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» Describing texture directions with Von Mises distributions
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ICIP
2004
IEEE
14 years 9 months ago
A probabilistic framework for object recognition in video
We propose a solution to the problem of object recognition given a continuous video sequence containing multiple views of an object. Initially, object models are acquired from ima...
Omar Javed, Mubarak Shah, Dorin Comaniciu
BMCBI
2010
229views more  BMCBI 2010»
13 years 7 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
ICCV
1999
IEEE
14 years 9 months ago
Correlation Model for 3D Texture
While an exact definition of texture is somewhat elusive, texture can be qualitatively described as a distribution of color, albedo or local normal on a surface. In the literature...
Kristin J. Dana, Shree K. Nayar
WSCG
2004
217views more  WSCG 2004»
13 years 9 months ago
Blending Textured Images Using a Non-parametric Multiscale MRF Method
In this paper we describe a new method for improving the representation of textures in blends of multiple images based on a Markov Random Field (MRF) algorithm. We show that direc...
Bernard Tiddeman
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
14 years 8 months ago
Eigenspace-based anomaly detection in computer systems
We report on an automated runtime anomaly detection method at the application layer of multi-node computer systems. Although several network management systems are available in th...
Hisashi Kashima, Tsuyoshi Idé