Manipulating space and time in visual media

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Abstract/Contents

Abstract
With the increased usage of digital technology, visual media has become a popular form of communication and is widely used for storytelling and art. Often times, authors of visual media may wish to make spatial or temporal edits in post-production. However, it can be difficult to author edits while preserving realism. One main issue is that there are many constraints involved in realism, which limit the edits that can be achieved given user-specified inputs. Moreover, often times these constraints are not explicitly defined. In this work, we introduce task-dependent realism, which explicitly defines realism for a target manipulation task. We focus on two manipulation tasks and identify spatial and temporal properties to relax to achieve a greater number of realistic-looking edits. This thesis contributes: 1) spatial and temporal constraints to relax and maintain for two manipulation tasks, based on perceptual properties; and 2) techniques which automatically maintain and relax these constraints as the user specifies input constraints and explores edits.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2023; ©2023
Publication date 2023; 2023
Issuance monographic
Language English

Creators/Contributors

Author Liu, Sean Jeng
Degree supervisor Agrawala, Maneesh
Thesis advisor Agrawala, Maneesh
Thesis advisor Hertzmann, Aaron
Thesis advisor Landay, James A, 1967-
Degree committee member Hertzmann, Aaron
Degree committee member Landay, James A, 1967-
Associated with Stanford University, School of Engineering
Associated with Stanford University, Computer Science Department

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Sean J. Liu.
Note Submitted to the Computer Science Department.
Thesis Thesis Ph.D. Stanford University 2023.
Location https://purl.stanford.edu/qg406gc5383

Access conditions

Copyright
© 2023 by Sean Jeng Liu
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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