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Virtual Experiments on ArUco and AprilTag Systems Comparison for Fiducial Marker Rotation Resistance under Noisy Sensory Data

Virtual Experiments on ArUco and AprilTag Systems Comparison...

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International Joint Conference on Neural Networks (IJCNN) held as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Zakiev, Aufar Tsoy, Tatyana Shabalina, Ksenia Magid, Evgeni Saha, Subir Kumar Kazan Fed Univ Intelligent Robot Dept Kazan Russia Indian Inst Technol Delhi Dept Mech Engn Delhi India

ISBN: (纸本)9781728169262

Modern robotic researches propose various machine vision methods for accomplishing robotic tasks. The recognition quality in these tasks is very important for successful performance. A large number of them use fiducial marker systems as a main element of algorithms. However, only a few researches are comparing standard marker systems. This paper is dedicated to the comparison of AprilTag and ArUco markers resistance to rotations in the presence of synthetic noise. Experiments were conducted in ROS/Gazebo virtual environment in order to provide a fair comparison of marker detection and recognition algorithms while eliminating external environment conditions that influence the algorithms' performance. The presented virtual environments allow collecting a significant amount of data by experiment process automation. Different levels of additive white Gaussian noise were applied to input sensory data in order to simulate the imperfection of real digital cameras. The main contribution of the paper is the systematic comparison of AprilTag and ArUco markers for rotation resistance in the presence of optical sensor noise.

关键词： robotics fiducial marker system recognition algorithms experimental comparison ROS Gazebo

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Building a larger class of graphs for efficient reconfiguration of vertex colouring

Building a larger class of graphs for efficient reconfigurat...

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作者： Merkel, Owen University of Waterloo

学位级别：硕士

A k-colouring of a graph G is an assignment of at most k colours to the vertices of G so that adjacent vertices are assigned different colours. The reconfiguration graph of the k-colourings, R k (G), is the graph whose vertices are the k-colourings of G and two colourings are joined by an edge in R k (G) if they differ in colour on exactly one vertex. For a k-colourable graph G, we investigate the connectivity and diameter of R k+1 (G). It is known that not all weakly chordal graphs have the property that R k+1 (G) is connected. On the other hand, R k+1 (G) is connected and of diameter O(n 2 ) for several subclasses of weakly chordal graphs such as chordal, chordal bipartite, and P 4 -free graphs. We introduce a new class of graphs called OAT graphs that extends the latter classes and in fact extends outside the class of weakly chordal graphs. OAT graphs are built from four simple operations, disjoint union, join, and the addition of a clique or comparable vertex. We prove that if G is a k-colourable OAT graph, then R k+1 (G) is connected with diameter O(n 2 ). Furthermore, we give polynomial time algorithms to recognize OAT graphs and to find a path between any two colourings in R k+1 (G). Feghali and Fiala defined a subclass of weakly chordal graphs, called compact graphs, and proved that for every k-colourable compact graph G, R k+1 (G) is connected with diameter O(n 2 ). We prove that the class of OAT graphs properly contains the class of compact graphs. Feghali and Fiala also asked if for a k-colourable (P 5, co-P 5, C 5 )-free graph G, R k+1 (G) is connected with diameter O(n 2 ). We answer this question in the positive for the subclass of P 4 -sparse graphs, which are the (P 5, co-P 5, C 5, P, co-P, fork, co-fork)-free graphs.

关键词： reconfiguration vertex colouring recognition algorithms

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Recognizing Optimal 1-Planar Graphs in Linear Time

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ALGORITHMICA 2018年第1期80卷 1-28页

作者： Brandenburg, Franz J. Univ Passau D-94030 Passau Germany

A graph with n vertices is 1-planar if it can be drawn in the plane such that each edge is crossed at most once, and is optimal if it has the maximum of edges. We show that optimal 1-planar graphs can be recognized in linear time. Our algorithm implements a graph reduction system with two rules, which can be used to reduce every optimal 1-planar graph to an irreducible extended wheel graph. The graph reduction system is non-deterministic, constraint, and non-confluent.

关键词： Graph drawing 1-Planar graphs recognition algorithms Graph reduction systems

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Strong involutions in finite special linear groups of odd characteristic

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JOURNAL OF ALGEBRA 2018年 498卷 413-447页

作者： Dixon, John D. Praeger, Cheryl E. Seress, Akos Carleton Univ Sch Math & Stat Ottawa ON K1S 5B6 Canada Univ Western Australia Sch Phys Math & Comp Crawley WA 6009 Australia

Let t be an involution in GL(n, q) whose fixed point space E+ has dimension k between n/3 and 2n/3. For each g is an element of GL(n, q) such that tt(9) has even order, contains a unique involution z(g) which commute... 详细信息

Let t be an involution in GL(n, q) whose fixed point space E+ has dimension k between n/3 and 2n/3. For each g is an element of GL(n, q) such that tt(9) has even order, < tt(g)> contains a unique involution z(g) which commutes with t. We prove that, with probability at least c/log n (for some c > 0), the restriction z(g)(vertical bar E+) is an involution on E+ with fixed point space of dimension between k/3 and 2k/3. This result has implications in the analysis of the complexity of recognition algorithms for finite classical groups in odd characteristic. We discuss how similar results for involutions in other finite classical groups would solve a major open problem in our understanding of the complexity of constructing involution centralisers in those groups. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Finite classical groups Involution centralisers recognition algorithms

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Common Green Plants Identification System 8

Common Green Plants Identification System

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8th International Conference on Virtual Reality and Visualization (ICVRV)

作者： Wang, Yu Li, Changsheng Beijing Technol & Business Univ Beijing Key Lab Big Data Technol Food Safety Beijing Peoples R China

ISBN: (纸本)9781538684979

A plant identification system which is designed to integrate local edge algorithms with other classical recognition algorithms in a prototype system is mainly composed of the following two parts. One is the system interface and another is algorithm embedding. A convenient visual environment is provided for users by this system interface, and algorithm functions and other auxiliary functions are integrated. After selecting the system integration algorithms and setting the necessary parameters, the tested plant image is automatically recognized by this system and the corresponding plant images from the database with a brief description are displayed. The tested common green images can be accurately identified and good identification results are obtained by this system.

关键词： plant identification recognition algorithms automatically algorithm embedding

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Study on the recognition algorithms for TDR Reflected Wave

Study on the Recognition Algorithms for TDR Reflected Wave

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Conference on the Future Computer and Control Systems

作者： Song, Jianhui Zhang, Guohua Sun, Peixin Feng, Naili Xu, Shaolin Shenyang Ligong Univ Sch Informat Sci & Engn Shenyang 110159 Peoples R China Shenyang Artillery Acad PLA Shenyang 110162 Peoples R China

ISBN: (纸本)9783642293894

The measuring accuracy of the TDR cable length measurement system relies on the recognition of the reflected wave. The reflected wave is susceptible to be affected by noise and the reflected wave detecting error is comparatively large. In order to correctly identifying and detecting the reflected wave, this dissertation studies four reflected wave recognition algorithms, which are established according to the threshold method, centroid method, polynomial fitting method and the wavelet modulus maxima method respectively. The advantages and disadvantages of these algorithms are analyzed. The repeatability and accuracies of the reflected wave arrival time for these algorithms are compared through practical applications.

关键词： TDR reflected wave recognition algorithms measuring accuracy

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On recognition of threshold tolerance graphs and their complements

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DISCRETE APPLIED MATHEMATICS 2017年第Part1期216卷 171-180页

作者： Golovach, Petr A. Heggernes, Pinar Lindzey, Nathan McConnell, Ross M. dos Santos, Vinicius Fernandes Spinrad, Jeremy P. Szwarcfiter, Jayme Luiz Univ Bergen Dept Informat POB 7803 N-5020 Bergen Norway Colorado State Univ Dept Math Ft Collins CO 80523 USA Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA Univ Estado Rio De Janeiro Dept Matemat Aplicada Rio De Janeiro Brazil Vanderbilt Univ Dept Elect Engn & Comp Sci 221 Kirkland Hall Nashville TN 37235 USA Univ Fed Rio de Janeiro Inst Matemat Caixa Postal 2324 BR-20001970 Rio De Janeiro RJ Brazil

A graph G = (V, E) is a threshold tolerance graph if each vertex v is an element of V can be assigned a weight w(v) and a tolerance t(v), such that two vertices x, y is an element of V are adjacent if w(x) + w(y) >= min(t(x), t(y)). Currently, the most efficient recognition algorithm for threshold tolerance graphs is the algorithm of Monma, Reed, and Trotter which has an O(n(4)) runtime. We give an O(n(2)) algorithm for recognizing threshold tolerance and their complements, the co-threshold tolerance (co-TT) graphs, resolving an open question of Golumbic, Weingarten, and Limouzy. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Graph classes recognition algorithms Threshold-tolerance graphs Strongly chordal graphs Interval graphs

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Radar signal classification algorithms synthesis and analysis 7

Radar signal classification algorithms synthesis and analysi...

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7th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO)

作者： Dorosinskiy, Leonid Myasnikov, Filipp Ural Fed Univ Ekaterinburg Russia

ISBN: (纸本)9781509054541

The main role in the task of process remote sensing data of the Earth surface are played algorithms of forming and classification those data. From the statistical point of view the solution is based on the maximum-likelihood method. The paper presents analytical equations for likelihood coefficients and the structural scheme of their forming in the solution of radar signal recognition. To analyze the efficiency of the proposed algorithms are found boundary equations for probability calculating of correct signals with the usage of Chernoff-Kailath ratios. This ratios evaluate the upper and lower probability boundaries of correct and incorrect decisions in the case of classification of optional class number from different type surfaces.

关键词： recognition algorithms probability detection noise

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Radarsignal classification algorythms synthesis and analysis 2

Radarsignal classification algorythms synthesis and analysis

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2nd IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Dorosinskiy, Leonid Myasnikov, Filipp Ural Fed Univ Ekaterinburg Russia

ISBN: (纸本)9781467389792

In the process of solving a wide range of tasks concerning the Earth surface remote sensing and its state monitoring, the main role is played by the algorithm of the surface image forming and the algorithm of images and their fragments classification as well. From the statistical point of view the solution is based on the maximum-likelihood method. The paper presents analytical equations for likelihood coefficients and the structural scheme of their forming in the solution of radar signal recognition. To analyze the efficiency of the proposed algorithms are found boundary equations for probability calculating of correct signals with the usage of Chernoff-Kailath ratios. This ratios evaluate the upper and lower probability boundaries of correct and incorrect decisions in the case of classification of optional class number from different type surfaces.

关键词： recognition algorithms probability detection noise

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Radarsignal classification algorythms synthesis and analysis

Radarsignal classification algorythms synthesis and analysis

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2017 IEEE 第2届先进信息技术,电子与自动化控制国际会议(IAEAC 2017)

作者： Leonid Dorosinskiy Filipp Myasnikov Ural Federal University named after the first President of Russia B.N.Yeltsin

ISBN: (纸本)9781467389808

关键词： recognition algorithms Probability Detection Noise Noise Class number Earth surface Probability synthesis Solutions images algorithms RADAR SIGNALS wide-range Religious Missions

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