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» Adaptive object tracking by learning background context
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ECCV
2006
Springer
14 years 11 months ago
Robust Head Tracking with Particles Based on Multiple Cues Fusion
This paper presents a fully automatic and highly robust head tracking algorithm based on the latest advances in real-time multi-view face detection techniques and multiple cues fus...
Yuan Li, Haizhou Ai, Chang Huang, Shihong Lao
ECCV
2004
Springer
15 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...

Publication
1301views
15 years 9 months ago
Markovian Tracking-by-Detection from a Single, Uncalibrated Camera
We present an algorithm for multi-person tracking-bydetection in a particle filtering framework. To address the unreliability of current state-of-the-art object detectors, our a...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...
ECCV
2010
Springer
14 years 10 months ago
Adapting Visual Category Models to New Domains
Abstract. Domain adaptation is an important emerging topic in computer vision. In this paper, we present one of the first studies of domain shift in the context of object recogniti...
Kate Saenko, Brian Kulis, Mario Fritz, Trevor Darr...
PAMI
2006
243views more  PAMI 2006»
14 years 9 months ago
Dynamical Statistical Shape Priors for Level Set-Based Tracking
In recent years, researchers have proposed to introduce statistical shape knowledge into level set based segmentation methods in order to cope with insufficient low-level informati...
Daniel Cremers