Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Efficient affinity-based edit propagation using K-D tree

Xu, Kun, Li, Yong, Ju, Tao, Hu, Shi-Min ORCID: https://orcid.org/0000-0001-7507-6542 and Liu, Tian-Qiang 2009. Efficient affinity-based edit propagation using K-D tree. ACM Transactions on Graphics 28 (5) , 118. 10.1145/1618452.1618464

[thumbnail of a118-xu.pdf]
Preview
PDF - Published Version
Download (3MB) | Preview

Abstract

Image/video editing by strokes has become increasingly popular due to the ease of interaction. Propagating the user inputs to the rest of the image/video, however, is often time and memory consuming especially for large data. We propose here an efficient scheme that allows affinity-based edit propagation to be computed on data containing tens of millions of pixels at interactive rate (in matter of seconds). The key in our scheme is a novel means for approximately solving the optimization problem involved in edit propagation, using adaptive clustering in a high-dimensional, affinity space. Our approximation significantly reduces the cost of existing affinity-based propagation methods while maintaining visual fidelity, and enables interactive stroke-based editing even on high resolution images and long video sequences using commodity computers.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Publisher: ACM
ISSN: 0730-0301
Date of First Compliant Deposit: 30 March 2016
Last Modified: 14 May 2023 01:51
URI: https://orca.cardiff.ac.uk/id/eprint/45688

Citation Data

Cited 137 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics