Efficient optimization of common base domains for cross parameterization

3D human ear modelling with parameterization technique and variation analysis

Anthropometry is vital to provide design references when seeking proper product fit. Nowadays, 3D anthropometry is widely used to provide more size and shape details for improving product designs. However, 3D ear anthropometry is still at an explorative stage, considering the complex ear morphology and other technical obstacles. The proposed research method in this study is applicable to analyse the 3D point cloud of the entire external ear. With the cross-parameterisation technique, the dataset was used to explore the morphological characteristics of the ear. Ear dimensions were automatically extracted and further analysed to explore the gender and symmetry differences using two-way ANOVA. The 3D ear models were investigated through Principal Component Analysis (PCA). The most significant variation was found in the helix and concha region, and the overall ear size is the second important factor determining ear variance. The statistical models were generated as 3D design references for ear-related products.Practitioner summary: This study revealed the morphological variations of the entire 3D external ear with a parameterised 3D ear dataset. Based on the PCA findings, a set of statistical models were generated as design references for product evaluation digitally or physically.

Volume-Enhanced Compatible Remeshing of 3D Models

Compatible remeshing provides meshes with common connectivity structures. The existing compatible remeshing methods usually suffer from high computational cost or poor quality. In this paper, we present a fast method for computing compatible meshes with high quality. Given two closed, oriented, and topologically equivalent surfaces and a sparse set of corresponding landmarks, we first compute a bijective inter-surface mapping, from which compatible meshes are generated. We then improve the remeshing quality by using a volume-enhanced optimization. In contrast to previous work, our method designs a fast volume-enhanced improvement procedure that directly reduces the isometric distortion of the map between the compatible meshes. Our method also tries to preserve the shapes of the input meshes by projecting the vertices of the compatible meshes onto the input surfaces. Central to this approach is the use of the monotone preconditioned conjugate gradient method, which minimizes the energies effectively and efficiently. Compared with state-of-the-art methods, our method performs about one order of magnitude faster with better remeshing quality. We demonstrate the efficiency and efficacy of our method using various model pairs.

Styling Evolution for Tight-Fitting Garments

We present an evolution method for designing the styling curves of garments. The procedure of evolution is driven by aesthetics-inspired scores to evaluate the quality of styling designs, where the aesthetic considerations are represented in the form of streamlines on human bodies. A dual representation is introduced in our platform to process the styling curves of designs, based on which robust methods for realizing the operations of evolution are developed. Starting from a given set of styling designs on human bodies, we demonstrate the effectiveness of set evolution inspired by aesthetic factors. The evolution is adaptive to the change of aesthetic inspirations. By this adaptation, our platform can automatically generate new designs fulfilling the demands of variations in different human bodies and poses.