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» Multiple Object Tracking Using Local PCA
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ICCV
2009
IEEE
13 years 6 months ago
Non-rigid object localization and segmentation using eigenspace representation
This paper presents a novel non-rigid object localization and segmentation algorithm using an eigenspace representation. Previous approaches to eigenspace methods for object track...
Omar Arif, Patricio A. Vela
MIAR
2006
IEEE
14 years 2 months ago
Statistics of Pose and Shape in Multi-object Complexes Using Principal Geodesic Analysis
Abstract. A main focus of statistical shape analysis is the description of variability of a population of geometric objects. In this paper, we present work in progress towards mode...
Martin Styner, Kevin Gorczowski, P. Thomas Fletche...
AMCS
2008
146views Mathematics» more  AMCS 2008»
13 years 8 months ago
Fault Detection and Isolation with Robust Principal Component Analysis
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
Yvon Tharrault, Gilles Mourot, José Ragot, ...
CLEAR
2006
Springer
116views Biometrics» more  CLEAR 2006»
13 years 12 months ago
Multi-and Single View Multiperson Tracking for Smart Room Environments
Abstract. Simultaneous tracking of multiple persons in real world environments is an active research field and several approaches have been proposed, based on a variety of features...
Keni Bernardin, Tobias Gehrig, Rainer Stiefelhagen
ICPR
2006
IEEE
14 years 9 months ago
Robust Tracking of Multiple People in Crowds Using Laser Range Scanners
Laser based people tracking systems have been developed for mobile robotic or intelligent surveillance areas. Existing systems rely on laser point clustering to extract object loc...
Jinshi Cui, Hongbin Zha, Huijing Zhao, Ryosuke Shi...