Title
3D Face Reconstruction from Front and Profile Image
Date of Award
2021
Degree Name
M.C.S. (Master of Computer Science)
Department
Department of Computer Science
Advisor/Chair
Mehdi R. Zargham
Abstract
Three dimensionality (3D) face modeling is an advanced and challenging feature for computer vision, and our goal is to implement it using various methods to bring 3D models closer to reality. Although many algorithms for construction of 3D model from two dimensional (2D) images are present, we propose a new approach using front and profile images with various image processing techniques for small computing devices. Basic methods such as resizing, denoise, overlay, blending etc. will be used for generation of the UV-map of texture, but as its core element, it relies on the Haar Cascade face detection algorithm. For structure or mesh, a shape detector with 68 landmarks to identify the shape of the face in the image and compare it with our own dataset for most similar structure. Though we have achieved good results from the proposed approach, there is potential to improve by making the model an identical replica.
Keywords
2D to 3D, Haar Cascade Classifier, OpenCV, dlib, UV-map and Mesh
Rights Statement
Copyright © 2021, author
Recommended Citation
Dasgupta, Sankarshan, "3D Face Reconstruction from Front and Profile Image" (2021). Graduate Theses and Dissertations. 6990.
https://ecommons.udayton.edu/graduate_theses/6990