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You searched for id:"handle:1805/19940". One record found.

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IUPUI

1. Gorrila, Anusha. Data Driven Dense 3D Facial Reconstruction From 3D Skull Shape.

Degree: 2019, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

This thesis explores a data driven machine learning based solution for Facial reconstruction from three dimensional (3D) skull shape for recognizing or identifying unknown subjects during forensic investigation. With over 8000 unidentified bodies during the past 3 decades, facial reconstruction of disintegrated bodies in helping with identification has been a critical issue for forensic practitioners. Historically, clay modelling has been used for facial reconstruction that not only requires an expert in the field but also demands a substantial amount of time for modelling, even after acquiring the skull model. Such manual reconstruction typically takes from a month to over 3 months of time and effort. The solution presented in this thesis uses 3D Cone Beam Computed Tomography (CBCT) data collected from many people to build a model of the relationship of facial skin to skull bone over a dense set of locations on the face. It then uses this skin-to-bone relationship model learned from the data to reconstruct the predicted face model from a skull shape of an unknown subject. The thesis also extends the algorithm in a way that could help modify the reconstructed face model interactively to account for the effects of age or weight. This uses the predicted face model as a starting point and creates different hypotheses of the facial appearances for different physical attributes. Attributes like age and body mass index (BMI) are used to show the physical facial appearance changes with the help of a tool we constructed. This could improve the identification process. The thesis also presents a methods designed for testing and validating the facial reconstruction algorithm.

Advisors/Committee Members: Tuceryan, Mihran, Fang, Shiaofen, Zheng, Jiang-Yu.

Subjects/Keywords: Facial reconstruction; 3d face; Face shape; Cranio-facial reconstruction; Face appearance change

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gorrila, A. (2019). Data Driven Dense 3D Facial Reconstruction From 3D Skull Shape. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/19940

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Gorrila, Anusha. “Data Driven Dense 3D Facial Reconstruction From 3D Skull Shape.” 2019. Thesis, IUPUI. Accessed August 24, 2019. http://hdl.handle.net/1805/19940.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Gorrila, Anusha. “Data Driven Dense 3D Facial Reconstruction From 3D Skull Shape.” 2019. Web. 24 Aug 2019.

Vancouver:

Gorrila A. Data Driven Dense 3D Facial Reconstruction From 3D Skull Shape. [Internet] [Thesis]. IUPUI; 2019. [cited 2019 Aug 24]. Available from: http://hdl.handle.net/1805/19940.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gorrila A. Data Driven Dense 3D Facial Reconstruction From 3D Skull Shape. [Thesis]. IUPUI; 2019. Available from: http://hdl.handle.net/1805/19940

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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