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CVPR
2004
IEEE
14 years 10 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
VLDB
2004
ACM
104views Database» more  VLDB 2004»
14 years 1 months ago
Remembrance of Streams Past: Overload-Sensitive Management of Archived Streams
This paper studies Data Stream Management Systems that combine real-time data streams with historical data, and hence access incoming streams and archived data simultaneously. A s...
Sirish Chandrasekaran, Michael J. Franklin
ICRA
2010
IEEE
259views Robotics» more  ICRA 2010»
13 years 5 months ago
RANSAC matching: Simultaneous registration and segmentation
The iterative closest points (ICP) algorithm is widely used for ego-motion estimation in robotics, but subject to bias in the presence of outliers. We propose a random sample conse...
Shao-Wen Yang, Chieh-Chih Wang, Chun-Hua Chang
ML
2008
ACM
248views Machine Learning» more  ML 2008»
13 years 7 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
UAI
2004
13 years 9 months ago
Dependent Dirichlet Priors and Optimal Linear Estimators for Belief Net Parameters
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
Peter Hooper