Title:
3D Reconstruction Of the Human Torso From Four Orthogonal Model Views Captured Using a Stationary RGB-D Camera
3D Reconstruction Of the Human Torso From Four Orthogonal Model Views Captured Using a Stationary RGB-D Camera
Author(s)
Attia, Shehab
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Abstract
Digital 3D models of the human body can be used to measure anthropometric features to
diagnose diseases. Circumference measurements of body parts can only be obtained from
360-degree spin 3D models. These type of models are created using a combination of scanning
hardware and stitching software. Current stitching techniques use an Iterative Closest Point
algorithm on manually or automatically generated registration landmarks, provided that there is a
rotation angle difference of 60 degrees or less between adjacent frames for sufficiently matching
features. This paper proposes a method to stitch four orthogonal (90-degree) views captured
using one Kinect camera by iteratively translating and rotating adjacent frames to minimize the
Root Mean Square Error between the contours of the torso in 2D planes. Future work will
involve mending holes in the stitched models and solving the shear transformation to improve
results on non-rigid bodies.
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Date Issued
2019-05
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Resource Type
Text
Resource Subtype
Undergraduate Thesis