3D facial model exaggeration builder for small or large sized model manufacturing

Lee, Won-Sook; Soon, Andrew; Zhu, Lijia

doi:10.1007/s10055-007-0071-9

Cited by 1 publication

(1 citation statement)

References 21 publications

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“…With the thriving developments of the applications in virtual reality such as 3D films, virtual Human-Machine Interaction (Essabbah et al 2014;Hernoux and Christmann 2015) and virtual agents (Chen et al 2016;Qu et al 2013), 3D human face analysis is considered to be one of the most important researches (Lee et al 2007) in this area. Compared to the analysis of 2D facial data, 3D facial analysis can achieve higher accuracy and efficiency than its equivalent 2D methods through the addition of another dimension.…”

Section: Introductionmentioning

confidence: 99%

Dense 3D facial reconstruction from a single depth image in unconstrained environment

Shu

Wang

et al. 2017

Virtual Reality

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With the increasing demands of applications in virtual reality such as 3D films, virtual Human-Machine Interactions and virtual agents, the analysis of 3D human face analysis is considered to be more and more important as a fundamental step for those virtual reality tasks. Due to information provided by an additional dimension, 3D facial reconstruction enables aforementioned tasks to be achieved with higher accuracy than those based on 2D facial analysis. The denser the 3D facial model is, the more information it could provide. However, most existing dense 3D facial reconstruction methods require complicated processing and high system cost. To this end, this paper presents a novel method that simplifies the process of dense 3D facial reconstruction by employing only one frame of depth data obtained with an off-the-shelf RGB-D sensor. The experiments showed competitive results with real world data.

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