English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Because of complexity and motility of human body surface, reconstruction of human body surface cannot be implemented perfectly through current existing algorithms compared to the ordinary objects. Also when we use Kinect camera to obtain the three-dimensional point cloud of human body, it is easy to be affected by all kinds of random noise due to the camera itself and the influence of environmental factors. Thus, to improve the current algorithms, this paper proposes a 3D point cloud registration algorithm based on depth image noise reduction and a 3D surface reconstruction method based on the improved SDF and Poisson optimization. The key points of the paper are as follows: (1) the depth image of the human body is obtained through Kinect camera, and the minimum energy is calculated by using the energy model and Gauss-Newton Algorithm to implement noise reduction for depth image. Then, the global registration is carried out by using the curve interpolation method to minimize the error in the point cloud registration. (2) By using the weight optimized directional distance function to combine the point clouds, the 3D human body surface is reconstructed through the estimation model of Poisson optimization to improve the continuity and completeness of the 3D curve.

Noise Reduction of 3D Human Body Surface Reconstruction Algorithm and Surface Continuous Optimization