In this paper the Authors present a novel approach to sound mixing. It is materialized in a system that enables to mix sound with hand gestures recognized in a video stream. The system has been developed in such a way that mixing operations can be performed both with or without visual support. To check the hypothesis that the mixing process needs only an auditory display, the influence of audio information visualization on sound...

The main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...

Głównym celem rozprawy było opracowanie systemu miksowania dźwięku za pomocą gestów rąk wykonywanych w powietrzu oraz zbadanie możliwości oferowanych przez takie rozwiązanie w porównaniu ze współczesną metodą miksowania sygnałów fonicznych, wykorzystującą środowisko komputera. Opracowany system rozpoznaje zarówno dynamiczne jak i statyczne gesty rąk. Rozpoznawanie gestów dynamicznych zrealizowano w oparciu o metody logiki rozmytej...

With a digital audio workstation, in contrast to the traditional mouse-keyboard computer interface, hand gestures can be used to mix audio with eyes closed. Mixing with a visual representation of audio parameters during experiments led to broadening the panorama and a more intensive use of shelving equalizers. Listening tests proved that the use of hand gestures produces mixes that are aesthetically as good as those obtained using...