CN108510500A - A kind of hair figure layer process method and system of the virtual figure image based on face complexion detection - Google Patents
A kind of hair figure layer process method and system of the virtual figure image based on face complexion detection Download PDFInfo
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Abstract
A kind of hair figure layer process method of the virtual figure image based on face complexion detection, which is characterized in that including detecting human face region and characteristic point；Area of skin color processing；Area of skin color and feature dot profile scratch the information such as head mask mask, obtain face mask mask；The processing of face mask, edge transition are natural；Each figure layer is rendered, final image is generated.The present invention provides a kind of hair figure layer process method and system of the virtual figure image based on face complexion detection.Since the difficulty of the stingy figure of hair in scratching head is larger, scratching the effect of hair can become unnatural due to the influence of various backgrounds and clothes, so present invention employs discount granting body and clothes figure layer subsequent scheme, cover in unnatural hair portion so that the figure image of generation is more beautiful.
Description
Technical Field
The invention relates to the field of computer image processing, in particular to a method and a system for processing a hair image layer of a virtual human image based on human face skin color detection.
Background
With the continuous development of artificial intelligence technology, image processing plays an increasingly important role in our daily life. The virtual character image hair processing is an important field in image processing, and before the virtual character image hair processing, human face, feature points and skin color area detection are required. The detection of the human face and the characteristic points is mainly based on a detection technology of machine learning. The skin color detection is mainly a process of selecting a corresponding color range in an image as a skin color according to the inherent color of the skin, namely selecting pixel points of an area where the human skin is located in the image.
The existing scheme mainly comprises the following steps: detecting face information of a current frame picture of a picture, obtaining an approximate outline of a face region according to an Active Shape Model (ASM) algorithm, estimating a skin region of the face according to the outline region, avoiding some regions (such as eyes, eyebrows and lip regions) which are possibly misled, performing threshold segmentation on the estimated skin color region of the face according to a skin threshold empirical parameter which is set in advance according to the estimated skin color region of the face, uniformly selecting a certain number of skin color seeds in different skin color regions, and performing spreading and detection on a peripheral connected region according to the selected seed points, so that all connected skin color regions can be detected; scheme II: the method comprises the steps of obtaining a face area from a gray-scale image of a current frame picture of the picture, calculating a histogram of the face area, finding approximate valley points of the histogram, and dividing a skin color area and a non-skin color area in the face area through the approximate valley points. However, the above two schemes have great difficulty in hair matting in matting, and the effect of hair matting can become unnatural due to the influence of various backgrounds and clothes.
Disclosure of Invention
The invention provides a method for processing a hair layer of a virtual character based on human face skin color detection, which comprises the following steps,
detecting a face area and feature points;
processing a skin color area;
obtaining a face mask by using the skin color area, the feature point outline, the head-scratching mask and other information;
face mask processing, and natural edge transition;
and rendering each layer to generate a final image.
And detecting the face region of the picture, and obtaining feature points of the five sense organs and the face contour by using a face region detection and feature point detection technology based on machine learning.
The skin color area processing comprises the following steps of,
combining the characteristic points and the brightness information to obtain an initial skin color area;
combining the brightness and the color information in the initial skin color area to obtain an accurate skin color area;
estimating an ellipsoid space of Skin Color according to a Skin Color Modeling method of a Skin Color Digital Photographic image of Skin Color Modeling based on the Skin Color area;
and solving by a max flow/min cut method in graph cut (graph cut) based on the spatial distance of the skin color ellipsoid to obtain an optimized skin color area.
The initial skin color region is obtained by combining the feature points and the brightness information, including,
255 is filled in a polygonal region surrounded by the feature points 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,45,46,47,42,27,39,40,41,36, and 0 is filled in a polygonal region surrounded by the feature points 48,49,50,51,52,53,54,55,56,57,58, 59; the region with luminance value L <30 is filled with 0 to obtain the initial skin color region.
The combination of luminance and color information in the initial skin tone region yields an accurate skin tone region including,
counting to obtain a brightness point set of a skin color area, wherein the brightness and position information of each pixel in the skin color area are recorded;
sorting the brightness point sets from small to large according to the brightness values, and removing 15% -20% of over-black and 10% -15% of over-bright pixel points;
selecting a middle brightness point set of a skin color area as a seed point set, searching the position of a middle point according to the point set of the skin color area, and selecting a left-right plus-minus 5 range as the seed point set;
selecting a new candidate skin color area, selecting feature points 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,27,26,25,24,23,22,21,20,19,18 as outer contours, pulling down portions of 18, 19, 20, 21, 22 (left eyebrow) and 23, 24, 25, 26, 27 (right eyebrow), removing portions surrounded by 31,32,33,34,35, 36 (nose), and removing portions surrounded by 37,38,39,40,41, 42 (right eye) and 43,44,45,46,47, 48 (left eye);
traversing the seed point set, and taking all pixels with the BGR color distance less than 50 from the seed point in the candidate skin color region obtained in the step (d) as a new skin color region.
The method for Modeling Skin Color Modeling of digital Photographic Images based on the Skin Color area estimates the ellipsoid space of the Skin Color according to the Skin Color of the digital Photographic Images, wherein the ellipsoid space model of the Skin Color is as follows:
Φ(X)＝[X-Ψ]TA-l[X-Ψ]
wherein,
x1.. Xn represents the color that appears in the skin color region, and f (Xi) represents the number of times the color Xi appears.
Estimating an ellipsoid spatial model of skin color based on the skin color region;
and substituting each pixel of the matting mask into the ellipsoid space model of the skin color to solve to obtain the ellipsoid space distance between each pixel and the skin color.
The smoother skin color area is obtained by solving by a maximum flow minimum cut (maxflow/min cut) method in graph cut (graph cut) based on the spatial distance of the skin color ellipsoid, comprising,
setting a smooth item to represent the weight between adjacent points,
dist1 represents the color difference, σ, between adjacent pixels1set to 15, α is set to 20;
setting weight values between the data items, the representative points and the Source Sink (Source/Sink),
dist2 represents the ellipsoid spatial distance (5c) of the pixel from skin color, with β set to 1, δ2Set to 15.
The mask processing of the human face, the transition of the edge is natural, including,
performing operation of expanding the face mask for 7 circles and then reducing the face mask for 7 circles;
performing Gaussian blur of 5x5 for 2 times to ensure the transition of the edges of the human face to be natural;
and obtaining the processed face mask and the face four-channel picture.
And rendering each layer to generate a final image, including,
pasting a real head map layer, and matting a four-channel picture obtained by a head mask;
pasting virtual body and clothes layers;
pasting a real face layer on the top layer;
the final image creates the effect.
The invention provides a hair layer processing system of a virtual character based on human face skin color detection, which comprises,
the detection module is used for detecting a face area and feature points;
the area processing module is used for processing the skin color area;
the head scratching processing module is used for obtaining a face mask by using information such as a skin color area, a characteristic point outline, a head scratching mask and the like;
the human face mask processing module is used for human face mask processing and natural edge transition;
and the rendering module is used for rendering each layer to generate a final image.
The invention provides a product for processing a hair layer of a virtual character based on human face skin color detection, which comprises images suitable for virtual reality, virtual fitting, virtual social contact, clothes, shoes and accessories and non-real contact measuring bodies.
Has the advantages that:
the invention provides a method and a system for processing a hair layer of a virtual character based on human face skin color detection. Because the difficulty of hair matting in head matting is higher, the effect of hair matting becomes unnatural due to the influence of various backgrounds and clothes, so the invention adopts the scheme that the head is distributed behind the body and the clothes layer, and the unnatural hair part is covered, so that the generated figure image is more beautiful.
Description of the drawings:
FIG. 1 is a schematic diagram of feature points of the five sense organs and facial contours
FIG. 2 is a schematic diagram of a mask
FIG. 3 is a schematic view of an initial skin tone region
FIG. 4 is a schematic diagram of an accurate skin tone region
FIG. 5 is a schematic view of a new skin tone region
FIG. 6 is a schematic view of the ellipsoid spatial distance between each pixel and skin tone
FIG. 7 is a schematic diagram of optimizing skin tone regions
FIG. 8 is a schematic diagram of face mask
FIG. 9 is a schematic diagram of processed face mask
FIG. 10 is a four-channel schematic diagram of a processed face
FIG. 11 is a final image generation effect diagram
Detailed Description
The embodiment provides a method for processing a hair layer of a virtual character based on human face skin color detection, which comprises the following steps,
detecting a face area and feature points;
processing a skin color area;
obtaining a face mask by using the skin color area, the feature point outline, the head-scratching mask and other information;
face mask processing, and natural edge transition;
and rendering each layer to generate a final image.
In a preferred embodiment, the face region of the detected picture in this embodiment uses a face region detection and feature point detection technology based on machine learning to obtain feature points of five sense organs and face contour.
The preferred embodiment, the skin tone region processing in this embodiment, includes,
combining the characteristic points and the brightness information to obtain an initial skin color area;
combining the brightness and the color information in the initial skin color area to obtain an accurate skin color area;
estimating an ellipsoid space of Skin Color according to a Skin Color Modeling method of a Skin Color Digital Photographic image of Skin Color Modeling based on the Skin Color area;
and solving by a max flow/min cut method in graph cut (graph cut) based on the spatial distance of the skin color ellipsoid to obtain an optimized skin color area.
In a preferred embodiment, the initial skin color region is obtained by combining the feature points and the luminance information in this embodiment, including filling 255 in a polygonal region surrounded by the feature points 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,45,46,47,42,27,39,40,41,36, and filling 0 in a polygonal region surrounded by the feature points 48,49,50,51,52,53,54,55,56,57,58, 59; the region with luminance value L <30 is filled with 0 to obtain the initial skin color region.
In the preferred embodiment, the present embodiment combines the luminance and color information in the initial skin color region to obtain the accurate skin color region, including,
counting to obtain a brightness point set of a skin color area, wherein the brightness and position information of each pixel in the skin color area are recorded;
sorting the brightness point sets from small to large according to the brightness values, and removing 15% -20% of over-black and 10% -15% of over-bright pixel points;
selecting a middle brightness point set of a skin color area as a seed point set, searching the position of a middle point according to the point set of the skin color area, and selecting a left-right plus-minus 5 range as the seed point set;
selecting a new candidate skin color area, selecting feature points 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,27,26,25,24,23,22,21,20,19,18 as outer contours, pulling down portions of 18, 19, 20, 21, 22 (left eyebrow) and 23, 24, 25, 26, 27 (right eyebrow), removing portions surrounded by 31,32,33,34,35, 36 (nose), and removing portions surrounded by 37,38,39,40,41, 42 (right eye) and 43,44,45,46,47, 48 (left eye);
traversing the seed point set, and taking all pixels with the BGR color distance less than 50 from the seed point in the candidate skin color region obtained in the step (d) as a new skin color region.
In the preferred embodiment, based on the skin color region, the ellipsoid space of the skin color is estimated according to the skin color Modeling of Digital Photographic Images, and the ellipsoid space model of the skin color is:
Φ(X)＝[X-Ψ]TA-l[X-Ψ]
wherein,
x1.. Xn represents the color that appears in the skin color region, and f (Xi) represents the number of times the color Xi appears.
Estimating an ellipsoid spatial model of skin color based on the skin color region;
and substituting each pixel of the matting mask into the ellipsoid space model of the skin color to solve to obtain the ellipsoid space distance between each pixel and the skin color.
In the preferred embodiment, in this embodiment, based on the spatial distance of the skin color ellipsoid, a smoother skin color region is obtained by solving with a max flow minimum cut (max flow/min cut) method in graph cut (graph cut), including,
setting a smooth item to represent the weight between adjacent points,
dist1 represents the color difference, σ, between adjacent pixels1set to 15, α is set to 20;
setting weight values between the data items, the representative points and the Source Sink (Source/Sink),
dist2 represents the ellipsoid spatial distance (5c) of the pixel from skin color, with β set to 1, δ2Set to 15.
In the preferred embodiment, the face mask processing, edge transition natural, including,
performing operation of expanding the face mask for 7 circles and then reducing the face mask for 7 circles;
performing Gaussian blur of 5x5 for 2 times to ensure the transition of the edges of the human face to be natural;
and obtaining the processed face mask and the face four-channel picture.
In the preferred embodiment, each layer is rendered in this embodiment to generate a final avatar, including,
pasting a real head map layer, and matting a four-channel picture obtained by a head mask;
pasting virtual body and clothes layers;
pasting a real face layer on the top layer;
the final image creates the effect.
The embodiment provides a hair layer processing system of virtual character based on human face skin color detection, which comprises,
the detection module is used for detecting a face area and feature points;
the area processing module is used for processing the skin color area;
the head scratching processing module is used for obtaining a face mask by using information such as a skin color area, a characteristic point outline, a head scratching mask and the like;
the human face mask processing module is used for human face mask processing and natural edge transition;
and the rendering module is used for rendering each layer to generate a final image.
The embodiment provides a product for processing the hair layer of a virtual character based on human face skin color detection, which comprises images suitable for virtual reality, virtual fitting, virtual social contact, clothes, shoes and accessories and non-real contact measuring bodies.
Claims (11)
1. A method for processing the hair layer of virtual figure based on human face skin color detection is characterized by comprising the following steps,
detecting a face area and feature points;
processing a skin color area;
obtaining a face mask by using the skin color area, the feature point outline, the head-scratching mask and other information;
face mask processing, and natural edge transition;
and rendering each layer to generate a final image.
2. The method as claimed in claim 1, wherein the facial region of the detected picture is processed by using facial region detection and feature point detection based on machine learning to obtain feature points of five sense organs and facial contour.
3. The method for processing the hair layer of the virtual character based on the human face skin color detection as claimed in claim 1, wherein the processing of the skin color area comprises,
combining the characteristic points and the brightness information to obtain an initial skin color area;
combining the brightness and the color information in the initial skin color area to obtain an accurate skin color area;
estimating an ellipsoid space of Skin Color according to a Skin Color Modeling method of a Skin Color Digital Photographic image of Skin Color Modeling based on the Skin Color area;
and solving by a maximum flow minimum cut (max flow/min cut) method in graph cuts (graph cuts) based on the spatial distance of the skin color ellipsoid to obtain an optimized skin color area.
4. A method as claimed in claim 3, wherein said combining feature points and luminance information to obtain an initial skin color region comprises filling 255 in a polygonal region surrounded by feature points 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,45,46,47,42,27,39,40,41,36 and filling 0 in a polygonal region surrounded by feature points 48,49,50,51,52,53,54,55,56,57,58, 59; the region with luminance value L <30 is filled with 0 to obtain the initial skin color region.
5. The method as claimed in claim 3, wherein said combining brightness and color information in the initial skin color region to obtain the accurate skin color region comprises,
counting to obtain a brightness point set of a skin color area, wherein the brightness and position information of each pixel in the skin color area are recorded;
sorting the brightness point sets from small to large according to the brightness values, and removing 15% -20% of over-black and 10% -15% of over-bright pixel points;
selecting a middle brightness point set of a skin color area as a seed point set, searching the position of a middle point according to the point set of the skin color area, and selecting a left-right plus-minus 5 range as the seed point set;
selecting a new candidate skin color area, selecting feature points 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,27,26,25,24,23,22,21,20,19,18 as outer contours, pulling down portions of 18, 19, 20, 21, 22 (left eyebrow) and 23, 24, 25, 26, 27 (right eyebrow), removing portions surrounded by 31,32,33,34,35, 36 (nose), and removing portions surrounded by 37,38,39,40,41, 42 (right eye) and 43,44,45,46,47, 48 (left eye);
traversing the seed point set, and taking all pixels with the BGR color distance less than 50 from the seed point in the candidate skin color region obtained in the step (d) as a new skin color region.
6. The method for processing the hair layer of the virtual character based on the human face Skin Color detection as claimed in claim 3, wherein the ellipsoid space of the Skin Color is estimated according to the Skin Color modeling Digital Photographic Images method of the Digital Photographic image based on the Skin Color area, and the ellipsoid space model of the Skin Color is as follows:
Φ(X)＝[X-Ψ]ΤΛ-1[X-Ψ]
wherein,
x1.. Xn represents the color that appears in the skin color region, and f (Xi) represents the number of times the color Xi appears.
Estimating an ellipsoid spatial model of skin color based on the skin color region;
and substituting each pixel of the matting mask into the ellipsoid space model of the skin color to solve to obtain the ellipsoid space distance between each pixel and the skin color.
7. The method for processing the hair layer of the virtual character based on the human face skin color detection as claimed in claim 3, wherein a smoother skin color region is obtained by solving with a max flow min cut method in a graph cut based on a skin color ellipsoid spatial distance, comprising,
setting a smooth item to represent the weight between adjacent points,
dist1 represents the color difference, σ, between adjacent pixels1set to 15, α is set to 20;
setting weight values between the data items, the representative points and the Source Sink (Source/Sink),
dist2 represents the ellipsoid spatial distance (5c) of the pixel from skin color, with β set to 1, δ2Set to 15.
8. The method for processing the hair layer of the virtual character based on the human face complexion detection as claimed in claim 1, wherein the human face mask is processed, the edge transition is natural, comprising,
performing operation of expanding the face mask for 7 circles and then reducing the face mask for 7 circles;
performing Gaussian blur of 5x5 for 2 times to ensure the transition of the edges of the human face to be natural;
and obtaining the processed face mask and the face four-channel picture.
9. The method of claim 1, wherein rendering layers to generate a final avatar comprises,
pasting a real head map layer, and matting a four-channel picture obtained by a head mask;
pasting virtual body and clothes layers;
pasting a real face layer on the top layer;
the final image creates the effect.
10. A system for processing a hair layer of an virtual character based on human face skin color detection as claimed in claim 1, comprising,
the detection module is used for detecting a face area and feature points;
the area processing module is used for processing the skin color area;
a head-scratching processing module, a skin color area, a characteristic point outline, a head-scratching mask and other information to obtain a face mask;
the human face mask processing module is used for processing the human face mask and enabling the edge transition to be natural;
and the rendering module is used for rendering each layer to generate a final image.
11. A product for processing a hair layer of a virtual figure based on face skin color detection is characterized by comprising images suitable for virtual reality, virtual fitting, virtual social contact, clothes, shoes, accessories and non-real contact measuring bodies, and the product for processing the hair layer of the virtual figure based on face skin color detection is the method and the system for processing the hair layer of the virtual figure based on face skin color detection in any one of claims 1 to 9.
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