Depth camera-based human-body model acquisition method and network virtual fitting system
First Claim
1. A human body model acquisition method based on depth cameras, comprising the following steps:
- step S1;
generating mark points covering a model body surface and for determining features of the model body surface on the model body surface, and collecting depth images of the model body from a plurality of angles by using the depth cameras to acquire a depth image sequence that covers the model body surface and contains the mark points;
step S2;
carrying target depth information point cloud grid reconstruction on frames of depth images in the depth image sequence; and
step S3;
mosaicing the reconstructed frames of depth images into a three-dimensional model of the model body according to the mark points in the reconstructed frames of depth images;
wherein prior to step S2, the method further comprises the following steps;
preprocessing the frames of depth images in the depth image sequence acquired in step S1 according to the following steps;
estimating the position of the model body in the depth image through segmenting a foreground by a median;
placing a model body outline generating seed at the center of the position;
diffusing the model body outline by depth search based on smoothness constraint, generating an accurate model body outline, extracting the model body outline, and meanwhile removing the rest parts in the depth image as backgrounds;
wherein when the model body outline of the next frame of depth image is extracted, extracting the model body outline in combination with the outline extraction result of the previous frame;
wherein when the depth image is a rigid-body depth image;
the step S1 is specifically as follows;
irradiating the model body from 360 degrees by using structured light generated by the depth cameras, so as to generate the mark points for determining the feature information of irradiation sites on the irradiation sites; and
collecting the depth images of the irradiation sites by using the depth cameras during the irradiation to acquire the depth image sequence that covers the model body surface and contains the mark points;
the step S3 is specifically as follows;
mosaicing the mark points with correlation higher than a set value according to the correlation of the mark points in every two adjacent frames of depth images in the reconstructed frames of depth images, and deleting the mark points with correlation lower than the set value, so as to mosaic the frames of depth images into the three-dimensional model of the model body;
when the depth image is a non-rigid-body depth image;
the step S1 is specifically as follows;
irradiating the model body from 360 degrees by using light spots of random lattices generated by the depth cameras, so as to generate the mark points for determining the feature information of irradiation sites on the irradiation sites; and
collecting the depth images of the irradiation sites by using the depth cameras during the irradiation to acquire the depth image sequence that covers the model body from 360 degrees and contains the mark points; and
the step S3 is specifically as follows;
mosaicing the mark points with correlation higher than the set value according to the correlation of the mark points in every two adjacent frames of depth images in the reconstructed frames of depth images, and deleting the mark points with correlation lower than the set value, so as to mosaic the frames of depth images into the three-dimensional model of the model body.
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Abstract
The present invention relates to a human body model acquisition method and a virtual network fitting system based on depth cameras. The method includes the following steps: step S1: generating mark points covering a model body surface and used for determining features of the model body surface on the model body surface, meanwhile collecting depth images of the model body from a plurality of angles by using the depth cameras to acquire a depth image sequence that covers the model body surface and contains the mark points; step S2: carrying target depth information point cloud grid reconstruction on frames of depth images in the depth image sequence; and step S3: mosaicing the reconstructed frames of depth images into a three-dimensional model of the model body according to the mark points in the reconstructed frames of depth images. Compared with the prior art, by adopting the human body model acquisition method and the virtual network fitting system based on the depth cameras provided by the present invention, the accurate three-dimensional human body model and the accurate three-dimensional garment model can be acquired, and virtual fitting is carried out accordingly to acquire a real fitting effect.
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Citations
20 Claims
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1. A human body model acquisition method based on depth cameras, comprising the following steps:
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step S1;
generating mark points covering a model body surface and for determining features of the model body surface on the model body surface, and collecting depth images of the model body from a plurality of angles by using the depth cameras to acquire a depth image sequence that covers the model body surface and contains the mark points;step S2;
carrying target depth information point cloud grid reconstruction on frames of depth images in the depth image sequence; andstep S3;
mosaicing the reconstructed frames of depth images into a three-dimensional model of the model body according to the mark points in the reconstructed frames of depth images;wherein prior to step S2, the method further comprises the following steps; preprocessing the frames of depth images in the depth image sequence acquired in step S1 according to the following steps; estimating the position of the model body in the depth image through segmenting a foreground by a median; placing a model body outline generating seed at the center of the position; diffusing the model body outline by depth search based on smoothness constraint, generating an accurate model body outline, extracting the model body outline, and meanwhile removing the rest parts in the depth image as backgrounds; wherein when the model body outline of the next frame of depth image is extracted, extracting the model body outline in combination with the outline extraction result of the previous frame; wherein when the depth image is a rigid-body depth image; the step S1 is specifically as follows; irradiating the model body from 360 degrees by using structured light generated by the depth cameras, so as to generate the mark points for determining the feature information of irradiation sites on the irradiation sites; and collecting the depth images of the irradiation sites by using the depth cameras during the irradiation to acquire the depth image sequence that covers the model body surface and contains the mark points; the step S3 is specifically as follows; mosaicing the mark points with correlation higher than a set value according to the correlation of the mark points in every two adjacent frames of depth images in the reconstructed frames of depth images, and deleting the mark points with correlation lower than the set value, so as to mosaic the frames of depth images into the three-dimensional model of the model body; when the depth image is a non-rigid-body depth image; the step S1 is specifically as follows; irradiating the model body from 360 degrees by using light spots of random lattices generated by the depth cameras, so as to generate the mark points for determining the feature information of irradiation sites on the irradiation sites; and collecting the depth images of the irradiation sites by using the depth cameras during the irradiation to acquire the depth image sequence that covers the model body from 360 degrees and contains the mark points; and the step S3 is specifically as follows; mosaicing the mark points with correlation higher than the set value according to the correlation of the mark points in every two adjacent frames of depth images in the reconstructed frames of depth images, and deleting the mark points with correlation lower than the set value, so as to mosaic the frames of depth images into the three-dimensional model of the model body. - View Dependent Claims (2, 3, 4, 5)
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6. A human body model acquisition method based on depth cameras, comprising the following steps:
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step S1;
generating mark points covering a model body surface and used for determining features of the model body surface on the model body surface, meanwhile collecting depth images of the model body from a plurality of angles by using the depth cameras to acquire a depth image sequence that covers the model body surface and contains the mark points;step S2;
carrying target depth information point cloud grid reconstruction on frames of depth images in the depth image sequence; andstep S3;
mosaicing the reconstructed frames of depth images into a three-dimensional model of the model body according to the mark points in the reconstructed frames of depth images. - View Dependent Claims (7, 8, 9, 10, 11, 12, 13, 14)
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15. A virtual network fitting method based on depth cameras, comprising
collecting a depth image sequence that covers a model body from 360 degrees; -
carrying target depth information point cloud grid reconstruction on each frame of depth image in the depth image sequence; mosaicing the reconstructed frames of depth images into a three-dimensional model of the model body; acquiring a three-dimensional garment model; matching the three-dimensional garment model with the three-dimensional model of the model body to generate a three-dimensional model of fitting effects; and outputting the three-dimensional model of fitting effects through a network. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification