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» Gibbs Likelihoods for Bayesian Tracking
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TSP
2008
139views more  TSP 2008»
13 years 7 months ago
Bayesian Filtering With Random Finite Set Observations
This paper presents a novel and mathematically rigorous Bayes recursion for tracking a target that generates multiple measurements with state dependent sensor field of view and clu...
Ba-Tuong Vo, Ba-Ngu Vo, Antonio Cantoni
ICMCS
2006
IEEE
234views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Decentralized Multiple Camera Multiple Object Tracking
In this paper, we present a novel decentralized Bayesian framework using multiple collaborative cameras for robust and efficient multiple object tracking with significant and pe...
Wei Qu, Dan Schonfeld, Magdi A. Mohamed
PAMI
2008
188views more  PAMI 2008»
13 years 7 months ago
Segmentation and Tracking of Multiple Humans in Crowded Environments
Segmentation and tracking of multiple humans in crowded situations is made difficult by interobject occlusion. We propose a model-based approach to interpret the image observations...
Tao Zhao, Ramakant Nevatia, Bo Wu
BMCBI
2008
186views more  BMCBI 2008»
13 years 7 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
CVPR
2012
IEEE
11 years 10 months ago
City scale geo-spatial trajectory estimation of a moving camera
This paper presents a novel method for estimating the geospatial trajectory of a moving camera with unknown intrinsic parameters, in a city-scale urban environment. The proposed m...
Gonzalo Vaca-Castano, Amir Roshan Zamir, Mubarak S...