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» Input Modeling Using Quantile Statistical Methods
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TCSV
2008
291views more  TCSV 2008»
13 years 7 months ago
A Statistical Video Content Recognition Method Using Invariant Features on Object Trajectories
Abstract--This work is dedicated to a statistical trajectorybased approach addressing two issues related to dynamic video content understanding: recognition of events and detection...
Alexandre Hervieu, Patrick Bouthemy, Jean-Pierre L...
FGR
2000
IEEE
162views Biometrics» more  FGR 2000»
13 years 11 months ago
Person Tracking in Real-World Scenarios Using Statistical Methods
This paper presents a novel approach to robust and flexible person tracking using an algorithm that combines two powerful stochastic modeling techniques: The first one is the tech...
Gerhard Rigoll, Stefan Eickeler, Stefan Mülle...
NAACL
2001
13 years 9 months ago
Applying Co-Training Methods to Statistical Parsing
We propose a novel Co-Training method for statistical parsing. The algorithm takes as input a small corpus (9695 sentences) annotated with parse trees, a dictionary of possible le...
Anoop Sarkar
GRAPHICSINTERFACE
2003
13 years 9 months ago
Input-based Language Modelling in the Design of High Performance Text Input Techniques
We present a critique of language-based modelling for text input research, and propose an alternative inputbased approach. Current language-based statistical models are derived fr...
R. William Soukoreff, I. Scott MacKenzie
ICIP
2004
IEEE
14 years 9 months ago
Unsupervised motion detection using a markovian temporal model with global spatial constraints
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
Pierre-Marc Jodoin, Max Mignotte