NDLI: MIMIC: Mobile mapping point density calculator

Please wait, while we are loading the content...

A promising future of computing for geospatial technologies

Big data computing for traffic information by GPS sensing

Realizing the geospatial potential of mobile, IoT and big data

Fast k-clustering queries on embeddings of road networks

Spatial analysis of Ohio police station locations using geographical information systems

Real-time 3-D mapping for robotic applications

Modeling spatial dependencies and semantic concepts in data mining

Science in times of crisis: delivering situational awareness to emergency managers and the public when disaster strikes

Computational intelligence and neuromorphic computing potential for geospatial research and applications

Cloud computing & big data computing

Wavelet-based automated river network generalization

Query optimization with value path materialization in column-stored DWMS

A machine learning system for recognizing subclasses

On clusterization of "big data" streams

Cloud/big data computing for defense

Exploring multivariate spatio-temporal change in climate data using image analysis techniques

Performance comparisons of spatial data processing techniques for a large scale mobile phone dataset

ArchaeoSTOR map: publishing archaeological geodata on the web

Connecting islands in the internet of things

CiVicinity events: pairing geolocation tools with a community calendar

On clusterization of "big data" streams

Variation of flow pattern in waterways due to degradation and aggradation

Big data and advanced spatial analytics

MIMIC: Mobile mapping point density calculator

Fast visibility analysis in 3D procedural modeling environments

Metadata management and revision history tracking for spatial data and GIS map figures

LiDAR data management pipeline; from spatial database population to web-application visualization

Constructing natural neighbor interpolation based grid DEM using CUDA

MapMyTrip app for Android smart phone

Temporally coherent real-time labeling of dynamic scenes

Airborne geo-location for search and rescue applications

Identical entity matching from multi-source spatial data

Towards a collaborative geosocial analysis workbench

Image-based structural damage assessment with sensor fusion

Evidence theory for reputation-based trust in wireless sensor networks

Retrieving large-scale high density video target tracks from spatial database

Real-time spatio-temporal analysis of West Nile virus using Twitter data

City-scale urban transport and dispersion simulation using geographic information system footprints

Modeling urban extent and density using radio artifacts from cellular and WiFi beacons

A practical approach to developing a web-based geospatial workflow composition and execution system

Mapping environmental pollution, contamination, and waste in the United States

An open source virtual globe framework for iOS, Android and WebGL compliant browser

Effectiveness of scalable vector graphics (SVG) for client-side vector mapping

National fire alert and monitoring system

Transport and dispersion simulation in downtown Oklahoma City and New York City

Cloud to host legacy airport layout plans and orthoimages

MIMIC: Mobile mapping point density calculator

Content Provider	ACM Digital Library
Author	Cahalane, Conor McCarthy, Tim McElhinney, Conor P.
Abstract	The current generation of Mobile Mapping Systems (MMSs) capture increasingly larger amounts of data in a short time frame. Due to the relative novelty of this technology there is no concrete understanding of the point density that different hardware configurations and operating parameters will exhibit on objects at specific distances. Depending on the project requirements, obtaining the required point density impacts on survey time, processing time, data storage and is the underlying limit of automated algorithms. A limited understanding of the capabilities of these systems means that defining point density in project specifications is a complicated process. We are in the process of developing a method for determining the quantitative resolution of point clouds collected by a MMS with respect to known objects at specified distances. We have previously demonstrated the capabilities of our system for calculating point spacing, profile angle and profile spacing individually. Each of these elements are a major factor in calculating point density on arbitrary objects, such as road signs, poles or buildings -all important features in asset management surveys. This paper will introduce the current version of the MobIle Mapping point densIty Calculator (MIMIC), MIMIC's visualisation module and finally discuss the methods employed to validate our work.
Starting Page	1
Ending Page	9
Page Count	9
File Format	PDF
ISBN	9781450311137
DOI	10.1145/2345316.2345335
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-07-01
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Mobile mapping Point density Lidar
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

MIMIC: An Innovative Methodology for Determining Mobile Laser Scanning System Point Density

Disturbance Analysis in the Classification of Objects Obtained from Urban LiDAR Point Clouds with Convolutional Neural Networks

Grammar supported Facade Reconstruction from Mobile LiDAR Mapping (2009)

Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping

HAALA N.: Grammar supported facade reconstruction from mobile lidar mapping

Ideal Angular Orientation of Selected 64-Channel Multi Beam Lidars for Mobile Mapping Systems

Improving MMS Performance during Infrastructure Surveys through Geometry Aided Design

3D crack skeleton extraction from mobile LiDAR point clouds

Velobug: a mobile system for 3D indoor mapping

MIMIC: Mobile mapping point density calculator

Similar Documents

MIMIC: An Innovative Methodology for Determining Mobile Laser Scanning System Point Density

Disturbance Analysis in the Classification of Objects Obtained from Urban LiDAR Point Clouds with Convolutional Neural Networks

Grammar supported Facade Reconstruction from Mobile LiDAR Mapping (2009)

Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping

HAALA N.: Grammar supported facade reconstruction from mobile lidar mapping

Ideal Angular Orientation of Selected 64-Channel Multi Beam Lidars for Mobile Mapping Systems

Improving MMS Performance during Infrastructure Surveys through Geometry Aided Design

3D crack skeleton extraction from mobile LiDAR point clouds

Velobug: a mobile system for 3D indoor mapping

MIMIC: Mobile mapping point density calculator