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» Describing texture directions with Von Mises distributions
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ICIP
2004
IEEE
15 years 11 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»
14 years 9 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
15 years 11 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»
14 years 11 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»
15 years 10 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