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» A Probabilistic Background Model for Tracking
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CVPR
2005
IEEE
14 years 9 months ago
Bayesian Object Detection in Dynamic Scenes
Detecting moving objects using stationary cameras is an important precursor to many activity recognition, object recognition and tracking algorithms. In this paper, three innovati...
Yaser Sheikh, Mubarak Shah
ALMOB
2008
82views more  ALMOB 2008»
13 years 7 months ago
Protein sequence and structure alignments within one framework
Background: Protein structure alignments are usually based on very different techniques to sequence alignments. We propose a method which treats sequence, structure and even combi...
Gundolf Schenk, Thomas Margraf, Andrew E. Torda
PREMI
2005
Springer
14 years 1 months ago
Hybrid Hierarchical Learning from Dynamic Scenes
The work proposes a hierarchical architecture for learning amic scenes at various levels of knowledge abstraction. The raw visual information is processed at different stages to g...
Prithwijit Guha, Pradeep Vaghela, Pabitra Mitra, K...
CEC
2007
IEEE
13 years 11 months ago
Mobile robot global localization using differential evolution and particle swarm optimization
For a mobile robot to move in a known environment and operate successfully, first it needs to robustly determine its initial position and orientation relative to the map, and then ...
Ali R. Vahdat, Naser NourAshrafoddin, Saeed Shiry ...
ICCV
2005
IEEE
14 years 1 months ago
LOCUS: Learning Object Classes with Unsupervised Segmentation
We address the problem of learning object class models and object segmentations from unannotated images. We introduce LOCUS (Learning Object Classes with Unsupervised Segmentation...
John M. Winn, Nebojsa Jojic