Audio-driven Nonlinear Video Diffusion
In this paper we present a novel nonlinear video diffusion approach based on the fusion of information in audio and video channels. Both modalities are efficiently combined into a diffusion coefficient that integrates the basic assumption in this domain, i.e. related events in audio and video channels occur approximately at the same time. The proposed diffusion coefficient depends thus on an estimate of the synchrony between sounds and video motion. As a result, information in video parts whose motion is not coherent with the soundtrack is reduced and the sound sources are automatically highlighted. Several tests on challenging real-world sequences presenting important auditive and/or visual distractors demonstrate that our approach is able to prevail regions which are related to the soundtrack. In addition, we propose an application to the extraction of audio-related video regions by unsupervised segmentation in order to illustrate the capabilities of our method. To the best of our knowledge, this is the first nonlinear video diffusion approach which integrates information from the audio modality.