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3D Face Reconstruction From Front And Profile Image

Abstract Details

2021, Master of Computer Science (M.C.S.), University of Dayton, Computer Science.
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.
Mehdi R. Zargham (Advisor)
Raghava Gowda (Committee Member)
Tom Ongwere (Committee Member)
51 p.

Recommended Citations

Citations

  • Dasgupta, S. (2021). 3D Face Reconstruction From Front And Profile Image [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1626689472561706

    APA Style (7th edition)

  • Dasgupta, Sankarshan. 3D Face Reconstruction From Front And Profile Image. 2021. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1626689472561706.

    MLA Style (8th edition)

  • Dasgupta, Sankarshan. "3D Face Reconstruction From Front And Profile Image." Master's thesis, University of Dayton, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1626689472561706

    Chicago Manual of Style (17th edition)