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Face Recognition Using Spatially Constrained Earth Mover's Distance
IEEE Transactions on Image Processing, 2008Face recognition is a challenging problem, especially when the face images are not strictly aligned (e.g., images can be captured from different viewpoints or the faces may not be accurately cropped by a human or automatic algorithm). In this correspondence, we investigate face recognition under the scenarios with potential spatial misalignments. First,
Xu, D., Yan, S., Luo, J.
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Efficient Clustering Earth Mover’s Distance
2011The two-class clustering problem is formulated as an integer convex optimisation problem which determines the maximum of the Earth Movers Distance (EMD) between two classes, constructing a bipartite graph with minimum flow and maximum inter-class EMD between two sets. Subsequently including the nearest neighbours of the start point in feature space and
Jenny Wagner, Björn Ommer
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Fast dataset search with earth mover's distance
Proceedings of the VLDB Endowment, 2022The amount of spatial data in open data portals has increased rapidly, raising the demand for spatial dataset search in large data repositories. In this paper, we tackle spatial dataset search by using the Earth Mover's Distance (EMD) to measure the similarity between datasets.
Wenzhe Yang +3 more
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The Tangent Earth Mover’s Distance
2013We present a new histogram distance, the Tangent Earth Mover’s Distance (TEMD). The TEMD is a generalization of the Earth Mover’s Distance (EMD) that is invariant to some global transformations. Thus, like the EMD it is robust to local deformations. Additionally, it is robuster to global transformations such as global translations and rotations of the ...
Ofir Pele, Ben Taskar
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Kernel Earth Mover's Distance for EEG Classification
Clinical EEG and Neuroscience, 2013Here, we propose a new kernel approach based on the earth mover's distance (EMD) for electroencephalography (EEG) signal classification. The EEG time series are first transformed into histograms in this approach. The distance between these histograms is then computed using the EMD in a pair-wise manner. We bring the distances into a kernel form called
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The Earth Mover's Distance under transformation sets
Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999The Earth Mover's Distance (EMD) is a distance measure between distributions with applications in image retrieval and matching. We consider the problem of computing a transformation of one distribution which minimizes its EMD to another. The applications discussed here include estimation of the size at which a color pattern occurs in an image, lighting-
S. Cohen, L. Guibasm
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Earth-Mover's distance as a tracking regularizer
2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2017Tracking time-varying signals is an important part of many engineering systems. Recently, signal processing techniques have been developed to improve tracking performance when the signal of interest is known a-priori to be sparse. Leveraging sparsity, however, depends heavily on gridding the space, treating the signal as a collection of active or ...
Adam S. Charles +3 more
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3D Models Retrieval Using Earth Mover’s Distance
International Journal of Open Problems in Computer Science and Mathematics, 2013Thanks to the recent and advanced development in threedimensional (3D) computer imaging technology, 3D objects begin to compete with traditional media (2D images, sounds, videos). These objects are usually represented by triangular meshes and are used in various fields. Thus, 3D object databases with size increasingly important become available.
O. Ait Zemzami, H. Aksasse, M. Ouanan
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Indexing Earth Mover’s Distance over Network Metrics
IEEE Transactions on Knowledge and Data Engineering, 2015The Earth Mover’s Distance (EMD) is a well-known distance metric for data represented as probability distributions over a predefined feature space. Supporting EMD-based similarity search has attracted intensive research effort. Despite the plethora of literature, most existing solutions are optimized for $L^p$ feature spaces (e.g., Euclidean ...
Ting Wang, Shicong Meng, Jiang Bian
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Distributed speaker recognition using earth mover's distance
Interspeech 2004, 2004In this paper, we focus on distributed speaker recognition, a technique in which quantized feature parameters are sent to a server, as with distributed speech recognition. The Gaussian mixture model , the traditional method used for speaker recognition, is trained using the maximum likelihood approach.
Yoshiyuki Umeda +3 more
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