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ICPR
2002
IEEE
12 years 9 months ago
Interacting Multiple Model (IMM) Kalman Filters for Robust High Speed Human Motion Tracking
Accurate and robust tracking of humans is of growing interest in the image processing and computer vision communities. The ability of a vision system to track the subjects and acc...
Michael E. Farmer, Rein-Lien Hsu, Anil K. Jain
TSP
2008
178views more  TSP 2008»
11 years 8 months ago
Extended Object Tracking Using Monte Carlo Methods
Abstract-- This paper addresses the problem of tracking extended objects, such as ships or a convoy of vehicles moving in urban environment. Two Monte Carlo techniques for extended...
Donka S. Angelova, Lyudmila Mihaylova
EICS
2009
ACM
12 years 2 months ago
Input evaluation of an eye-gaze-guided interface: Kalman filter vs. velocity threshold eye movement identification
This paper evaluates the input performance capabilities of Velocity Threshold (I-VT) and Kalman Filter (I-KF) eye movement detection models when employed for eye-gaze-guided inter...
Do Hyong Koh, Sandeep A. Munikrishne Gowda, Oleg V...
ICRA
2002
IEEE
104views Robotics» more  ICRA 2002»
12 years 1 months ago
Improbability Filtering for Rejecting False Positives
—In this paper we describe a novel approach, called improbability filtering, to rejecting false-positive observations from degrading the tracking performance of an Extended Kalma...
Brett Browning, Michael H. Bowling, Manuela M. Vel...
BMVC
2010
11 years 6 months ago
Manifold Learning for ToF-based Human Body Tracking and Activity Recognition
In this paper, we propose a method for simultaneous human full-body pose tracking and activity recognition from time-of-flight (ToF) camera images. Simple and sparse depth cues ar...
Loren Arthur Schwarz, Diana Mateus, Victor Castane...
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