- title = "{genBRDF}: discovering new analytic {BRDFs} with genetic programming",
- author = "Adam Brady and Jason Lawrence and Pieter Peers and Westley Weimer",
- journal = "ACM Transactions on Graphics",
- year = "2014",
- volume = "33",
- number = "4",
- pages = "114:1--114:11",
- month = jul,
- keywords = "genetic algorithms, genetic programming, GPU, BRDF, analytic, isotropic",
- publisher = "ACM",
- ISSN = "0730-0301",
- acmid = "2601193",
-
URL = "
https://web.eecs.umich.edu/~weimerw/p/brady_sig14.pdf",
-
URL = "
http://doi.acm.org/10.1145/2601097.2601193",
-
DOI = "
doi:10.1145/2601097.2601193",
- size = "11 pages",
- abstract = "We present a framework for learning new analytic BRDF models through Genetic Programming that we call genBRDF. This approach to reflectance modelling can be seen as an extension of traditional methods that rely either on a phenomenological or empirical process. Our technique augments the human effort involved in deriving mathematical expressions that accurately characterise complex high-dimensional reflectance functions through a large-scale optimisation. We present a number of analysis tools and data visualisation techniques that are crucial to sifting through the large result sets produced by genBRDF in order to identify fruitful expressions. Additionally, we highlight several new models found by genBRDF that have not previously appeared in the BRDF literature. These new BRDF models are compact and more accurate than current state-of-the-art alternatives.",
-
notes = "
p114:2 'we attempt to grow new' [mathematical expressions]. p114:5 'implemented the BRDF fitting procedure in CUDA and used a 24 node NVidia Tesla M2075 GPU cluster.'
cited by \cite{Dorn:2015:Pacific-Graphics}",
