PFAAM An Active Appearance Model based Particle Filter for both Robust and Precise Tracking

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Fourth Canadian Conference on Computer and Robot Vision (CRV '07)

Montreal, Quebec, Canada

May 28-May 30

ISBN: 0-7695-2786-8

	ASCII Text	x
	Sven , McElory Hoffmann, Karin Hunter, Andreas Schilling, "PFAAM An Active Appearance Model based Particle Filter for both Robust and Precise Tracking," Computer and Robot Vision, Canadian Conference, pp. 339-346, Fourth Canadian Conference on Computer and Robot Vision (CRV '07), 2007.

	BibTex	x
	@article{ 10.1109/CRV.2007.50, author = {Sven and McElory Hoffmann and Karin Hunter and Andreas Schilling}, title = {PFAAM An Active Appearance Model based Particle Filter for both Robust and Precise Tracking}, journal ={Computer and Robot Vision, Canadian Conference}, volume = {0}, year = {2007}, isbn = {0-7695-2786-8}, pages = {339-346}, doi = {http://doi.ieeecomputersociety.org/10.1109/CRV.2007.50}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer and Robot Vision, Canadian Conference TI - PFAAM An Active Appearance Model based Particle Filter for both Robust and Precise Tracking SN - 0-7695-2786-8 SP339 EP346 A1 - Sven , A1 - McElory Hoffmann, A1 - Karin Hunter, A1 - Andreas Schilling, PY - 2007 KW - null VL - 0 JA - Computer and Robot Vision, Canadian Conference ER -

Sven, University of Tubingen

McElory Hoffmann, University of Stellenbosch

Karin Hunter, University of Stellenbosch

Andreas Schilling, University of Tubingen

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CRV.2007.50

Model based tracking is one key component of many systems today, e.g. within video surveillance or human computer interfaces (HCI). Our approach consists of a combination of particle filters (PFs) and active appearance models (AAMs): the PFAAM. It combines the robustness of PFs with the precision of AAMs. Experimental results are given. PFAAM shows superior perfomance compared to both standard AAMs and PFs using AAMs as cues only, i.e. without using a local optimization loop.

Citation:

Sven , McElory Hoffmann, Karin Hunter, Andreas Schilling, "PFAAM An Active Appearance Model based Particle Filter for both Robust and Precise Tracking," crv, pp.339-346, Fourth Canadian Conference on Computer and Robot Vision (CRV '07), 2007

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