A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
Many algorithms extract terms from text together with some kind of taxonomic classification (is-a) link. However, the general approaches used today, and specifically the methods o...
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...
In this paper, we propose a new integration approach for simulation and behaviour in the learning context that is able to coherently manage the shared virtual environment for the ...