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» Probabilistic Object Tracking Using Multiple Features
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ICPR
2010
IEEE
14 years 3 months ago
Object Recognition and Localization Via Spatial Instance Embedding
—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...
Nazli Ikizler Cinbis, Stan Sclaroff
IAJIT
2010
95views more  IAJIT 2010»
13 years 7 months ago
Modelling of Updating Moving Object Database Using Timed Petri Net Model
: Tracking moving objects is one of the most common requirements for many location-based applications. The location of a moving object changes continuously but the database locatio...
Hatem Abdul-Kader, Warda El-Kholy
ICIP
2005
IEEE
14 years 11 months ago
Novel likelihood estimation technique based on boosting detector
This paper presents novel likelihood estimation to be used for particle filter based object tracking. The likelihood estimation is built upon cascade object detector trained with ...
Haijing Wang, Peihua Li, Tianwen Zhang
ECCV
2004
Springer
14 years 11 months ago
A Boosted Particle Filter: Multitarget Detection and Tracking
The problem of tracking a varying number of non-rigid objects has two major difficulties. First, the observation models and target distributions can be highly non-linear and non-Ga...
Kenji Okuma, Ali Taleghani, Nando de Freitas, Jame...
NIPS
2008
13 years 10 months ago
Structured ranking learning using cumulative distribution networks
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
Jim C. Huang, Brendan J. Frey