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» Learning with Local Drift Detection
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CVPR
2007
IEEE
16 years 3 months ago
Robust Click-Point Linking: Matching Visually Dissimilar Local Regions
This paper presents robust click-point linking: a novel localized registration framework that allows users to interactively prescribe where the accuracy has to be high. By emphasi...
Kazunori Okada, Xiaolei Huang
ECCV
2006
Springer
16 years 3 months ago
Learning Compositional Categorization Models
Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
Björn Ommer, Joachim M. Buhmann
CVPR
2010
IEEE
15 years 10 months ago
Chaotic Invariants of Lagrangian Particle Trajectories for Anomaly Detection in Crowded Scenes
A novel method for crowd flow modeling and anomaly detection is proposed for both coherent and incoherent scenes. The novelty is revealed in three aspects. First, it is a unique ut...
Shandong Wu, Brian E. Moore, and Mubarak Shah
123
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IPSN
2004
Springer
15 years 7 months ago
Distributed online localization in sensor networks using a moving target
We describe a novel method for node localization in a sensor network where there are a fraction of reference nodes with known locations. For application-specific sensor networks, ...
Aram Galstyan, Bhaskar Krishnamachari, Kristina Le...
ICCV
2007
IEEE
16 years 3 months ago
Learning Structured Appearance Models from Captioned Images of Cluttered Scenes
Given an unstructured collection of captioned images of cluttered scenes featuring a variety of objects, our goal is to learn both the names and appearances of the objects. Only a...
Michael Jamieson, Afsaneh Fazly, Sven J. Dickinson...