Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/78131
Título: | Ensemble metropolis light transport |
Autor(es): | Bashford-Rogers, Thomas Santos, Luís Paulo Marnerides, Demetris Debattista, Kurt |
Palavras-chave: | Light transport Markov Chain Monte Carlo MCMC ensemble |
Data: | 2022 |
Editora: | ACM |
Revista: | ACM Transactions on Graphics |
Citação: | Bashford-Rogers, T., Santos, L. P., Marnerides, D., & Debattista, K. (2022, February 28). Ensemble Metropolis Light Transport. ACM Transactions on Graphics. Association for Computing Machinery (ACM). http://doi.org/10.1145/3472294 |
Resumo(s): | This article proposes a Markov Chain Monte Carlo (MCMC) rendering algorithm based on a family of guided transition kernels. The kernels exploit properties of ensembles of light transport paths, which are distributed according to the lighting in the scene, and utilize this information to make informed decisions for guiding local path sampling. Critically, our approach does not require caching distributions in world space, saving time and memory, yet it is able to make guided sampling decisions based on whole paths. We show how this can be implemented efficiently by organizing the paths in each ensemble and designing transition kernels for MCMC rendering based on a carefully chosen subset of paths from the ensemble. This algorithm is easy to parallelize and leads to improvements in variance when rendering a variety of scenes. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/78131 |
DOI: | 10.1145/3472294 |
ISSN: | 0730-0301 |
Versão da editora: | https://dl.acm.org/doi/10.1145/3472294 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CCTC - Artigos em revistas internacionais |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
3472294.pdf | 19,94 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons