculate the focusing evaluation of estimate that image described in each is directed to its human face characteristic point;
By the focusing of described camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from.
Correspondingly, the embodiment of the present invention additionally provides a kind of terminal, comprising:
Image acquisition units, for the focusing that changes camera from and gather each focusing under image;
Feature point recognition unit, for identifying the human face characteristic point in image described in each;
Evaluation of estimate computing unit, is directed to the focusing evaluation of estimate of its human face characteristic point for calculating image described in each;
Focus control unit, for by the focusing of described camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from.
The embodiment of the present invention, first the focusing changing camera from and gather each focusing under image, then the human face characteristic point in each image is identified, then the focusing evaluation of estimate that each image is directed to its human face characteristic point is calculated, and then by the focusing of camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from, can realize exactly camera being focused on face, improve shooting effect, improve the experience of user.
Accompanying drawing explanation
In order to be illustrated more clearly in the technical scheme of the embodiment of the present invention, below the accompanying drawing used required in describing embodiment is briefly described, apparently, accompanying drawing in the following describes is some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the schematic flow sheet of a kind of self-focusing method that the embodiment of the present invention provides;
Fig. 2 is the schematic flow sheet of the self-focusing method of another kind that the embodiment of the present invention provides;
Fig. 3 is the structural representation of a kind of terminal that the embodiment of the present invention provides;
Fig. 4 is the structural representation of the another kind of terminal that the embodiment of the present invention provides;
Fig. 5 is the schematic diagram of a kind of human face characteristic point that the embodiment of the present invention provides;
Fig. 6 is the schematic diagram of the another kind of human face characteristic point that the embodiment of the present invention provides.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
A kind of self-focusing method that the embodiment of the present invention provides is applied to the terminal being configured with camera, and described terminal can comprise smart mobile phone, panel computer, notebook computer, desktop computer, digital audio & video players, electronic reader, handheld game machine and vehicle electronic device etc.
Fig. 1 is the schematic flow sheet of a kind of self-focusing method in the embodiment of the present invention.The flow process of the self-focusing method as shown in the figure in the present embodiment can comprise:
S101, change camera focusing from and gather each focusing under image.
Alternatively, the terminal focusing that can change camera in default adjustable range from and gather each focusing under image.Wherein, described focusing refers to the distance between the camera lens of camera to focal position from (FocusDistance), if focal position overlaps with subject, then subject is now the most clear.In addition, described default adjustable range is preset by designer or user, is not construed as limiting here, and such as, under close shot photographed scene, default adjustable range is 20cm to 30m; And for example, under vista shot scene, default adjustable range is 1m to 1000m.
S102, identifies the human face characteristic point in image described in each.
For the ease of understanding, first introduce human face characteristic point here, the point that human face characteristic point has referred to face assigned address corresponding, as the position such as canthus, the corners of the mouth.As an optional example, refer to Fig. 5, suppose the face in Fig. 5 a presentation video, then 8 dots in Fig. 5 b can represent human face characteristic point.It should be noted that, human face characteristic point can pass through facial modeling (FacialLandmarkLocalization) technology and detect from image, such as based on stable facial modeling (Exemplar-basedGraphMatchingforRobustFacialLandmarkLocali zation) technology etc. of figure coupling, do not do exhaustive here.
Particularly, terminal detects human face characteristic point by facial modeling technology from each image.
S103, calculates the focusing evaluation of estimate that image described in each is directed to its human face characteristic point.
Described focusing evaluation of estimate, for weighing the focusing effect of a pictures, can comprise pixel, anti-noise value or image sharpness value etc., be not construed as limiting here.It is pointed out that in the embodiment of the present invention, be described as focusing evaluation of estimate using image sharpness value.
Described image sharpness value is a kind of index reflecting plane of delineation definition and image border sharpness, and image sharpness value is higher, and the contrast of its details is higher, views and admires more clear.Further, the assessment mode of image sharpness value has a lot, such as depth assessment, gray scale assessment and gradient assessment etc., and the present embodiment is evaluated as example with gradient, and namely the image sharpness value of described default neighborhood equals the Grad summation of all picture points in default neighborhood.Wherein, gradient calculation can use tenengrad/sobel operator or PrewittGradientEdgeDetection operator, does not do detailed expansion here.
As an optional example, refer to Fig. 6, suppose that 8 dots in Fig. 6 a represent the human face characteristic point identified, then 8 little square frames in Fig. 6 b can represent the default neighborhood of human face characteristic point, and terminal calculates the image sharpness value of these default neighborhoods.It is pointed out that the size value of default neighborhood does not do concrete restriction here, can set according to the distance value of face to terminal, such as, suppose that face is 50m to the distance value of terminal, then the size that can arrange default neighborhood is 10*10 pixel.
Particularly, terminal calculates the image sharpness value of the default neighborhood of the human face characteristic point of each image.
Should understand ground, the peripheral region of human face characteristic point is that the definition of whole face requires the highest place, and therefore the present embodiment not only can accurately focus on face, accelerate focusing speed, further improves shooting effect.
S104, by the focusing of described camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from.
Particularly, terminal by the focusing of camera from focusing corresponding to the image being adjusted to maximum image sharpness value from.
In specific implementation process, terminal searches out the image of maximum image sharpness value from each image by preset search mode, and by the focusing of camera from focusing corresponding to the image being adjusted to the maximum image sharpness value searched out from.Further, preset search mode can be the searching algorithm based on the degree of depth, gray scale or gradient, and described searching algorithm includes but not limited to hill-climbing algorithm, simulated annealing or genetic algorithm etc.Preferably, the preset search mode in the present embodiment based on searching algorithm be hill-climbing algorithm.
Described hill-climbing algorithm is a kind of local method preferentially, namely from current focusing from the image of correspondence, compare with the focusing of the surrounding image from correspondence, if the sharpness value of present image is larger, so return present image, as the image having maximum image sharpness value, otherwise just replace present image with the image of surrounding maximum image sharpness value, realize the object of climbing to the eminence on mountain peak by that analogy, until search out the image of maximum image sharpness value.Alternatively, the hill-climbing algorithm in the embodiment of the present invention can adopt RS search method, does not do detailed expansion here.
The embodiment of the present invention, first the focusing changing camera from and gather each focusing under image, then the human face characteristic point in each image is identified, then the focusing evaluation of estimate that each image is directed to its human face characteristic point is calculated, and then by the focusing of camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from, can realize exactly camera being focused on face, improve shooting effect, improve the experience of user.
Fig. 2 is the structural representation of another kind of self-focusing method in the embodiment of the present invention.The flow process of the self-focusing method as shown in the figure in the present embodiment can comprise:
S201, the focusing changing camera in default adjustable range from and gather each focusing under image.
Wherein, described focusing refers to the distance between the camera lens of camera to focal position from (FocusDistance), if focal position overlaps with subject, then subject is now the most clear.In addition, described default adjustable range is preset by designer or user, is not construed as limiting here, and such as, under close shot photographed scene, default adjustable range is 20cm to 30m; And for example, under vista shot scene, default adjustable range is 1m to 1000m.
S202, identifies the human face characteristic point in image described in each.
For the ease of understanding, first introduce human face characteristic point here, the point that human face characteristic point has referred to face assigned address corresponding, as the position such as canthus, the corners of the mouth.As an optional example, refer to Fig. 5, suppose the face in Fig. 5 a presentation video, then 8 dots in Fig. 5 b can represent human face characteristic point.It should be noted that, human face characteristic point can pass through facial modeling (FacialLandmarkLocalization) technology and detect from image, such as based on stable facial modeling (Exemplar-basedGraphMatchingforRobustFacialLandmarkLocali zation) technology etc. of figure coupling, do not do exhaustive here.
Particularly, terminal detects human face characteristic point by facial modeling technology from each image.
S203, calculates the image sharpness value of the default neighborhood of the human face characteristic point in image described in each.
Described image sharpness value is a kind of index reflecting plane of delineation definition and image border sharpness, and image sharpness value is higher, and the contrast of its details is higher, views and admires more clear.Further, the assessment mode of image sharpness value has a lot, such as depth assessment, gray scale assessment and gradient assessment etc., and the present embodiment is evaluated as example with gradient, and namely the image sharpness value of described default neighborhood equals the Grad summation of all picture points in default neighborhood.Wherein, gradient calculation can use tenengrad/sobel operator or PrewittGradientEdgeDetection operator, does not do detailed expansion here.
As an optional example, refer to Fig. 6, suppose that 8 dots in Fig. 6 a represent the human face characteristic point identified, then 8 little square frames in Fig. 6 b can represent the default neighborhood of human face characteristic point, and terminal calculates the image sharpness value of these default neighborhoods.It is pointed out that the size value of default neighborhood does not do concrete restriction here, can set according to the distance value of face to terminal, such as, suppose that face is 50m to the distance value of terminal, then the size that can arrange default neighborhood is 10*10 pixel.
Should understand ground, the peripheral region of human face characteristic point is that the definition of whole face requires the highest place, and therefore the present embodiment not only can accurately focus on face, accelerate focusing speed, further improves shooting effect.
S204, searches out the image of maximum image sharpness value from image described in each by preset search mode.
Wherein, preset search mode can be the searching algorithm based on the degree of depth, gray scale or gradient, and described searching algorithm includes but not limited to hill-climbing algorithm, simulated annealing or genetic algorithm etc.Preferably, the preset search mode in the present embodiment based on searching algorithm be hill-climbing algorithm.
Described hill-climbing algorithm is a kind of local method preferentially, namely from current focusing from the image of correspondence, compare with the focusing of the surrounding image from correspondence, if the sharpness value of present image is larger, so return present image, as the image having maximum image sharpness value, otherwise just replace present image with the image of surrounding maximum image sharpness value, realize the object of climbing to the eminence on mountain peak by that analogy, until search out the image of maximum image sharpness value.Alternatively, the hill-climbing algorithm in the embodiment of the present invention can use RS searching algorithm, does not do detailed expansion here.
S205, judges whether the scene of the image of current described camera collection changes.
Wherein, scene changes refers to whether the content of gathered image changes.In specific implementation process, can judge whether the position of camera changes, and also whether can change according to the mean flow rate of the image collected judges according to the gyrostatic information of terminal.
Particularly, whether the scene of the image of the current camera collection of terminal judges changes, and if so, then returns step S201, if not, then performs step S206.
S206, by the focusing of described camera from focusing corresponding to the image being adjusted to the described maximum image sharpness value searched out from.
The embodiment of the present invention, first the focusing changing camera from and gather each focusing under image, then the human face characteristic point in each image is identified, then the focusing evaluation of estimate that each image is directed to its human face characteristic point is calculated, and then by the focusing of camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from, can realize exactly camera being focused on face, improve shooting effect, improve the experience of user.
Fig. 3 is the structural representation of a kind of terminal in the embodiment of the present invention.Terminal as shown in the figure in the embodiment of the present invention at least can comprise image acquisition units 310, Feature point recognition unit 320, evaluation of estimate computing unit 330 and focus control unit 340, wherein:
Image acquisition units 310, for the focusing that changes camera from and gather each focusing under image.
Alternatively, image acquisition units 310 focusing that can change camera in default adjustable range from and gather each focusing under image.Wherein, described focusing refers to the distance between the camera lens of camera to focal position from (FocusDistance), if focal position overlaps with subject, then subject is now the most clear.In addition, described default adjustable range is preset by designer or user, is not construed as limiting here, and such as, under close shot photographed scene, default adjustable range is 20cm to 30m; And for example, under vista shot scene, default adjustable range is 1m to 1000m.
Feature point recognition unit 320, for identifying the human face characteristic point in image described in each.
For the ease of understanding, first introduce human face characteristic point here, the point that human face characteristic point has referred to face assigned address corresponding, as the position such as canthus, the corners of the mouth.As an optional example, refer to Fig. 5, suppose the face in Fig. 5 a presentation video, then 8 dots in Fig. 5 b can represent human face characteristic point.It should be noted that, human face characteristic point can pass through facial modeling (FacialLandmarkLocalization) technology and detect from image, such as based on stable facial modeling (Exemplar-basedGraphMatchingforRobustFacialLandmarkLocali zation) technology etc. of figure coupling, do not do exhaustive here.
Particularly, Feature point recognition unit 320 detects human face characteristic point by facial modeling technology from each image.
Evaluation of estimate computing unit 330, is directed to the focusing evaluation of estimate of its human face characteristic point for calculating image described in each.
Described focusing evaluation of estimate, for weighing the focusing effect of a pictures, can comprise pixel, anti-noise value or image sharpness value etc., be not construed as limiting here.It is pointed out that in the embodiment of the present invention, be described as focusing evaluation of estimate using image sharpness value.
Described image sharpness value is a kind of index reflecting plane of delineation definition and image border sharpness, and image sharpness value is higher, and the contrast of its details is higher, views and admires more clear.Further, the assessment mode of image sharpness value has a lot, such as depth assessment, gray scale assessment and gradient assessment etc., and the present embodiment is evaluated as example with gradient, and namely the image sharpness value of described default neighborhood equals the Grad summation of all picture points in default neighborhood.Wherein, gradient calculation can use tenengrad/sobel operator or PrewittGradientEdgeDetection operator, does not do detailed expansion here.
As an optional example, refer to Fig. 6, suppose that 8 dots in Fig. 6 a represent the human face characteristic point identified, then 8 little square frames in Fig. 6 b can represent the default neighborhood of human face characteristic point, and evaluation of estimate computing unit 330 calculates the image sharpness value of these default neighborhoods.It is pointed out that the size value of default neighborhood does not do concrete restriction here, can set according to the distance value of face to terminal, such as, suppose that face is 50m to the distance value of terminal, then the size that can arrange default neighborhood is 10*10 pixel.
Particularly, evaluation of estimate computing unit 330 calculates the image sharpness value of the default neighborhood of the human face characteristic point of each image.
Should understand ground, the peripheral region of human face characteristic point is that the definition of whole face requires the highest place, and therefore the present embodiment not only can accurately focus on face, accelerate focusing speed, further improves shooting effect.
Focus control unit 340, for by the focusing of described camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from.
Particularly, focus control unit 340 by the focusing of camera from focusing corresponding to the image being adjusted to maximum image sharpness value from.
In specific implementation process, focus control unit 340 can search out the image of maximum image sharpness value from each image by preset search mode, by the focusing of camera from focusing corresponding to the image being adjusted to the maximum image sharpness value searched out from.
Wherein, preset search mode can be the searching algorithm based on the degree of depth, gray scale or gradient, and described searching algorithm includes but not limited to hill-climbing algorithm, simulated annealing or genetic algorithm etc.Preferably, the preset search mode in the present embodiment based on searching algorithm be hill-climbing algorithm.
Described hill-climbing algorithm is a kind of local method preferentially, namely from current focusing from the image of correspondence, compare with the focusing of the surrounding image from correspondence, if the sharpness value of present image is larger, so return present image, as the image having maximum image sharpness value, otherwise just replace present image with the image of surrounding maximum image sharpness value, realize the object of climbing to the eminence on mountain peak by that analogy, until search out the image of maximum image sharpness value.Alternatively, the hill-climbing algorithm in the embodiment of the present invention can use RS searching algorithm, does not do detailed expansion here.
Fig. 4 is the structural representation of a kind of terminal in the embodiment of the present invention, and as shown in Figure 4, this terminal can comprise: at least one processor 401, such as CPU, at least one camera 403, memory 404, at least one communication bus 402.Wherein, communication bus 402 is for realizing the connection communication between these assemblies.Memory 404 can be high-speed RAM memory, also can be non-volatile memory (non-volatilememory), such as at least one magnetic disc store.Optionally, memory 404 can also be that at least one is positioned at the storage device away from aforementioned processor 401.Store batch processing code in memory 404, and processor 401 is for calling the program code stored in memory 404, for performing following operation:
Change camera focusing from and gather each focusing under image;
Identify the human face characteristic point in image described in each;
Calculate the focusing evaluation of estimate that image described in each is directed to its human face characteristic point;
By the focusing of described camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from.
Alternatively, processor 401 focusing that changes camera from and gather each focusing under the concrete operations of image be:
The focusing changing camera in default adjustable range from and gather each focusing under image.
Again alternatively, processor 401 calculates the concrete operations that image described in each is directed to the focusing evaluation of estimate of described human face characteristic point and is:
Calculate the image sharpness value of the default neighborhood of the human face characteristic point in image described in each.
Correspondingly, processor 401 by the focusing of described camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from concrete operations be:
By the focusing of described camera from focusing corresponding to the image being adjusted to maximum image sharpness value from.
Further, processor 401 by the focusing of described camera from focusing corresponding to the image being adjusted to maximum image sharpness value from concrete operations be:
From image described in each, the image of maximum image sharpness value is searched out by preset search mode;
By the focusing of described camera from focusing corresponding to the image being adjusted to the described maximum image sharpness value searched out from.
Again alternatively, the image sharpness value of described default neighborhood equals the Grad summation of all picture points in described default neighborhood.
The embodiment of the present invention, first the focusing changing camera from and gather each focusing under image, then the human face characteristic point in each image is identified, then the focusing evaluation of estimate that each image is directed to its human face characteristic point is calculated, and then by the focusing of camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from, can realize exactly camera being focused on face, improve shooting effect, improve the experience of user.
One of ordinary skill in the art will appreciate that all or part of flow process realized in above-described embodiment method, that the hardware that can carry out instruction relevant by computer program has come, described program can be stored in a computer read/write memory medium, this program, when performing, can comprise the flow process of the embodiment as above-mentioned each side method.Wherein, described storage medium can be magnetic disc, CD, read-only store-memory body (Read-OnlyMemory, ROM) or random store-memory body (RandomAccessMemory, RAM) etc.
Step in embodiment of the present invention method can be carried out order according to actual needs and be adjusted, merges and delete.
Unit in embodiment of the present invention device, can carry out merging, divide and deleting according to actual needs.
Unit described in the embodiment of the present invention, universal integrated circuit can be passed through, such as CPU (CentralProcessingUnit, central processing unit), or realized by ASIC (ApplicationSpecificIntegratedCircuit, application-specific integrated circuit (ASIC)).
Above disclosedly be only present pre-ferred embodiments, certainly can not limit the interest field of the present invention with this, therefore according to the equivalent variations that the claims in the present invention are done, still belong to the scope that the present invention is contained.
Claims (10)
1. a self-focusing method, is characterized in that, described method comprises:
Change camera focusing from and gather each focusing under image;
Identify the human face characteristic point in image described in each;
Calculate the focusing evaluation of estimate that image described in each is directed to its human face characteristic point;
By the focusing of described camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from.
2. the method for claim 1, is characterized in that, the focusing of described change camera from and gather each focusing under image, comprising:
The focusing changing camera in default adjustable range from and gather each focusing under image.
3. the method for claim 1, is characterized in that, described calculating image described in each is directed to the focusing evaluation of estimate of described human face characteristic point, comprising:
Calculate the image sharpness value of the default neighborhood of the human face characteristic point in image described in each;
Described by the focusing of described camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from, comprising:
By the focusing of described camera from focusing corresponding to the image being adjusted to maximum image sharpness value from.
4. method as claimed in claim 3, is characterized in that, described by the focusing of described camera from focusing corresponding to the image being adjusted to maximum image sharpness value from, comprising:
From image described in each, the image of maximum image sharpness value is searched out by preset search mode;
By the focusing of described camera from focusing corresponding to the image being adjusted to the described maximum image sharpness value searched out from.
5. the method for claim 1, is characterized in that, the image sharpness value of described default neighborhood equals the Grad summation of all picture points in described default neighborhood.
6. a terminal, is characterized in that, described terminal comprises:
Image acquisition units, for the focusing that changes camera from and gather each focusing under image;
Feature point recognition unit, for identifying the human face characteristic point in image described in each;
Evaluation of estimate computing unit, is directed to the focusing evaluation of estimate of its human face characteristic point for calculating image described in each;
Focus control unit, for by the focusing of described camera from focusing corresponding to the image being adjusted to maximum focusing evaluation of estimate from.
7. terminal as claimed in claim 6, is characterized in that, described image acquisition units, specifically for the focusing that changes camera in default adjustable range from and gather each focusing under image.
8. terminal as claimed in claim 6, is characterized in that, institute's evaluation values computing unit, specifically for calculating the image sharpness value of the default neighborhood of the human face characteristic point in image described in each;
Described focus control unit, specifically for by the focusing of described camera from focusing corresponding to the image being adjusted to maximum image sharpness value from.
9. terminal as claimed in claim 8, is characterized in that, described focus control unit, specifically for:
From image described in each, the image of maximum image sharpness value is searched out by preset search mode;
By the focusing of described camera from focusing corresponding to the image being adjusted to the described maximum image sharpness value searched out from.
10. terminal as claimed in claim 6, it is characterized in that, the image sharpness value of described default neighborhood equals the Grad summation of all picture points in described default neighborhood.
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