Multi-view video acquisition is widely used for reconstruction and free-viewpoint rendering of dynamic scenes by directly resampling from the captured images. This paper addresses the problem of optimally resampling and representing multi-view video to obtain a compact representation without loss of the view-dependent dynamic surface appearance. Spatio-temporal optimisation of the multi-view re...

One way to handle data mining problems where class prior probabilities and/or misclassification costs between classes are highly unequal is to resample the data until a new, desired class distribution in the training data is achieved. Many resampling techniques have been proposed in the past, and the relationship between resampling and cost-sensitive learning has been well studied. Surprisingly...

In Guided Evolutionary Multi-objective Optimization the goal is to find a diverse, but locally focused non-dominated front in a decision maker’s area of interest, as close as possible to the true Paretofront. The optimization can focus its efforts towards the preferred area and achieve a better result [9, 17, 7, 13]. The modeled and simulated systems are often stochastic and a common method to ...

Resampling is the process of selecting from a set candidate samples to achieve distribution (approximately) proportional desired target. Recent work has revisited its application Monte Carlo integration, yielding powerful and practical importance sampling methods. One drawback existing resampling methods that they cannot generate stratified samples. We propose two complementary techniques effic...

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive o...

A resampling scheme for clustering with similarity to bootstrap aggregation (bagging) is presented. Bagging is used to improve the quality of pathbased clustering, a data clustering method that can extract elongated structures from data in a noise robust way. The results of an agglomerative optimization method are influenced by small fluctuations of the input data. To increase the reliability o...

Broadband underwater acoustic communication signals undergo either a compression or dilation in the presence of relative motion between a source and a receiver. Consequently, underwater acoustic communications with a mobile source/receiver require Doppler compensation through resampling. However, resampling may not be necessary when a channel-estimate-based time reversal approach is applied wit...

Wavelet analysis is now frequently used to extract information from ecological and epidemiological time series. Statistical hypothesis tests are conducted on associated wavelet quantities to assess the likelihood that they are due to a random process. Such random processes represent null models and are generally based on synthetic data that share some statistical characteristics with the origin...

This paper presents a proficiently developed resampling algorithm for particle filtering. In any filtering algorithm adopting the perception of particles, especially in visual tracking, resampling is an essential process that determines the algorithm’s performance and accuracy in the implementation step. It is usually a linear function of the weight of the particles, which determines the number...

This letter provides an adaptive resampling method. It determines the number of particles to resample so that the Kullback–Leibler distance (KLD) between distribution of particles before resampling and after resampling does not exceed a pre-specified error bound. The basis of the method is the same as Fox’s KLD-sampling but implemented differently. The KLD-sampling assumes that samples are comi...