# Automated Process for Generating Digitised Maps through GPS Data Compression

Save this PDF as:

Size: px
Start display at page:

## Transcription

5 radians meters Figure 7: Another example of relative cluster heading measured against distance. Again, the dotted lines indicate the segmentation of the areas of constant curvature. fit the best line or arc to each segment determined in the previous subsection. For the straght lines, this is a standard regression analysis. The arcs are more difficult since circles are non-linear. The fitting technique used for this analysis is known as non-linear least squares fitting [6]. The non-linear least squares fitting technique involves finding an objective function which is to be minimised, indicating the quality of the fit. The objective function is described in Equation 4. Levenberg-Marquardt Algorithm was used to minimise this objective function, as described in [6]. J(x, y, r) = ( (xi x) 2 + (y i y) 2 r) 2 (4) d i x d i y d i r = (x i x)/(d i + r) = (y i y)/(d i + r) = 1 Objective Function (J) and set of derivatives for the Levenberg-Marquardt Algorithm The iterative Levenberg-Marquardt Algorithm requires a good first estimate of the center and radius of the circle. This can be achieved by taking the first and last point of each set of points, and finding the point where their perpendicular vectors intersect. Even with noisy data, this can provide a sufficient estimate of the center of the circle and radius. 6 Results Figure 8 shows the result of the process introduced in this paper. The lines and arcs are plotted on an image of the area from where data was collected. The lines match very well, and the notches in the lines indicate where one line/arc finished and another begins. It should be noted here that some of the longer curves were broken into two or three sections. This is due to the transition curves, and shows that they are sufficiently modelled by a number of circular arcs. Frequency Error (m) Figure 8: Histogram of the error between the original clusters and the set of lines and circle arcs The quality of the compression can be seen in Figure 8. This histogram illustrates the amount of error between the thousands of clusters and the corresponding lines and arcs. The compression ratio can be seen in Figure 1. The vast majority of the clusters were located within 0.5 meters of the resulting arcs and lines that make up the compressed digitised map. This is sufficient for all applications mentioned in the introduction of this paper. 7 Conclusion This paper introduced a technique for generating a minimal digitised road map. The process started by collecting data from a fleet of vehicles, and the result was a set of lines and arcs that make up a road map. It was shown in this paper that the compression from a set of road points (clusters) to the set of arcs and lines had minimal error in the large test data set presented. This technique was used in a mining environment, and was successful even with no defined road edges or lane markings. Acknowlegements This work is supported by CRC Mining and the ARC Centre of Excellence program, funded by the Australian Research Council (ARC) and the New South Wales State Government.

6 References [1] S. E. J. Goldbeck, B. Huertgen and L. Kelch, Lane following combining vision and dgps, Journal of Image and Vision Computing, vol. 18, no. 5, pp , April [2] K. Kluge, Extracting road curvature and orientation from image edge points without perceptual grouping into features, in Proc. Intelligent Vehicles Symposium., Oct 1994, pp [3] G. Vosselman and J. D. Knecht, Road tracing by profile matching and kalman filtering, 1995, pp [4] S. Rogers, P. Langley, and C. Wilson, Mining gps data to augment road models, in KDD 99: Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining. New York, NY, USA: ACM Press, 1999, pp [5] R. T. Underwood, The Geometric Design of Roads. South Melbourne: Macmillan Company of Australia, [6] C. M. Shakarji, Least-squares fitting algorithms of the nist algorithm testing system, Journal of Res. Natl. Inst. Stand. Technol., vol. 103, no. 6, pp , November 1998.

### Path Tracking for a Miniature Robot

Path Tracking for a Miniature Robot By Martin Lundgren Excerpt from Master s thesis 003 Supervisor: Thomas Hellström Department of Computing Science Umeå University Sweden 1 Path Tracking Path tracking

### Automatic Labeling of Lane Markings for Autonomous Vehicles

Automatic Labeling of Lane Markings for Autonomous Vehicles Jeffrey Kiske Stanford University 450 Serra Mall, Stanford, CA 94305 jkiske@stanford.edu 1. Introduction As autonomous vehicles become more popular,

### Simultaneous Gamma Correction and Registration in the Frequency Domain

Simultaneous Gamma Correction and Registration in the Frequency Domain Alexander Wong a28wong@uwaterloo.ca William Bishop wdbishop@uwaterloo.ca Department of Electrical and Computer Engineering University

### A Reliability Point and Kalman Filter-based Vehicle Tracking Technique

A Reliability Point and Kalman Filter-based Vehicle Tracing Technique Soo Siang Teoh and Thomas Bräunl Abstract This paper introduces a technique for tracing the movement of vehicles in consecutive video

### The Scientific Data Mining Process

Chapter 4 The Scientific Data Mining Process When I use a word, Humpty Dumpty said, in rather a scornful tone, it means just what I choose it to mean neither more nor less. Lewis Carroll [87, p. 214] In

### Detecting Road Intersections from GPS Traces

GIScience 2010, Sixth International Conference on Geographic Information Science, Zurich, 14-17th September, 2010 Detecting Road Intersections from GPS Traces Alireza Fathi College of Computing Georgia

### Integration of GPS Traces with Road Map

Integration of GPS Traces with Road Map Lijuan Zhang Institute of Cartography and Geoinformatics Leibniz University of Hannover Hannover, Germany +49 511.762-19437 Lijuan.Zhang@ikg.uni-hannover.de Frank

JOURNAL OF PHYSICAL AGENTS, VOL. 4, NO., MAY 1 35 Probabilistic Estimation of Unmarked Roads using Radar Juan I. Nieto, Andres Hernandez-Gutierrez and Eduardo Nebot Abstract This paper presents a probabilistic

### Introduction. Chapter 1

1 Chapter 1 Introduction Robotics and automation have undergone an outstanding development in the manufacturing industry over the last decades owing to the increasing demand for higher levels of productivity

### Model-based Chart Image Recognition

Model-based Chart Image Recognition Weihua Huang, Chew Lim Tan and Wee Kheng Leow SOC, National University of Singapore, 3 Science Drive 2, Singapore 117543 E-mail: {huangwh,tancl, leowwk@comp.nus.edu.sg}

### Static Environment Recognition Using Omni-camera from a Moving Vehicle

Static Environment Recognition Using Omni-camera from a Moving Vehicle Teruko Yata, Chuck Thorpe Frank Dellaert The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 USA College of Computing

### Mathematics on the Soccer Field

Mathematics on the Soccer Field Katie Purdy Abstract: This paper takes the everyday activity of soccer and uncovers the mathematics that can be used to help optimize goal scoring. The four situations that

### Classification of Fingerprints. Sarat C. Dass Department of Statistics & Probability

Classification of Fingerprints Sarat C. Dass Department of Statistics & Probability Fingerprint Classification Fingerprint classification is a coarse level partitioning of a fingerprint database into smaller

### Curve Fitting Best Practice

Enabling Science Curve Fitting Best Practice Part 3: Fitting data Regression and residuals are an important function and feature of curve fitting and should be understood by anyone doing this type of analysis.

### Orbital Mechanics. Angular Momentum

Orbital Mechanics The objects that orbit earth have only a few forces acting on them, the largest being the gravitational pull from the earth. The trajectories that satellites or rockets follow are largely

### Galaxy Morphological Classification

Galaxy Morphological Classification Jordan Duprey and James Kolano Abstract To solve the issue of galaxy morphological classification according to a classification scheme modelled off of the Hubble Sequence,

### Assessment. Presenter: Yupu Zhang, Guoliang Jin, Tuo Wang Computer Vision 2008 Fall

Automatic Photo Quality Assessment Presenter: Yupu Zhang, Guoliang Jin, Tuo Wang Computer Vision 2008 Fall Estimating i the photorealism of images: Distinguishing i i paintings from photographs h Florin

### Analecta Vol. 8, No. 2 ISSN 2064-7964

EXPERIMENTAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS IN ENGINEERING PROCESSING SYSTEM S. Dadvandipour Institute of Information Engineering, University of Miskolc, Egyetemváros, 3515, Miskolc, Hungary,

### MOBILE ROBOT TRACKING OF PRE-PLANNED PATHS. Department of Computer Science, York University, Heslington, York, Y010 5DD, UK (email:nep@cs.york.ac.

MOBILE ROBOT TRACKING OF PRE-PLANNED PATHS N. E. Pears Department of Computer Science, York University, Heslington, York, Y010 5DD, UK (email:nep@cs.york.ac.uk) 1 Abstract A method of mobile robot steering

### Solving Simultaneous Equations and Matrices

Solving Simultaneous Equations and Matrices The following represents a systematic investigation for the steps used to solve two simultaneous linear equations in two unknowns. The motivation for considering

### Resolution Enhancement of Photogrammetric Digital Images

DICTA2002: Digital Image Computing Techniques and Applications, 21--22 January 2002, Melbourne, Australia 1 Resolution Enhancement of Photogrammetric Digital Images John G. FRYER and Gabriele SCARMANA

### Solutions to Exercises, Section 5.1

Instructor s Solutions Manual, Section 5.1 Exercise 1 Solutions to Exercises, Section 5.1 1. Find all numbers t such that ( 1 3,t) is a point on the unit circle. For ( 1 3,t)to be a point on the unit circle

### Senior Secondary Australian Curriculum

Senior Secondary Australian Curriculum Mathematical Methods Glossary Unit 1 Functions and graphs Asymptote A line is an asymptote to a curve if the distance between the line and the curve approaches zero

### Figure 2.1: Center of mass of four points.

Chapter 2 Bézier curves are named after their inventor, Dr. Pierre Bézier. Bézier was an engineer with the Renault car company and set out in the early 196 s to develop a curve formulation which would

### Floating Car Data in the Netherlands

Floating Car Data in the Netherlands Aad de Hoog Ministry of Transport, Public Works and Water Management The Netherlands 1 Overview Setting the scene Concept, technique and results Dutch policy Future

### Modelling, Extraction and Description of Intrinsic Cues of High Resolution Satellite Images: Independent Component Analysis based approaches

Modelling, Extraction and Description of Intrinsic Cues of High Resolution Satellite Images: Independent Component Analysis based approaches PhD Thesis by Payam Birjandi Director: Prof. Mihai Datcu Problematic

### Support Vector Machines with Clustering for Training with Very Large Datasets

Support Vector Machines with Clustering for Training with Very Large Datasets Theodoros Evgeniou Technology Management INSEAD Bd de Constance, Fontainebleau 77300, France theodoros.evgeniou@insead.fr Massimiliano

### Segmentation of building models from dense 3D point-clouds

Segmentation of building models from dense 3D point-clouds Joachim Bauer, Konrad Karner, Konrad Schindler, Andreas Klaus, Christopher Zach VRVis Research Center for Virtual Reality and Visualization, Institute

### Jiří Matas. Hough Transform

Hough Transform Jiří Matas Center for Machine Perception Department of Cybernetics, Faculty of Electrical Engineering Czech Technical University, Prague Many slides thanks to Kristen Grauman and Bastian

### J. P. Oakley and R. T. Shann. Department of Electrical Engineering University of Manchester Manchester M13 9PL U.K. Abstract

A CURVATURE SENSITIVE FILTER AND ITS APPLICATION IN MICROFOSSIL IMAGE CHARACTERISATION J. P. Oakley and R. T. Shann Department of Electrical Engineering University of Manchester Manchester M13 9PL U.K.

### Image Compression through DCT and Huffman Coding Technique

International Journal of Current Engineering and Technology E-ISSN 2277 4106, P-ISSN 2347 5161 2015 INPRESSCO, All Rights Reserved Available at http://inpressco.com/category/ijcet Research Article Rahul

### Improved Billboard Clouds for Extreme Model Simplification

Improved Billboard Clouds for Extreme Model Simplification I.-T. Huang, K. L. Novins and B. C. Wünsche Graphics Group, Department of Computer Science, University of Auckland, Private Bag 92019, Auckland,

### An Overview of Knowledge Discovery Database and Data mining Techniques

An Overview of Knowledge Discovery Database and Data mining Techniques Priyadharsini.C 1, Dr. Antony Selvadoss Thanamani 2 M.Phil, Department of Computer Science, NGM College, Pollachi, Coimbatore, Tamilnadu,

### A PHOTOGRAMMETRIC APPRAOCH FOR AUTOMATIC TRAFFIC ASSESSMENT USING CONVENTIONAL CCTV CAMERA

A PHOTOGRAMMETRIC APPRAOCH FOR AUTOMATIC TRAFFIC ASSESSMENT USING CONVENTIONAL CCTV CAMERA N. Zarrinpanjeh a, F. Dadrassjavan b, H. Fattahi c * a Islamic Azad University of Qazvin - nzarrin@qiau.ac.ir

### In mathematics, there are four attainment targets: using and applying mathematics; number and algebra; shape, space and measures, and handling data.

MATHEMATICS: THE LEVEL DESCRIPTIONS In mathematics, there are four attainment targets: using and applying mathematics; number and algebra; shape, space and measures, and handling data. Attainment target

### Interactive Flag Identification using Image Retrieval Techniques

Interactive Flag Identification using Image Retrieval Techniques Eduardo Hart, Sung-Hyuk Cha, Charles Tappert CSIS, Pace University 861 Bedford Road, Pleasantville NY 10570 USA E-mail: eh39914n@pace.edu,

### Blind Deconvolution of Barcodes via Dictionary Analysis and Wiener Filter of Barcode Subsections

Blind Deconvolution of Barcodes via Dictionary Analysis and Wiener Filter of Barcode Subsections Maximilian Hung, Bohyun B. Kim, Xiling Zhang August 17, 2013 Abstract While current systems already provide

### Optimal Design of α-β-(γ) Filters

Optimal Design of --(γ) Filters Dirk Tenne Tarunraj Singh, Center for Multisource Information Fusion State University of New York at Buffalo Buffalo, NY 426 Abstract Optimal sets of the smoothing parameter

### APPLICATION OF DATA MINING TECHNIQUES FOR BUILDING SIMULATION PERFORMANCE PREDICTION ANALYSIS. email paul@esru.strath.ac.uk

Eighth International IBPSA Conference Eindhoven, Netherlands August -4, 2003 APPLICATION OF DATA MINING TECHNIQUES FOR BUILDING SIMULATION PERFORMANCE PREDICTION Christoph Morbitzer, Paul Strachan 2 and

### Calculus C/Multivariate Calculus Advanced Placement G/T Essential Curriculum

Calculus C/Multivariate Calculus Advanced Placement G/T Essential Curriculum UNIT I: The Hyperbolic Functions basic calculus concepts, including techniques for curve sketching, exponential and logarithmic

### Traffic Monitoring Systems. Technology and sensors

Traffic Monitoring Systems Technology and sensors Technology Inductive loops Cameras Lidar/Ladar and laser Radar GPS etc Inductive loops Inductive loops signals Inductive loop sensor The inductance signal

### Position, Velocity, and Acceleration

Chapter 2 Position, Velocity, and Acceleration In this section, we will define the first set of quantities (position, velocity, and acceleration) that will form a foundation for most of what we do in this

### Clustering & Visualization

Chapter 5 Clustering & Visualization Clustering in high-dimensional databases is an important problem and there are a number of different clustering paradigms which are applicable to high-dimensional data.

### Whiteboard It! Convert Whiteboard Content into an Electronic Document

Whiteboard It! Convert Whiteboard Content into an Electronic Document Zhengyou Zhang Li-wei He Microsoft Research Email: zhang@microsoft.com, lhe@microsoft.com Aug. 12, 2002 Abstract This ongoing project

### IB Mathematics SL :: Checklist. Topic 1 Algebra The aim of this topic is to introduce students to some basic algebraic concepts and applications.

Topic 1 Algebra The aim of this topic is to introduce students to some basic algebraic concepts and applications. Check Topic 1 Book Arithmetic sequences and series; Sum of finite arithmetic series; Geometric

### Visualizing Data: Scalable Interactivity

Visualizing Data: Scalable Interactivity The best data visualizations illustrate hidden information and structure contained in a data set. As access to large data sets has grown, so has the need for interactive

### Models and Filters for camera-based Multi-target Tracking. Dr.-Ing. Mirko Meuter interactive Summer School 4-6 July, 2012

Models and Filters for camera-based Multi-target Tracking Dr.-Ing. Mirko Meuter interactive Summer School 4-6 July, 2012 Outline: Contents of the Presentation From detection to tracking Overview over camera

### Visual Structure Analysis of Flow Charts in Patent Images

Visual Structure Analysis of Flow Charts in Patent Images Roland Mörzinger, René Schuster, András Horti, and Georg Thallinger JOANNEUM RESEARCH Forschungsgesellschaft mbh DIGITAL - Institute for Information

### The Mathematics of Highway Design

The Mathematics of Highway Design Scenario As a new graduate you have gained employment as a graduate engineer working for a major contractor that employs 2000 staff and has an annual turnover of 600m.

### PHOTOGRAMMETRIC TECHNIQUES FOR MEASUREMENTS IN WOODWORKING INDUSTRY

PHOTOGRAMMETRIC TECHNIQUES FOR MEASUREMENTS IN WOODWORKING INDUSTRY V. Knyaz a, *, Yu. Visilter, S. Zheltov a State Research Institute for Aviation System (GosNIIAS), 7, Victorenko str., Moscow, Russia

### Electric Power Steering Automation for Autonomous Driving

Electric Power Steering Automation for Autonomous Driving J. E. Naranjo, C. González, R. García, T. de Pedro Instituto de Automática Industrial (CSIC) Ctra. Campo Real Km.,2, La Poveda, Arganda del Rey,

### Quality of Map-Matching Procedures Based on DGPS and Stand-Alone GPS Positioning in an Urban Area

Quality of Map-Matching Procedures Based on DGPS and Stand-Alone GPS Positioning in an Urban Area Konstantinos LAKAKIS, Paraskevas SAVVAIDIS, Ioannis M. IFADIS and Ioannis D. DOUKAS, Greece Key words:

### A Computer Vision System on a Chip: a case study from the automotive domain

A Computer Vision System on a Chip: a case study from the automotive domain Gideon P. Stein Elchanan Rushinek Gaby Hayun Amnon Shashua Mobileye Vision Technologies Ltd. Hebrew University Jerusalem, Israel

### Section 4: The Basics of Satellite Orbits

Section 4: The Basics of Satellite Orbits MOTION IN SPACE VS. MOTION IN THE ATMOSPHERE The motion of objects in the atmosphere differs in three important ways from the motion of objects in space. First,

### CIRCLE GEOMETRY GEOMETRY 2. Dr Adrian Jannetta MIMA CMath FRAS INU0114/514 (MATHS 1) Circle Geometry 1/ 16 Adrian Jannetta

CIRCLE GEOMETRY GEOMETRY 2 INU0114/514 (MATHS 1) Dr Adrian Jannetta MIMA CMath FRAS Circle Geometry 1/ 16 Adrian Jannetta Overview We will extend our knowledge of geometry to problems connected to circles.

### 3D Pipeline Segmentation (planar)

3D Pipeline Segmentation (planar) Registration (using lines) 3D PHOTOGRAPHY EXAMPLE Ten scans were acquired of façade of Thomas Hunter Building (NYC) Automatic registration. Each scan has a different color.

### Redundant Data Removal Technique for Efficient Big Data Search Processing

Redundant Data Removal Technique for Efficient Big Data Search Processing Seungwoo Jeon 1, Bonghee Hong 1, Joonho Kwon 2, Yoon-sik Kwak 3 and Seok-il Song 3 1 Dept. of Computer Engineering, Pusan National

### A REVIEW ON KALMAN FILTER FOR GPS TRACKING

A REVIEW ON KALMAN FILTER FOR GPS TRACKING Ms. SONAL(Student, M.Tech ), Dr. AJIT SINGH (Professor in CSE & IT) Computer Science & Engg. (Network Security) BPS Mahila Vishwavidyalaya Khanpur Kalan, Haryana

### Color to Grayscale Conversion with Chrominance Contrast

Color to Grayscale Conversion with Chrominance Contrast Yuting Ye University of Virginia Figure 1: The sun in Monet s Impression Sunrise has similar luminance as the sky. It can hardly be seen when the

### Cloud tracking with optical flow for short-term solar forecasting

Cloud tracking with optical flow for short-term solar forecasting Philip Wood-Bradley, José Zapata, John Pye Solar Thermal Group, Australian National University, Canberra, Australia Corresponding author:

### Robust Outlier Detection Technique in Data Mining: A Univariate Approach

Robust Outlier Detection Technique in Data Mining: A Univariate Approach Singh Vijendra and Pathak Shivani Faculty of Engineering and Technology Mody Institute of Technology and Science Lakshmangarh, Sikar,

Image Segmentation Preview Segmentation subdivides an image to regions or objects Two basic properties of intensity values Discontinuity Edge detection Similarity Thresholding Region growing/splitting/merging

### Phase Portraits for u = A u

Phase Portraits for u = A u How to Construct a Phase Portrait Badly Threaded Solution Curves Solution Curve Tangent Matching Phase Portrait Illustration Phase plot by computer Revised Computer Phase plot

### False alarm in outdoor environments

Accepted 1.0 Savantic letter 1(6) False alarm in outdoor environments Accepted 1.0 Savantic letter 2(6) Table of contents Revision history 3 References 3 1 Introduction 4 2 Pre-processing 4 3 Detection,

### Least-Squares Intersection of Lines

Least-Squares Intersection of Lines Johannes Traa - UIUC 2013 This write-up derives the least-squares solution for the intersection of lines. In the general case, a set of lines will not intersect at a

Lecture 4: Transformations Regression III: Advanced Methods William G. Jacoby Michigan State University Goals of the lecture The Ladder of Roots and Powers Changing the shape of distributions Transforming

### 1.6 Powers of 10 and standard form Write a number in standard form. Calculate with numbers in standard form.

Unit/section title 1 Number Unit objectives (Edexcel Scheme of Work Unit 1: Powers, decimals, HCF and LCM, positive and negative, roots, rounding, reciprocals, standard form, indices and surds) 1.1 Number

### Detailed simulation of mass spectra for quadrupole mass spectrometer systems

Detailed simulation of mass spectra for quadrupole mass spectrometer systems J. R. Gibson, a) S. Taylor, and J. H. Leck Department of Electrical Engineering and Electronics, The University of Liverpool,

### Section 11.1: Vectors in the Plane. Suggested Problems: 1, 5, 9, 17, 23, 25-37, 40, 42, 44, 45, 47, 50

Section 11.1: Vectors in the Plane Page 779 Suggested Problems: 1, 5, 9, 17, 3, 5-37, 40, 4, 44, 45, 47, 50 Determine whether the following vectors a and b are perpendicular. 5) a = 6, 0, b = 0, 7 Recall

### Circle Object Recognition Based on Monocular Vision for Home Security Robot

Journal of Applied Science and Engineering, Vol. 16, No. 3, pp. 261 268 (2013) DOI: 10.6180/jase.2013.16.3.05 Circle Object Recognition Based on Monocular Vision for Home Security Robot Shih-An Li, Ching-Chang

### A Multi-Model Filter for Mobile Terminal Location Tracking

A Multi-Model Filter for Mobile Terminal Location Tracking M. McGuire, K.N. Plataniotis The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 1 King s College

### Social Media Mining. Data Mining Essentials

Introduction Data production rate has been increased dramatically (Big Data) and we are able store much more data than before E.g., purchase data, social media data, mobile phone data Businesses and customers

### Motion Graphs. It is said that a picture is worth a thousand words. The same can be said for a graph.

Motion Graphs It is said that a picture is worth a thousand words. The same can be said for a graph. Once you learn to read the graphs of the motion of objects, you can tell at a glance if the object in

### Social Innovation through Utilization of Big Data

Social Innovation through Utilization of Big Data Hitachi Review Vol. 62 (2013), No. 7 384 Shuntaro Hitomi Keiro Muro OVERVIEW: The analysis and utilization of large amounts of actual operational data

### Appendix E: Graphing Data

You will often make scatter diagrams and line graphs to illustrate the data that you collect. Scatter diagrams are often used to show the relationship between two variables. For example, in an absorbance

### A Novel Approach for Network Traffic Summarization

A Novel Approach for Network Traffic Summarization Mohiuddin Ahmed, Abdun Naser Mahmood, Michael J. Maher School of Engineering and Information Technology, UNSW Canberra, ACT 2600, Australia, Mohiuddin.Ahmed@student.unsw.edu.au,A.Mahmood@unsw.edu.au,M.Maher@unsw.

### IMPROVED VIRTUAL MOUSE POINTER USING KALMAN FILTER BASED GESTURE TRACKING TECHNIQUE

39 IMPROVED VIRTUAL MOUSE POINTER USING KALMAN FILTER BASED GESTURE TRACKING TECHNIQUE D.R.A.M. Dissanayake, U.K.R.M.H. Rajapaksha 2 and M.B Dissanayake 3 Department of Electrical and Electronic Engineering,

### Lesson 5 Rotational and Projectile Motion

Lesson 5 Rotational and Projectile Motion Introduction: Connecting Your Learning The previous lesson discussed momentum and energy. This lesson explores rotational and circular motion as well as the particular

### Object Detection using Circular Hough Transform

Object Detection using Circular Hough Transform Introduction to the Hough Transform Fatoumata Dembele dembelef@msu.edu ECE 448 Design Team 3 Executive Summary One of the major challenges in computer vision

### Neural Networks. CAP5610 Machine Learning Instructor: Guo-Jun Qi

Neural Networks CAP5610 Machine Learning Instructor: Guo-Jun Qi Recap: linear classifier Logistic regression Maximizing the posterior distribution of class Y conditional on the input vector X Support vector

### Method for detecting software anomalies based on recurrence plot analysis

Journal of Theoretical and Applied Computer Science Vol. 6, No. 1, 2012, pp. 3-12 ISSN 2299-2634 http://www.jtacs.org Method for detecting software anomalies based on recurrence plot analysis Michał Mosdorf

### Chess Vision. Chua Huiyan Le Vinh Wong Lai Kuan

Chess Vision Chua Huiyan Le Vinh Wong Lai Kuan Outline Introduction Background Studies 2D Chess Vision Real-time Board Detection Extraction and Undistortion of Board Board Configuration Recognition 3D

### ColorCrack: Identifying Cracks in Glass

ColorCrack: Identifying Cracks in Glass James Max Kanter Massachusetts Institute of Technology 77 Massachusetts Ave Cambridge, MA 02139 kanter@mit.edu Figure 1: ColorCrack automatically identifies cracks

### Calibrating a Camera and Rebuilding a Scene by Detecting a Fixed Size Common Object in an Image

Calibrating a Camera and Rebuilding a Scene by Detecting a Fixed Size Common Object in an Image Levi Franklin Section 1: Introduction One of the difficulties of trying to determine information about a

### More Local Structure Information for Make-Model Recognition

More Local Structure Information for Make-Model Recognition David Anthony Torres Dept. of Computer Science The University of California at San Diego La Jolla, CA 9093 Abstract An object classification

### Machine Learning and Data Mining. Regression Problem. (adapted from) Prof. Alexander Ihler

Machine Learning and Data Mining Regression Problem (adapted from) Prof. Alexander Ihler Overview Regression Problem Definition and define parameters ϴ. Prediction using ϴ as parameters Measure the error

### Image Content-Based Email Spam Image Filtering

Image Content-Based Email Spam Image Filtering Jianyi Wang and Kazuki Katagishi Abstract With the population of Internet around the world, email has become one of the main methods of communication among

### Lecture 20. PLANAR KINEMATIC-PROBLEM EXAMPLES

Lecture 20. PLANAR KINEMATIC-PROBLEM EXAMPLES Figure 4.15 Slider-crank mechanism. TASK: For a given constant rotation rate, find the velocity and acceleration terms of the piston for one cycle of θ. Geometric

### Coding and decoding with convolutional codes. The Viterbi Algor

Coding and decoding with convolutional codes. The Viterbi Algorithm. 8 Block codes: main ideas Principles st point of view: infinite length block code nd point of view: convolutions Some examples Repetition

### Modified Sift Algorithm for Appearance Based Recognition of American Sign Language

Modified Sift Algorithm for Appearance Based Recognition of American Sign Language Jaspreet Kaur,Navjot Kaur Electronics and Communication Engineering Department I.E.T. Bhaddal, Ropar, Punjab,India. Abstract:

### Getting to know your TI-83

Calculator Activity Intro Getting to know your TI-83 Press ON to begin using calculator.to stop, press 2 nd ON. To darken the screen, press 2 nd alternately. To lighten the screen, press nd 2 alternately.

### What is Visualization? Information Visualization An Overview. Information Visualization. Definitions

What is Visualization? Information Visualization An Overview Jonathan I. Maletic, Ph.D. Computer Science Kent State University Visualize/Visualization: To form a mental image or vision of [some

### 3D Object Detection from Roadside Data Using Laser Scanners

3D Object Detection from Roadside Data Using Laser Scanners Jimmy Tang and Avideh Zakhor Berkeley, CA ABSTRACT The detection of objects on a given road path by vehicles equipped with range measurement

### Detection and Recognition of Mixed Traffic for Driver Assistance System

Detection and Recognition of Mixed Traffic for Driver Assistance System Pradnya Meshram 1, Prof. S.S. Wankhede 2 1 Scholar, Department of Electronics Engineering, G.H.Raisoni College of Engineering, Digdoh

### In addition to looking for applications that can be profitably examined algebraically,

The mathematics of stopping your car Eric Wood National Institute of Education, Singapore In addition to looking for applications that can be profitably examined algebraically, numerically

### Towards Online Recognition of Handwritten Mathematics

Towards Online Recognition of Handwritten Mathematics Vadim Mazalov, joint work with Oleg Golubitsky and Stephen M. Watt Ontario Research Centre for Computer Algebra Department of Computer Science Western

### Level Set Framework, Signed Distance Function, and Various Tools

Level Set Framework Geometry and Calculus Tools Level Set Framework,, and Various Tools Spencer Department of Mathematics Brigham Young University Image Processing Seminar (Week 3), 2010 Level Set Framework

### Experiments on the local load balancing algorithms; part 1

Experiments on the local load balancing algorithms; part 1 Ştefan Măruşter Institute e-austria Timisoara West University of Timişoara, Romania maruster@info.uvt.ro Abstract. In this paper the influence