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ICPR
2006
IEEE
16 years 7 months ago
Background Robust Object Labeling by Voting of Weight-Aggregated Local Features
In this paper, we present a new voting-based object labeling method that is robust to background clutter. The conventional simple voting method shows very poor performance under c...
In-So Kweon, Kuk-Jin Yoon, Sungho Kim
ICML
2005
IEEE
16 years 7 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
ICPR
2008
IEEE
16 years 2 months ago
Online Feature Evaluation For Object Tracking Using Kalman Filter
An online feature evaluation method for visual object tracking is put forward in this paper. Firstly, a combined feature set is built using color histogram (HC) bins and gradien...
Zhenjun Han, Qixiang Ye, Jianbin Jiao+
ICIAR
2004
Springer
16 years 1 days ago
Learning an Information Theoretic Transform for Object Detection
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
Jianzhong Fang, Guoping Qiu
TIDSE
2004
Springer
16 years 16 hour ago
Object Oriented Prompted Play (O2P2): A Pragmatic Approach to Interactive Narrative
We describe an interactive narrative system that embodies Object Oriented Prompted Play (O2P2). This means that behaviours, attributes, and crucially stories are attached to object...
Daniel Roberts, Mark Wright