The Quadratic-Chi Histogram Distance Family
By Ofir Pele, Michael Werman. 2010
300 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Media Technology
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
- Federico Tombari
- Andrew Zisserman
- Xiaogang Wang
- Luigi Di Stefano
- Vladlen Koltun
- Luc Van Gool
- Samuele Salti
- Andrea Vedaldi
In Media Technology
- Relja Arandjelovi'c
- Andrew Zisserman
- Federico Tombari
- Kun Fu
- Xian Sun
- Hongqi Wang
- Samuele Salti
- Yasen Zhang
Citations in the corpus
- SHOT: Unique signatures of histograms for surface and texture description (2014, methodology): “In this respect, SHOT’s structure may allow for handling missing data during the matching stage by deploying a suitable metric to compare descriptors, such as the Earth Mover’s Distance (EMD) [56] or the recently proposed Quadratic-Chi Histogram Distance [57].”
- Three things everyone should know to improve object retrieval (2012, methodology): “For example, Johnson [12] uses Jeffrey’s divergence to compare SIFT vectors concentrating on descriptor compression, Pele and Werman use a variant of the Earth Mover’s Distance [19] or a quadratic χ(2) metric [20].”
- High-Resolution Remote-Sensing Image Classification via an Approximate Earth Mover's Distance-Based Bag-of-Features Model (2013, background): “, if two bins in the histograms are erroneously quantized, this will not affect the distance [12].”