Most motion-based tracking algorithms assume that objects undergo rigid motion, which is most likely disobeyed in real world. In this paper, we present a novel motionbased trackin...
While subjectivity related research in other languages has increased, most of the work focuses on single languages. This paper explores the integration of features originating fro...
An operational framework is developed for testing stationarity relatively to an observation scale, in both stochastic and deterministic contexts. The proposed method is based on a ...
Pierre Borgnat, Patrick Flandrin, Paul Honeine, C&...
This paper presents a discriminative training (DT) approach to irrelevant variability normalization (IVN) based training of feature transforms and hidden Markov models for large v...
—In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where p...