3D face pose alignment algorithm and device based on artificial intelligence
A face pose and artificial intelligence technology, applied in 3D modeling, computing, image data processing, etc., can solve problems such as slow generation speed and poor quality of 3D models, and achieve the effect of improving computing speed and image quality
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Embodiment 1
[0058] This embodiment provides an artificial intelligence-based 3D face pose alignment device. The 3D facial posture alignment device includes a 3D shooting device, an adjustment module, a recognition module, an acquisition module, a setting module and a circulation module.
[0059] The 3D shooting device is used to acquire several frames of 3D images of a shooting target.
[0060] In this embodiment, the 3D camera device is a mobile phone with a 3D camera, and the 3D camera device may also be a 3D SLR camera or a laser radar.
[0061] The 3D images of the several frames are acquired by 3D camera, the mobile phone shoots 3D video streams, and the image of each frame is the 3D image.
[0062] The adjustment module is used to adjust the spatial position of each frame of 3D images using artificial intelligence algorithms so that the 3D images of each frame are at the target position, and in the 3D images at the target position, any adjacent two frames of 3D images include A mu...
Embodiment 2
[0084] This embodiment is basically the same as Embodiment 1, the only difference is:
[0085] The 3D face posture alignment device includes a selection module, a setting module and a circulation module,
[0086] The selection module is used to select a target 3D image;
[0087] The identification module is used to identify the feature points of the target 3D image and adjacent frame images of the target 3D image;
[0088] The adjustment module is used to adjust the spatial position of adjacent frame images of the target 3D image to the spatial position where the target 3D image is located by aligning corresponding feature points using an artificial intelligence algorithm, and the spatial position where the target 3D image is located is the target position;
[0089] The identification module is also used to identify the feature points of the processed image, the processed image is an adjacent frame image of the 3D image adjusted to the target position;
[0090] The loop modu...
Embodiment 3
[0106] This embodiment is basically the same as Embodiment 1, the only difference is:
[0107] The 3D image is acquired by a mobile terminal with a 3D camera, and the mobile terminal includes a motion sensor, an acquisition module and a calculation module.
[0108] The motion sensor is used to obtain the motion trajectory of the mobile terminal;
[0109] For a target 3D image, the acquiring module is configured to acquire the position of the target 3D image and the next frame of the 3D image of the target 3D image on the motion track and the shooting direction of the 3D camera;
[0110] The calculation module is used to obtain the position of the target 3D image and the corresponding feature point on the next frame of the 3D image of the target 3D image according to the position on the motion track and the shooting direction of the 3D camera;
PUM
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Abstract
Description
Claims
Application Information
![application no application](https://static-eureka.patsnap.com/ssr/23.2.0/_nuxt/application.06fe782c.png)
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