Computer Vision Problems in Plant Phenotyping (CVPPP2018)
Paper submission details:
Plant phenotyping is the identification of effects on plant structure and function (the phenotype) resulting from genotypic differences (i.e., differences in the genetic code) and the environmental conditions a plant has been exposed to. Knowledge of plant phenotypes is a key ingredient of the knowledge-based bioeconomy, which not only literally helps to feed the world, but is also essential for feed, fibre, and fuel production. Following on from successful workshops at ECCV 2014, BMVC 2015, and ICCV 2017 this workshop continues to showcase the challenges raised by and extend the state of the art in computer vision for plant phenotyping. The overriding goal is not only to identify key but unsolved problems and expose the current state-of-the-art, but also to broaden the field and the community.
Specific topics of interest include, but are not limited to:
- Advances in segmentation, tracking, detection, reconstruction and identification methods that address unsolved plant phenotyping scenarios
- Open source implementation, comparison and discussion of existing methods and annotation tools
- Image data sets defining plant phenotyping challenges, complete with annotations if appropriate, accompanied with benchmark methods if possible, and suitable evaluation methods. Compare e.g. the Plant Leaf Segmentation Challenge (LSC), which spawned from earlier CVPPPs and is meanwhile hosted at CodaLab1 as permanent competition.
Paper submission date:06th July 2018