Robust dense reconstruction by range merging based on confidence estimation

Region Merging Based on Robust Statistical Testing

This paper addresses the problem of nding moving objects present in an image sequence. More speciically, a method is proposed to merge regions based on a coherent motion criterion. A Modiied Kolmogorov-Smirnov test is proposed which exploits both the motion information present in the residual distribution and the motion information of the motion parameter space. Therefore, all the available mot...

Confidence Intervals Based on Robust Estimators

Lexical tuning based on triphone confidence estimation

We propose and test a practical means of finding poor pronunciations and missing variants for large lexicons. We do so by statistically assessing the confidence of each phone in each pronunciation and comparing it with the statistical distribution of the same confidence metric for corresponding phones over the entire training corpus. A phone is targeted for correction for each word in which its...

Multi-represented Classification Based on Confidence Estimation

Complex objects are often described by multiple representations modeling various aspects and using various feature transformations. To integrate all information into classification, the common way is to train a classifier on each representation and combine the results based on the local class probabilities. In this paper, we derive so-called confidence estimates for each of the classifiers refl...

Optical Flow Estimation with Confidence Measures for Super-resolution based on Recursive Robust Total Least Squares

In this paper we propose a novel optical flow estimation method accompanied by confidence measures. Our main goal is fast and highly accurate motion estimation in regions where information is available and a confidence measure which identifies these regions. Therefore we extend the structure tensor method to robust recursive total least squares (RRTLS) and run it on a GPU for real-time processi...