NDLI: Online Algorithms for Classification of Urban Objects in 3D Point Clouds

Content Provider	IEEE Xplore Digital Library
Author	Stamos, I. Hadjiliadis, O. Hongzhong Zhang Flynn, T.
Copyright Year	2012
Abstract	The current technology in stationary laser range-scanning enables high-resolution acquisition of 3D data in a sequential fashion. Traditionally, range scans are processed offline after acquisition, which significantly slows down the procedure. In this work we alleviate this limitation by developing low-complexity, online detection and classification algorithms. These algorithms are innovative in that they classify points into 5 distinct classes (vegetation, vertical, horizontal, car and curb regions) and robustly determine the level of the ground without requiring any prior training or parameter estimation. To construct these algorithms we extract cleverly chosen summary statistics which significantly reduce the dimensionality of the data. This reduction enables us to contrast the different classes by appropriately chosen Markov models and then use online techniques to detect a transition from one Markov model to the other. The identification of the ground level is further achieved by taking advantage of statistical properties of the distribution of the summary statistics. Our algorithms also use contextual cues to verify the existence of specific classes of objects. All our algorithms take advantage of the sequential nature of data acquisition by running in parallel and labeling points on-the-fly. Thus, these algorithms can be potentially integrated with the scanner's hardware and provide the foundation for the construction of high-resolution 3D data scanners that classify data as acquired. We have run experiments using complex urban range scans and have evaluated the classification accuracy against ground-truth.
Starting Page	332
Ending Page	339
File Size	817000
Page Count	8
File Format	PDF
ISBN	9781467344708
e-ISBN	9780769548739
DOI	10.1109/3DIMPVT.2012.75
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-13
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vegetation mapping Hidden Markov models Surface emitting lasers Vegetation Markov processes Vectors Classification algorithms
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

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