Go with the Winners Strategy in Path Tracing
dc.contributor.author
dc.date.accessioned
2014-09-29T06:21:13Z
dc.date.available
2014-09-29T06:21:13Z
dc.date.issued
2005
dc.identifier.issn
1213-6972
dc.identifier.uri
dc.description.abstract
This paper proposes a new random walk strategy that minimizes the variance of the estimate using statistical estimations of local and global features of the scene. Based on the local and global properties, the algorithm decides at each point whether a Russian-roulette like random termination is worth performing, or on the contrary, we should split the path into several child paths. In this sense the algorithm is similar to the go-with-the-winners strategy invented in general Monte Carlo context. However, instead of establishing thresholds to make decisions, we compute the number of child paths on a continuous level and show that Russian roulette can be interpreted as a kind of splitting using fractional number of children. The new method is built into a path tracing algorithm, and a minimum cost heuristic is proposed for choosing the number of re°ected rays. Comparing it with the classical path tracing approach we concluded that the new method reduced the variance signi¯cantly
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
University of West Bohemia, Czech Republic
dc.relation.isformatof
Reproducció digital del document publicat a: http://wscg.zcu.cz/wscg2005/Papers_2005/Journal/!WSCG2005_Journal_Final.pdf
dc.relation.ispartof
© Journal of WSCG, 2005, vol. 13, núm. 1-3, p.49-56
dc.relation.ispartofseries
Articles publicats (D-IMA)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Go with the Winners Strategy in Path Tracing
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.embargo.terms
Cap
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.idgrec
004785
dc.identifier.eissn
1213-6964