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» Visual Tracking with Online Multiple Instance Learning
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MMM
2007
Springer
114views Multimedia» more  MMM 2007»
14 years 1 months ago
Mining Multiple Visual Appearances of Semantics for Image Annotation
This paper investigates the problem of learning the visual semantics of keyword categories for automatic image annotation. Supervised learning algorithms which learn only a single ...
Hung-Khoon Tan, Chong-Wah Ngo
TOMCCAP
2010
202views more  TOMCCAP 2010»
13 years 2 months ago
Audio-visual atoms for generic video concept classification
We investigate the challenging issue of joint audio-visual analysis of generic videos targeting at semantic concept detection. We propose to extract a novel representation, the Sh...
Wei Jiang, Courtenay V. Cotton, Shih-Fu Chang, Dan...
CORR
2010
Springer
124views Education» more  CORR 2010»
13 years 7 months ago
Online Learning of Noisy Data with Kernels
We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
ICCV
2009
IEEE
15 years 17 days ago
Joint learning of visual attributes, object classes and visual saliency
We present a method to learn visual attributes (eg.“red”, “metal”, “spotted”) and object classes (eg. “car”, “dress”, “umbrella”) together. We assume imag...
Gang Wang, David Forsyth
WACV
2012
IEEE
12 years 3 months ago
Online discriminative object tracking with local sparse representation
We propose an online algorithm based on local sparse representation for robust object tracking. Local image patches of a target object are represented by their sparse codes with a...
Qing Wang, Feng Chen, Wenli Xu, Ming-Hsuan Yang