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» Online Empirical Evaluation of Tracking Algorithms
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ICPR
2004
IEEE
15 years 10 months ago
Switching Particle Filters for Efficient Real-time Visual Tracking
Particle filtering is an approach to Bayesian estimation of intractable posterior distributions from time series signals distributed by non-Gaussian noise. A couple of variant par...
Kenji Doya, Shin Ishii, Takashi Bando, Tomohiro Sh...
CVPR
2008
IEEE
15 years 11 months ago
Visual tracking via incremental Log-Euclidean Riemannian subspace learning
Recently, a novel Log-Euclidean Riemannian metric [28] is proposed for statistics on symmetric positive definite (SPD) matrices. Under this metric, distances and Riemannian means ...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
CIKM
2010
Springer
14 years 8 months ago
Online learning for recency search ranking using real-time user feedback
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
Taesup Moon, Lihong Li, Wei Chu, Ciya Liao, Zhaohu...
IWCMC
2010
ACM
15 years 2 months ago
Energy-aware online routing with QoS constraints in multi-rate wireless ad hoc networks
Wireless ad hoc networks consist of hundreds to thousands of mobile nodes that are powered by batteries. To prolong the network operational time, energy conservation in such netwo...
Wei Yang, Weifa Liang, Jun Luo, Wenhua Dou
ICCV
2009
IEEE
2030views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Robust Tracking-by-Detection using a Detector Confidence Particle Filter
We propose a novel approach for multi-person trackingby- detection in a particle filtering framework. In addition to final high-confidence detections, our algorithm uses the con...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...