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The cognitive goal of this paper is to assess whether marker-less motion capture systems provide sufficient data to recognize human postures in the side view. The research goal is to develop a new posture classification method that allows for analysing human activities using data recorded by RGB‐D sensors. The method is insensitive to recorded activity duration and gives satisfactory results for the...
Rozpoznawanie postur jest potrzebne do analizy czynności wykonywanych przez człowieka, syntezy ruchu robotów humanoidalnych oraz w badaniach nad robotami współpracującymi. Popularne w ostatnich latach tanie, bezprzewodowe czujniki wizyjne RGB-D umożliwiające łatwa˛ rejestracje˛ ruchu człowieka, ułatwiają˛ realizacje˛ tego zadania badawczego. Powszechnie stosowane są, tu konwencjonalne klasyfikatory,...
Despite the growing popularity of machine learning technology, vision‐based action recognition/forecasting systems are seen as black‐boxes by the user. The effecti‐ veness of such systems depends on the machine learning algorithms, it is difficult (or impossible) to explain the de‐ cisions making processes to the users. In this context, an approach that offers the user understanding of these re‐ asoning...
Anticipating human intentional actions is essential for many applications involving service robots and social robots. Nowadays assisting robots must do reasoning beyond the present with predicting future actions. It is difficult due to its non-Markovian property and the rich contextual information. This task requires the subtle details inherent in human movements that may imply a future action. This...
Nowadays in human-robot interactions, robots must do reasoning beyond the present with predicting the future actions. This task requires the subtle details inherent in human movements that may imply a future action. In this paper, we employ a probabilistic method for action prediction in human-object interactions. The key idea of our approach is the description of the so-called object affordance,...
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