Still Image Objective Segmentation Evaluation using Ground Truth

By Vasileios Mezaris, I. Kompatsiaris, Michael Gerasimos Strintzis. 2003

42 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Massimo Minervini
2. Sotirios A. Tsaftaris
3. Hanno Scharr
4. Christian Klukas
5. Jean-Michel Pape
6. Andreas Fischbach
7. Xi Yin
8. Imanol Luengo

In Evaluation & Benchmarks

1. Xi Yin
2. Hanno Scharr
3. Mengye Ren
4. Richard S. Zemel
5. Ian Stavness
6. Jordan R. Ubbens

Citations in the corpus

• Finely-grained annotated datasets for image-based plant phenotyping (2016, background): “Evaluation criteria: Several segmentation criteria are available for comparing between ground truth and algorithmic outcomes (Mezaris et al., 2003; Unnikrishnan et al., 2007).”
• segmentation in plant phenotyping: a collation study. Machine Vision and Applications (2017, background): “Measuring multi-object segmentation accuracy is an active topic of research with several metrics previously proposed [33–35 , 44 measuring the degree of overlap among ground truth P gt and algorithmic result P ar binary segmentation masks.”