Topic
Centroid
About: Centroid is a research topic. Over the lifetime, 4110 publications have been published within this topic receiving 53637 citations. The topic is also known as: barycenter (geometry) & geometric center of a plane figure.
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06 Dec 1999TL;DR: In this article, an angular orientation of a lattice image pattern is found by forming a composite image of superimposed portions of lattice images by aligning centroids of a single lattice element in each portion.
Abstract: An angular orientation of a lattice image pattern is found by forming a composite image of superimposed portions of a lattice image by aligning centroids of a lattice element in each portion, and determining a lattice axis from a line fit through centroids of lattice elements in the composite image. The composite image is formed by selecting a seed pixel, finding a local minimum near the seed pixel and then finding a centroid based on the local minimum. From the centroid, it is determined whether the glyph centroid has sufficient contrast to be included in the composite image. The composite image is formed by superimposing subsamples of the lattice image based on glyph centroids. The composite image is then analyzed to determine a lattice axis through centroids in the composite image, and determining a quadrant image based on the lattice axis.
62 citations
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TL;DR: This work shows how models consisting of a collection of fuzzy points can be visualized in parallel coordinates, and shows the spread of the fuzzy membership in each dimension in detail to allow for a better interpretation of overlap in fuzzy rules.
Abstract: Exploratory data analysis heavily relies on methods to visualize data and models in a user friendly and interpretable manner. We show how models consisting of a collection of fuzzy points can be visualized in parallel coordinates. In contrast to existing techniques that display only lines representing centroids or shaded areas showing the general variance of cluster centers, the proposed technique shows the spread of the fuzzy membership in each dimension in detail. This allows for a better interpretation of overlap in fuzzy rules.
61 citations
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TL;DR: Simulation results and theoretical analysis prove that proposed algorithm outperforms the traditional DV-Hop algorithm in terms of localization error and power consumption.
61 citations
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23 Jun 2014TL;DR: This paper proposes an extension which projects features to fern-specific embedding spaces, which yields improved matching rates in short runtime and provides improved matching performance in comparison to the standard nearest neighbor approach.
Abstract: The prevalent approach to image-based localization is matching interest points detected in the query image to a sparse 3D point cloud representing the known world The obtained correspondences are then used to recover a precise camera pose The state-of-the-art in this field often ignores the availability of a set of 2D descriptors per 3D point, for example by representing each 3D point by only its centroid In this paper we demonstrate that these sets contain useful information that can be exploited by formulating matching as a discriminative classification problem Since memory demands and computational complexity are crucial in such a setup, we base our algorithm on the efficient and effective random fern principle We propose an extension which projects features to fern-specific embedding spaces, which yields improved matching rates in short runtime Experiments first show that our novel formulation provides improved matching performance in comparison to the standard nearest neighbor approach and that we outperform related randomization methods in our localization scenario
61 citations
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TL;DR: A multimodal biometric system for personal identity verification is proposed using hand shape and hand geometry in this paper and outperforms other approaches with the best 0.31% of EER.
Abstract: Shape and geometry features are encoded from contour of the hand only.Robust preprocessing is introduced to cope with the noise and disjoint fingers.Hand orientation and finger registration is applied to provide more flexibility.Two level score fusion is adopted to enhance the verification performance.Promising results are obtained over contact and contactless (IITD) datasets. A multimodal biometric system for personal identity verification is proposed using hand shape and hand geometry in this paper. Shape and geometry features are derived with the help of only contour of the hand image for which only one image acquisition device is sufficient. All the processing is done with respect to a stable reference point at wrist line which is more stable as compared to the centroid against the finger rotation and peaks and valleys determination. Two shape based features are extracted by using the distance and orientation of each point of hand contour with respect to the reference point followed by wavelet decomposition to reduce the dimension. Seven distances are used to encode the geometrical information of the hand. Shape and geometry based features are fused at score levels and their performances are evaluated using standard ROC curves between false acceptance rate, true acceptance rate, equal error rate and decidability index. Different similarity measures are used to examine the accuracy of the introduced method. Performance of system is analyzed for shape based (distance and orientation) and geometrical features individually as well as for all possible combinations of feature and score level fusion. The proposed features and fusion methods are studied over two hand image datasets, (1) JUET contact database of 50 subjects having 10 templates each and (2) IITD contactless dataset of 240 subjects with 5 templates each. The proposed method outperforms other approaches with the best 0.31% of EER.
61 citations