TY - GEN
T1 - Localized earth mover's distance for robust histogram comparison
AU - Won, Kwang Hee
AU - Jung, Soon Ki
PY - 2011
Y1 - 2011
N2 - The Earth Mover's Distance (EMD) is a useful cross-bin distance metric for comparing two histograms. The EMD is based on the minimal cost that must be paid to transform one histogram into the other. But outlier noise in the histogram causes the EMD to be greatly exaggerated. In this paper, we propose the localized Earth Mover's Distance (LEMD). The LEMD separates noises from meaningful transportation of data by specifying local relations among bins, and gives a predefined penalty to those noises, according to the applications. An extended version of the tree-based transportation simplex algorithm is proposed for LEMD. The localized property of LEMD is formulated similarly to the original EMD with the thresholded ground distance, such as EMD-hat [7] and FastEMD [8]. However, we show 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.
AB - The Earth Mover's Distance (EMD) is a useful cross-bin distance metric for comparing two histograms. The EMD is based on the minimal cost that must be paid to transform one histogram into the other. But outlier noise in the histogram causes the EMD to be greatly exaggerated. In this paper, we propose the localized Earth Mover's Distance (LEMD). The LEMD separates noises from meaningful transportation of data by specifying local relations among bins, and gives a predefined penalty to those noises, according to the applications. An extended version of the tree-based transportation simplex algorithm is proposed for LEMD. The localized property of LEMD is formulated similarly to the original EMD with the thresholded ground distance, such as EMD-hat [7] and FastEMD [8]. However, we show 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.
UR - http://www.scopus.com/inward/record.url?scp=79952517824&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-19315-6_37
DO - 10.1007/978-3-642-19315-6_37
M3 - Conference contribution
AN - SCOPUS:79952517824
SN - 9783642193149
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 478
EP - 489
BT - Computer Vision, ACCV 2010 - 10th Asian Conference on Computer Vision, Revised Selected Papers
T2 - 10th Asian Conference on Computer Vision, ACCV 2010
Y2 - 8 November 2010 through 12 November 2010
ER -