eprintid: 2653
rev_number: 22
eprint_status: archive
userid: 318
dir: disk0/00/00/26/53
datestamp: 2017-12-08 05:04:25
lastmod: 2017-12-08 05:04:25
status_changed: 2017-12-08 05:04:25
type: book_section
metadata_visibility: show
creators_name: Dinh, Quang Huy
creators_name: Ma, Thi Chau
creators_name: Bui, The Duy
creators_name: Nguyen, Trong Toan
creators_name: Nguyen, Dinh Tu
creators_id: chaumt@vnu.edu.vn
creators_id: duybt@vnu.edu.vn
title: Facial soft tissue thicknesses prediction using anthropometric distances
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: Predicting the face of an unidentified individual from its skeletal remains is a difficult matter. Obviously, if the soft tissue thicknesses at every location at the skull are known, we can easily rebuild the face from the skull model. Thus, the problem turns out to be predicting the soft tissue thicknesses for any given skull. With the rapid development of the computer, different techniques are being used in the community for prediction tasks and in recent years the concept of neural networks has emerged as one of them. The principal strength of the neural network is its ability to find patterns and irregularities as well as detecting multi-dimensional non-linear connections in data. In this paper, we propose a method of applying neural networks to predict the soft tissue thicknesses for facial reconstruction. We use the distances between anthropometric locations at the skull as input, and the soft tissue thicknesses as output, as this format is suitable for many machine learning mechanisms. These data is collected and measured from candidates using the Computed Tomography (CT) technique.
date: 2011
publisher: SpringerLink
full_text_status: none
pres_type: poster
pagerange: 117-126
event_title: New Challenges for Intelligent Information and Database Systems. Berlin, Heidelberg
event_type: other
refereed: TRUE
book_title: New Challenges for Intelligent Information and Database Systems
related_url_url: https://link.springer.com/chapter/10.1007/978-3-642-19953-0_12
citation:   Dinh, Quang Huy and Ma, Thi Chau and Bui, The Duy and Nguyen, Trong Toan and Nguyen, Dinh Tu  (2011) Facial soft tissue thicknesses prediction using anthropometric distances.   In:  New Challenges for Intelligent Information and Database Systems.   SpringerLink, pp. 117-126.