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∗ Mean-Shift Algorithm
"... – theory & applications – mean-shift object tracking ..."
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– theory & applications – mean-shift object tracking
Convergence of a Mean Shift Algorithm
"... Abstract: Mean shift is an effective iterative algorithm widely used in clustering, tracking, segmentation, discontinuity preserving smoothing, filtering, edge detection, and information fusion etc. However, its convergence, a key property of any iterative method, has not been rigorously proved till ..."
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Abstract: Mean shift is an effective iterative algorithm widely used in clustering, tracking, segmentation, discontinuity preserving smoothing, filtering, edge detection, and information fusion etc. However, its convergence, a key property of any iterative method, has not been rigorously proved
Information theoretic mean shift algorithm
- In Proceedings of IEEE Conf. on Machine Learning for Signal Processing
"... In this paper we introduce a new cost function called Information Theoretic Mean Shift algorithm to capture the “predominant structure ” in the data. We formulate this problem with a cost function which minimizes the entropy of the data subject to the constraint that the Cauchy-Schwartz distance bet ..."
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Cited by 2 (1 self)
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In this paper we introduce a new cost function called Information Theoretic Mean Shift algorithm to capture the “predominant structure ” in the data. We formulate this problem with a cost function which minimizes the entropy of the data subject to the constraint that the Cauchy-Schwartz distance
Review of Mean Shift Algorithm and its Improvements
"... This paper review‟s the origins of basic mean shift algorithm, as being a procedure which iteratively moves data points to the average of data points and its extension to the field of object tracking. Tracking of any given object forms integral part in surveillance, control and analysis applications ..."
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This paper review‟s the origins of basic mean shift algorithm, as being a procedure which iteratively moves data points to the average of data points and its extension to the field of object tracking. Tracking of any given object forms integral part in surveillance, control and analysis
Clustering permutations by Exponential Blurring Mean-Shift algorithm
, 2008
"... Suppose that a sample of people independently examine a fixed set of k items and then rank these items according to personal judgment. Whatever the nature of these items, each person produces a ranking. This paper aims at clustering people into different groups according to their preferences. We pro ..."
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propose the exponential blurring mean-shift (EBMS) algorithm which shifts the rankings to new locations obtained by a locally weighted combination of all the data. The number of clusters does not need to be specified in advance and outliers can be detected. Our experiments show that the EBMS algorithm can
On the convergence of the mean shift algorithm in the onedimensional space
- Pattern Recognition Letters
, 2013
"... ar ..."
EVALUATION OF MEAN SHIFT ALGORITHM AS APPLIED TO IMAGE SEGMENTATION
, 2007
"... The idea of evaluating segmentation algorithms based on human perception and content based image retrieval came about from discussions with my thesis advisor Dr. Douglas Heisterkamp. He provided me ample time and guidance for me to be able to carry out the research for this thesis. Dr. Jay Hanan has ..."
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The idea of evaluating segmentation algorithms based on human perception and content based image retrieval came about from discussions with my thesis advisor Dr. Douglas Heisterkamp. He provided me ample time and guidance for me to be able to carry out the research for this thesis. Dr. Jay Hanan
Image Segmentation based on Mean Shift Algorithm and Normalized Cuts
"... ABSTRACT: A novel approach for Image segmentation is proposed based on mean shift algorithm and normalized cuts algorithm. The normalized cuts algorithm gives good accuracy and better segmentation compared to all most of the existing methods. But it requires high computational power, also it takes ..."
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ABSTRACT: A novel approach for Image segmentation is proposed based on mean shift algorithm and normalized cuts algorithm. The normalized cuts algorithm gives good accuracy and better segmentation compared to all most of the existing methods. But it requires high computational power, also it takes
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48,433
