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17 years 3 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
CVPR
2009
IEEE
2358views Computer Vision» more  CVPR 2009»
16 years 11 months ago
Pictorial Structures Revisited: People Detection and Articulated Pose Estimation
Non-rigid object detection and articulated pose estimation are two related and challenging problems in computer vision. Numerous models have been proposed over the years and oft...
Mykhaylo Andriluka (TU Darmstadt), Stefan Roth (TU...
CVPR
2009
IEEE
16 years 11 months ago
The Geometry of 2D Image Signals
This paper covers a fundamental problem of local phase based signal processing: the isotropic generalization of the classical 1D analytic signal to two dimensions. The well know...
Lennart Wietzke (Kiel University), Gerald Sommer (...
CVPR
2006
IEEE
16 years 6 months ago
Context and Hierarchy in a Probabilistic Image Model
It is widely conjectured that the excellent ROC performance of biological vision systems is due in large part to the exploitation of context at each of many levels in a part/whole...
Ya Jin, Stuart Geman
CVPR
2007
IEEE
16 years 6 months ago
Objects in Action: An Approach for Combining Action Understanding and Object Perception
Analysis of videos of human-object interactions involves understanding human movements, locating and recognizing objects and observing the effects of human movements on those obje...
Abhinav Gupta, Larry S. Davis