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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.


Papers
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Book ChapterDOI
10 Sep 2018
TL;DR: CentroidNet is introduced which is a Fully Convolutional Neural Network (FCNN) architecture specifically designed for object localization and counting and compared to the state-of-the-art networks YOLOv2 and RetinaNet, which share similar properties.
Abstract: In precision agriculture, counting and precise localization of crops is important for optimizing crop yield. In this paper CentroidNet is introduced which is a Fully Convolutional Neural Network (FCNN) architecture specifically designed for object localization and counting. A field of vectors pointing to the nearest object centroid is trained and combined with a learned segmentation map to produce accurate object centroids by majority voting. This is tested on a crop dataset made using a UAV (drone) and on a cell-nuclei dataset which was provided by a Kaggle challenge. We define the mean Average F1 score (mAF1) for measuring the trade-off between precision and recall. CentroidNet is compared to the state-of-the-art networks YOLOv2 and RetinaNet, which share similar properties. The results show that CentroidNet obtains the best F1 score. We also explicitly show that CentroidNet can seamlessly switch between patches of images and full-resolution images without the need for retraining.

17 citations

Proceedings ArticleDOI
Pengdi Huang1, Yiping Chen1, Jonathan Li1, Yongtao Yu1, Cheng Wang1, Hongshan Nie 
26 Jul 2015
TL;DR: This paper proposes a method for automated extraction of street trees in a typical urban environment from 3D point cloud data acquired by the mobile laser scanning system and utilizes the voxel-based method to remove the ground points from the scene.
Abstract: This paper proposes a method for automated extraction of street trees in a typical urban environment from 3D point cloud data acquired by the mobile laser scanning system First, the algorithm utilizes the voxel-based method to remove the ground points from the scene Second, the Euclidean distance clustering is adopted to cluster points into individual objects The eigenvalues of neighborhood covariance matrix and the corresponding normalized centroid distance are computed for each point to obtain the subdivided dimensional features Finally, the statistical component features and horizontal information are calculated for object detection The experiment results show the feasibility of the proposed algorithm

17 citations

Journal ArticleDOI
01 Dec 2002
TL;DR: Variation in position resulting from different interpretations is examined in the context of the centroid of the Australian State of Victoria, and GIS software are evaluated to determine the efficacy of their centroid functions.
Abstract: The concept of a centroid is useful for many spatial applications, and the determination of the centroid of a plane polygon is standard functionality in most Geographic Information System (GIS) software. A common reason for determining a centroid is to create a convenient point of reference for a polygon, often for positioning a textual label. For such applications, the rigour with which the centroid is determined is not critical, because in the positioning of a label, for example, the main criteria is that it be within the polygon and reasonably central for easy interpretation. However, there may be applications where the determination of a centroid has, at the very least, an impact on civic pride and quite possibly financial repercussions. We refer here to an administrative or natural region where a nominated centroid has a certain curiosity value with the potential to become a tourist attraction. Such centroids provide economic benefit to those in a sub-region, usually in close proximity to the centroi...

17 citations

Journal ArticleDOI
TL;DR: The results show that the proposed DIC-DOC-K-means algorithm gives a better performance for the number of clusters that are equal to theNumber of classes in the data set with respect to purity, entropy and F-measure.
Abstract: In this article, a new initial centroid selection for a K-means document clustering algorithm, namely, Dissimilarity-based Initial Centroid selection for DOCument clustering using K-means (DIC-DOC-...

17 citations

Proceedings ArticleDOI
01 Jan 2005
TL;DR: A triangulation-based method to triangulate each posture to different triangle meshes from which two important posture features are then extracted, i.e., the ones of skeleton and centroid context.
Abstract: This paper presents a new posture classification system to analyze different human behaviors directly from video sequences using the technique of triangulation. For well analyzing each posture in the video sequences, we propose a triangulation-based method to triangulate it to different triangle meshes from which two important posture features are then extracted, i.e., the ones of skeleton and centroid context. The first one is used for a coarse search and the second one is for a finer classification to classify postures in more details. For the first descriptor, we take advantages of a dfs (depth-first search) scheme to extract the skeleton features of a posture from its triangulation result. Then, with the help of skeleton information, we can define a new shape descriptor, i.e., centroid context, to describe a posture up to a semantic level. That is, the centroid context is a finer descriptor to describe a posture not only from its whole shape but also from its body parts. Since the two descriptors are complement to each other, all desired human postures can be compared and classified very accurately. The nice ability of posture classification can help us generate a set of key postures for transferring a behavior sequence to a set of symbols. Then, a novel string matching scheme is proposed to analyze different human behaviors. Experimental results have proved that the proposed method is robust, accurate, and powerful in human behavior analysis

17 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023492
20221,001
2021184
2020202
2019269
2018271