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...
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, ...
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...
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...
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 ...