Computer Vision Problems in Plant Phenotyping (CVPPP)
Long Beach, California, in conjunction with CVPR 2019
The goal of this workshop, following on from the successful CVPPPs at ECCV 2014, ICCV 2017 and BMVC 2015 and 2018, is to continue to showcase the challenges raised by and extend the state of the art in computer vision for plant phenotyping: the recovery of quantitative descriptions of plant structure and function.
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.
For more information, please contact: Tony Pridmore