filmov
tv
My Research Story - Implicit Representations and Evolving Surface Remeshing
Показать описание
This is my lecture presentation I've given to the Department of Applied Informatics at Commenius University in Bratislava (in December 13th 2021). It outlines my research story which includes a research project at a company I worked for, my master's thesis, and my current line of research for my dissertation.
Enjoy.
00:00 - 00:33 Intro
00:33 - 4:26 The "Gentle" Introduction
4:26 - 8:45 The Rough Timeline of This Project
8:45 - 27:03 Part I. - Introduction to Signed Distance Fields of Polygonal Meshes
27:03 - 38:18 Part II. - Evolving Surface Shrink-Wrapping of Polygonal Meshes
38:18 - 38:56 New Insights from This Project
38:56 - 43:11 What's Next?
43:11 Acknowledgements
Known Errors:
1.) At 22:20 - The dmin value should be the sqrt of the minimum squared distance. Computing square root is expensive, so it should only be done once the minimum squared distance is found.
2.) At 22:50 - The mapping formulas from x,y,z Euclidean coordinates to grid index space should be of form:
ix = floor( ( 0.5*(C.min.x + C.max.x) - g_min,x)/s)
because the centroid x-coordinate of cube voxel C is: 0.5*(C.min.x + C.max.x)
3.) At 22:20 - The first if should take place when the box size is larger than minimum cell size.
Presentation Abstract:
Implicit representations of 3D objects find their applications in many areas of CAD geometry. It is often easier for users to generate an "outline" (e.g.: a contour rendering of a volumetric representation) of their desired shape, and modify its topological properties after conversion to a polygonal representation. Combining pre-existing polygonal meshes into an implicit object requires high computational efficiency for computing their signed distance fields (SDF). We deal with this problem using a three step approach with hierarchical volume subdivision followed by applying a numerical Eikonal solver. Furthermore, we test and analyze an experimental approach to triangular remeshing using an SDF-based advection onto a mesh obstacle.
Enjoy.
00:00 - 00:33 Intro
00:33 - 4:26 The "Gentle" Introduction
4:26 - 8:45 The Rough Timeline of This Project
8:45 - 27:03 Part I. - Introduction to Signed Distance Fields of Polygonal Meshes
27:03 - 38:18 Part II. - Evolving Surface Shrink-Wrapping of Polygonal Meshes
38:18 - 38:56 New Insights from This Project
38:56 - 43:11 What's Next?
43:11 Acknowledgements
Known Errors:
1.) At 22:20 - The dmin value should be the sqrt of the minimum squared distance. Computing square root is expensive, so it should only be done once the minimum squared distance is found.
2.) At 22:50 - The mapping formulas from x,y,z Euclidean coordinates to grid index space should be of form:
ix = floor( ( 0.5*(C.min.x + C.max.x) - g_min,x)/s)
because the centroid x-coordinate of cube voxel C is: 0.5*(C.min.x + C.max.x)
3.) At 22:20 - The first if should take place when the box size is larger than minimum cell size.
Presentation Abstract:
Implicit representations of 3D objects find their applications in many areas of CAD geometry. It is often easier for users to generate an "outline" (e.g.: a contour rendering of a volumetric representation) of their desired shape, and modify its topological properties after conversion to a polygonal representation. Combining pre-existing polygonal meshes into an implicit object requires high computational efficiency for computing their signed distance fields (SDF). We deal with this problem using a three step approach with hierarchical volume subdivision followed by applying a numerical Eikonal solver. Furthermore, we test and analyze an experimental approach to triangular remeshing using an SDF-based advection onto a mesh obstacle.
0:44:54
My Research Story - Implicit Representations and Evolving Surface Remeshing
0:02:20
UC Davis School of Nursing Students Research Implicit Bias
0:01:44
Implicit and Explicit
0:02:16
IMPLICIT AND EXPLICIT STATEMENTS
0:04:22
POV Marketing: Implicit vs. Explicit
1:29:59
Implicit short-term memory and contextual biases
0:50:02
Conferência | How is social inequality reproduced by grade retention? Implicit bias among teachers
0:19:45
NatCon At Home - Perception Is Everything: The Impact of Implicit Bias in Mental Health & Addict...
1:55:44
U.S. Transhumanist Party Virtual Enlightenment Salon with William Dawley – January 19, 2025
1:28:10
Implicit Bias in Health Care: Endometriosis Awareness
15:38:33
I Sent THIS to My Teacher—Now She’s Talking About a Wedding [FULL]
0:20:16
Ashley A. (P9 XXXIII): Implicit Bias and How it Affects Patients of Color
0:57:57
Implicit Representations of Meaning in Neural Language Models / Jacob Andreas (MIT)
0:15:01
Learning Structured Implicit Shape Representations - Part 1/4
1:53:23
Healthcare Provider Forum - Strategies to Reduce Implicit Bias in Cancer Survivorship Care
0:53:57
Health Equity & Implicit Bias - Keynote
0:21:30
116 – New Research on Implicit Learning: Is it a More Effective Way to Acquire New Skills?
0:51:03
HEAR Symposium - Short Poster Presentation: Implicit Bias in Clinical Care and Training
1:06:16
Recent applications of the Minimally Implicit Runge-Kutta (MIRK) methods in astrophysics.
0:57:34
Deactivating Implicit Bias, Eliminating Treatment Disparities in Oncology: The Road Ahead
0:56:34
Uncovering and Reasoning with Implicit Mental Models
1:04:45
A Metastudy Approach to Examining the Structure of Implicit Memory
0:28:59
Ep 16 - The impact of implicit bias in healthcare
0:03:20
The Neuroscience of Implicit Moral Evaluation and Its Relation to Generosity in Early Childhood
Комментарии