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Morphing Based Approach for Process Planning for Fabrication of Geometries and the Control of Material Composition
The inherent limitation of most of the solid freeform fabrication is the deposition in form
of layers. Artificial imposition of the process for the desired geometric morphology and
the functional gradience of material limits the accuracy of the workpiece. Mathematical
morphing of geometry and the material gradience allows a smooth variation across the
part geometry and the material composition of the part. The paper describes a framework
for process planning and implementation of fabrication of geometries and control of the
material composition. Simulation results for the suggested approach are described in the
paper.Mechanical Engineerin
Abstract Morphing Using the Hausdorff Distance and Voronoi Diagrams
This paper introduces two new abstract morphs for two 2-dimensional shapes. The intermediate shapes gradually reduce the Hausdorff distance to the goal shape and increase the Hausdorff distance to the initial shape. The morphs are conceptually simple and apply to shapes with multiple components and/or holes. We prove some basic properties relating to continuity, containment, and area. Then we give an experimental analysis that includes the two new morphs and a recently introduced abstract morph that is also based on the Hausdorff distance [Van Kreveld et al., 2022]. We show results on the area and perimeter development throughout the morph, and also the number of components and holes. A visual comparison shows that one of the new morphs appears most attractive
Reliable Face Morphing Attack Detection in On-The-Fly Border Control Scenario with Variation in Image Resolution and Capture Distance
Face Recognition Systems (FRS) are vulnerable to various attacks performed
directly and indirectly. Among these attacks, face morphing attacks are highly
potential in deceiving automatic FRS and human observers and indicate a severe
security threat, especially in the border control scenario. This work presents
a face morphing attack detection, especially in the On-The-Fly (OTF) Automatic
Border Control (ABC) scenario. We present a novel Differential-MAD (D-MAD)
algorithm based on the spherical interpolation and hierarchical fusion of deep
features computed from six different pre-trained deep Convolutional Neural
Networks (CNNs). Extensive experiments are carried out on the newly generated
face morphing dataset (SCFace-Morph) based on the publicly available SCFace
dataset by considering the real-life scenario of Automatic Border Control (ABC)
gates. Experimental protocols are designed to benchmark the proposed and
state-of-the-art (SOTA) D-MAD techniques for different camera resolutions and
capture distances. Obtained results have indicated the superior performance of
the proposed D-MAD method compared to the existing methods.Comment: The paper is accepted at the International Joint Conference on
Biometrics (IJCB) 202
A Survey of Morphing Techniques
Image morphing provides the tool to generate the flexible and powerful visual effect. Morphing depicts the transformation of one image into another image. The process of image morphing starts with the feature specification phase and then proceeds to warp generation phase, followed by the transition control phase. This paper surveys the various techniques available for all three stages of image morphing
Image Morphing
Morphing is also used in the gaming industry to add engaging animation to video games and computer games. However, morphing techniques are not limited only to entertainment purposes. Morphing is a powerful tool that can enhance many multimedia projects such as presentations, education, electronic book illustrations, and computer-based training
Optimized normal and distance matching for heterogeneous object modeling
This paper presents a new optimization methodology of material blending for heterogeneous object modeling by matching the material governing features for designing a heterogeneous object. The proposed method establishes point-to-point correspondence represented by a set of connecting lines between two material directrices. To blend the material features between the directrices, a heuristic optimization method developed with the objective is to maximize the sum of the inner products of the unit normals at the end points of the connecting lines and minimize the sum of the lengths of connecting lines. The geometric features with material information are matched to generate non-self-intersecting and non-twisted connecting surfaces. By subdividing the connecting lines into equal number of segments, a series of intermediate piecewise curves are generated to represent the material metamorphosis between the governing material features. Alternatively, a dynamic programming approach developed in our earlier work is presented for comparison purposes. Result and computational efficiency of the proposed heuristic method is also compared with earlier techniques in the literature. Computer interface implementation and illustrative examples are also presented in this paper
Variational Autoencoders for Deforming 3D Mesh Models
3D geometric contents are becoming increasingly popular. In this paper, we
study the problem of analyzing deforming 3D meshes using deep neural networks.
Deforming 3D meshes are flexible to represent 3D animation sequences as well as
collections of objects of the same category, allowing diverse shapes with
large-scale non-linear deformations. We propose a novel framework which we call
mesh variational autoencoders (mesh VAE), to explore the probabilistic latent
space of 3D surfaces. The framework is easy to train, and requires very few
training examples. We also propose an extended model which allows flexibly
adjusting the significance of different latent variables by altering the prior
distribution. Extensive experiments demonstrate that our general framework is
able to learn a reasonable representation for a collection of deformable
shapes, and produce competitive results for a variety of applications,
including shape generation, shape interpolation, shape space embedding and
shape exploration, outperforming state-of-the-art methods.Comment: CVPR 201
matching, interpolation, and approximation ; a survey
In this survey we consider geometric techniques which have been used to
measure the similarity or distance between shapes, as well as to approximate
shapes, or interpolate between shapes. Shape is a modality which plays a key
role in many disciplines, ranging from computer vision to molecular biology.
We focus on algorithmic techniques based on computational geometry that have
been developed for shape matching, simplification, and morphing
Optimum Slice Reduction Algorithm For Fast Surface Reconstruction From Contour Slices
Tesis ini memfokus kepada pembinaan semula permukaan daripada siri hirisan
kontur, dengan tujuan mempercepatkan proses pembinaan semula di samping
mengekalkan kualiti output pada tahap yang boleh diterima.
This thesis is concerned with the reconstruction of surface from a series of
contour slices, with the aim to speed up the reconstruction process while preserving
the output quality at an acceptable level
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