Segmentation and Classification of Human Forms using LADAR Data

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35th Applied Imagery and Pattern Recognition Workshop (AIPR'06)

Washington, DC, USA

October 11-October 13

ISBN: 0-7695-2739-6

	ASCII Text	x
	James S. Albus, Tsai Hong, Tommy Chang, "Segmentation and Classification of Human Forms using LADAR Data," Applied Image Pattern Recognition Workshop,, pp. 7, 35th Applied Imagery and Pattern Recognition Workshop (AIPR'06), 2006.

	BibTex	x
	@article{ 10.1109/AIPR.2006.35, author = {James S. Albus and Tsai Hong and Tommy Chang}, title = {Segmentation and Classification of Human Forms using LADAR Data}, journal ={Applied Image Pattern Recognition Workshop,}, volume = {0}, year = {2006}, issn = {1550-5219}, pages = {7}, doi = {http://doi.ieeecomputersociety.org/10.1109/AIPR.2006.35}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Applied Image Pattern Recognition Workshop, TI - Segmentation and Classification of Human Forms using LADAR Data SN - 1550-5219 SP EP A1 - James S. Albus, A1 - Tsai Hong, A1 - Tommy Chang, PY - 2006 KW - null VL - 0 JA - Applied Image Pattern Recognition Workshop, ER -

James S. Albus, Intelligent Systems Division National Institute of Standards and Technology

Tsai Hong, Intelligent Systems Division National Institute of Standards and Technology

Tommy Chang, Intelligent Systems Division National Institute of Standards and Technology

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AIPR.2006.35

High resolution LADAR (LAser Detection and Ranging) images of scenes containing human forms have been automatically segmented and simple algorithms have been developed for recognizing human forms in various positions in both cluttered and uncluttered scenes. Registration of LADAR and color CCD images is suggested as a method to enhance the ability to segment both types of images.

Citation:

James S. Albus, Tsai Hong, Tommy Chang, "Segmentation and Classification of Human Forms using LADAR Data," aipr, pp.7, 35th Applied Imagery and Pattern Recognition Workshop (AIPR'06), 2006

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