Doctoral Thesis Proposal - Nicole Feng
— 10:00am
Location:
In Person
-
Reddy Conference Room, Gates Hillman 4405
Speaker:
NICOLE FENG
,
Ph.D. Student
Computer Science Department
Carnegie Mellon University
https://nzfeng.github.io/
This thesis presents robust algorithms for inside-outside computation and curve reconstruction (via winding numbers) and signed distance computation. These algorithms make geometric inferences from imperfect data, where such imperfect data includes noisy, incomplete, or inaccurate observations or representations of shapes that result from either acquisition or authoring of geometry. A theme is that robustness and versatility can often be achieved by processing smooth, globally-defined functions encoding the geometry of interest, that are more amenable to robust computation than the original, defective curve or surface. For both inside-outside and signed distance computation we can unlock further control over geometry and topology by processing higher-order derivatives of these functions. In many cases, we can also re-cast our algorithms, formulated in terms of smooth functions, onto different discretizations and geometric data structures. Another theme is that robust reconstruction and robust signed distance computation are closely related problems; towards this end, we provide a formalization of their relationship that justifies the design of our algorithms.
Thesis Committee
Keenan Crane (Chair)
Ioannis Gkioulekas
Nancy Pollard
Chris Wojtan (Institute of Science and Technology Austria)
Additional Information
For More Information:
matthewstewart@cmu.edu