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» Novel Observation Model for Probabilistic Object Tracking
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AVSS
2008
IEEE
14 years 3 months ago
Object and Scene-Centric Activity Detection Using State Occupancy Duration Modeling
We propose a video event analysis framework based on object segmentation and tracking, combined with a Hidden Semi-Markov Model (HSMM) that uses state occupancy duration modeling....
Murtaza Taj, Andrea Cavallaro
BMCBI
2006
91views more  BMCBI 2006»
13 years 9 months ago
Cheminformatics methods for novel nanopore analysis of HIV DNA termini
Background: Channel current feature extraction methods, using Hidden Markov Models (HMMs) have been designed for tracking individual-molecule conformational changes. This informat...
Stephen Winters-Hilt, Matthew Landry, Mark Akeson,...
TROB
2008
118views more  TROB 2008»
13 years 8 months ago
A New Kalman-Filter-Based Framework for Fast and Accurate Visual Tracking of Rigid Objects
The best of Kalman-filter-based frameworks reported in the literature for rigid object tracking work well only if the object motions are smooth (which allows for tight uncertainty ...
Youngrock Yoon, Akio Kosaka, Avinash C. Kak
ICRA
2009
IEEE
137views Robotics» more  ICRA 2009»
14 years 3 months ago
Unsupervised learning of 3D object models from partial views
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...
JMM2
2007
212views more  JMM2 2007»
13 years 8 months ago
Flux Tensor Constrained Geodesic Active Contours with Sensor Fusion for Persistent Object Tracking
— This paper makes new contributions in motion detection, object segmentation and trajectory estimation to create a successful object tracking system. A new efficient motion det...
Filiz Bunyak, Kannappan Palaniappan, Sumit Kumar N...