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CVPR
2011
IEEE
15 years 27 days ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
ICPR
2008
IEEE
16 years 5 months ago
NorMaL: Non-compact Markovian Likelihood for change detection
This paper presents a new normalcy model of a scene for change detection using images taken from multiple views and varying illumination conditions. Each coregistered pixel site i...
David B. Cooper, Joseph L. Mundy, Osman Gokhan Sez...
228
Voted
CVPR
2009
IEEE
1216views Computer Vision» more  CVPR 2009»
16 years 11 months ago
Marked Point Processes for Crowd Counting
A Bayesian marked point process (MPP) model is developed to detect and count people in crowded scenes. The model couples a spatial stochastic process governing number and placem...
Robert T. Collins, Weina Ge
SIGGRAPH
1998
ACM
15 years 8 months ago
A Beam Tracing Approach to Acoustic Modeling for Interactive Virtual Environments
Virtual environment research has focused on interactive image generation and has largely ignored acoustic modeling for spatialization of sound. Yet, realistic auditory cues can co...
Thomas A. Funkhouser, Ingrid Carlbom, Gary Elko, G...
141
Voted
ICPR
2008
IEEE
16 years 5 months ago
Parametric video compression using appearance space
The novelty of the approach presented in this paper is the unique object-based video coding framework for videos obtained from a static camera. As opposed to most existing methods...
Santanu Chaudhury, Subarna Tripathi, Sumantra Dutt...