The Earth Mover's Distance as a Metric for Image Retrieval

@article{Rubner2004TheEM,
  title={The Earth Mover's Distance as a Metric for Image Retrieval},
  author={Yossi Rubner and Carlo Tomasi and Leonidas J. Guibas},
  journal={International Journal of Computer Vision},
  year={2004},
  volume={40},
  pages={99-121}
}
We investigate the properties of a metric between two distributions, the Earth Mover's Distance (EMD), for content-based image retrieval. [] Key Method This combination leads to an image comparison framework that often accounts for perceptual similarity better than other previously proposed methods. The EMD is based on a solution to the transportation problem from linear optimization, for which efficient algorithms are available, and also allows naturally for partial matching.
Earth Mover's Distance based Similarity Search at Scale
TLDR
This paper focuses on optimizing the refinement phase of EMD-based similarity search by adapting an efficient min-cost flow algorithm (SIA) for EMD computation, proposing a dynamic distance bound, and proposed a dynamic refinement order for the candidates which, paired with a concurrent EMD refinement strategy, reduces the amount of needless computations.
Intensity-based image registration using Earth Mover's Distance
TLDR
Two image alignment measures using Earth Mover's Distance as a metric on the space of joint intensity distributions are introduced and it is shown that EMD-based measures can be efficiently applied to rigid registration tasks.
A Linear Approximate Algorithm for Earth Mover's Distance with Thresholded Ground Distance
TLDR
A new image distance metric, , is presented, which applies a threshold to the ground distance and a novel linear approximation algorithm, which achieves complexity with the benefit of qualified bins.
Supervised Earth Mover's Distance Learning and Its Computer Vision Applications
TLDR
This work proposes to jointly optimize the ground distance matrix and the EMD flow-network based on a partial ordering of histogram distances in an optimization framework to produce more accurate EMD values and flow-networks.
A linear-time approximation of the earth mover's distance
TLDR
A new distance function that calculates an approximate earth mover's distance in linear time and employs the space-filling curve for multidimensional color space to achieve order-of-magnitude time improvement but incurs small errors.
Earth Mover Distance on superpixels
TLDR
This construction approximates the EMD between two images, by computing a pixel-wise transport at the complexity cost of computing an E MD between 1-D Histograms and preserves the geometrical and topological structure of the image.
Localized Earth Mover's Distance for Robust Histogram Comparison
TLDR
The localized Earth Mover's Distance (LEMD) is proposed and it is shown that LEMD is more stable than EMD-hat for noise-added or shape-deformed data, and is faster than FastEMD that is the state of the art among EMD variants.
Accurate Approximation of the Earth Mover’s Distance in Linear Time
TLDR
A new distance function is proposed that calculates an approximate earth mover’s distance in linear time and employs the space-filling curve for multidimensional color space to calculate the dissimilarity between two images.
On the Earth Mover's Distance as a histogram similarity metric for image retrieval
  • Zhenghua Yu, G. Herman
  • Computer Science
    2005 IEEE International Conference on Multimedia and Expo
  • 2005
TLDR
The performance of the Earth Mover's Distance vs /spl chi//sup 2/ distance as histogram similarity metrics for image retrieval is evaluated experimentally and may constitute guidelines in adopting the EMD.
On Efficient Query Processing with the Earth Mover's Distance
TLDR
The ongoing experimental evaluation on real data points out the high efficiency of the proposed lower bound Independent Minimization for Signatures (IM-Sig) to the Earth Mover's Distance on feature signatures as an efficient filter approximation approach, contributing to a promising start in the research field of efficient query processing with the Earth mover's distance.
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