“Data-Driven Shape Analysis and Processing” Chaired by Niloy J. Mitra, Evangelos Kalogerakis, Qixing Huang, Vladimir G. Kim and Kevin (Kai) Xu
Conference:
Type(s):
Title:
- Data-Driven Shape Analysis and Processing
Course Organizer(s):
Presenter(s)/Author(s):
Abstract:
Data-driven methods serve an increasingly important role in dis- covering geometric, structural, and semantic relationships between shapes. We provide an overview of the main concepts and components of these methods, as well as discuss their application to classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis. We finally discuss ideas that can inspire future research in data-driven shape analysis and processing.
Additional Information:
Level: Intermediate
Prerequisites: Some basic knowledge of machine learning and geometry processing is a plus, but not required.
Presentation Language: English
Intended Audience: The course is intended for junior graduate students who are interested in geometry analysis and processing. We will give an overview of state-of-the art methods and cover basic toolsets.
