The workshop programme can be downloaded from here.
Computer Vision Problems in Plant Phenotyping
Location: Faraday L
Workshop website: http://www.plant-phenotyping.org/CVPPP2015
Call for papers: http://www.plant-phenotyping.org/CVPPP2015-call
Paper submission details: http://www.plant-phenotyping.org/CVPPP2015-authorinformation
- Sotirios Tsaftaris, IMT Lucca, Italy and Northwestern University, USA
- Hanno Scharr, Forschungszentrum Jülich, Germany
- Tony Pridmore, University of Nottingham, UK
Background: Plant Phenotyping
The goal of this second workshop, following on from the first successful CVPPP at ECCV 2014, is to continue to showcase the challenges raised by and extend the state of the art in computer vision for plant phenotyping. 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.
While collection of phenotypic traits was previously manual, non-invasive, image-based methods are now increasingly utilized in plant phenotyping and the resulting images need to be analysed in a high throughput, robust, accurate, and reliable manner. The problems raised differ from the usual tasks addressed by the computer vision community, due to the requirements posed by this challenging application scenario.
Plants are complex, self-changing systems whose complexity increases over time. Typical phenotyping problems include measuring the size, shape, 3D surface structure, architecture, and other structural traits of plants and their organs (leaves, fruit, roots etc.). Many scenarios require quantitative description of plant populations, where core problems include reliable detection and multi-label segmentation of many similar objects, or the reconstruction of specular, almost featureless, and overlapping surfaces. Quantitative description of the growth of these complex, deforming objects is vital, and requires suitable tracking, optical flow and/or scene flow estimation methods. Inherently, the tracked objects change their appearance over time. In some cases images may be acquired under controlled conditions, but they are increasingly likely to be taken in more challenging natural environments like greenhouses, or in the field. Automated image acquisition protocols are highly desirable, generating large numbers of images.
Unfortunately, without automated and accurate computer vision to extract the phenotypes, a bottleneck is formed, hampering our understanding of plant biology.
Scope of the Workshop:
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. Since plant phenotyping is an important aspect of agriculture and will support the sustainability of our planet and its inhabitants, having new vision scientists enter this field is more crucial than ever.
We welcome submissions that propose interesting computer vision solutions, but also submissions that introduce challenging computer vision problems in plant phenotyping, accompanied with benchmark datasets and suitable performance evaluation methods.
Specific topics of interest include, but are not limited to, the following:
- 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
Keynote Speaker: Prof. Tim Cootes (University of Manchester)