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In the presence of strong noise or reverberation, the acoustic source localization and tracking problem is confronted with severe challenges. One of them is that the maximal peak of the localization function may not be generated by the real source. In this paper, the stochastic region contraction (SRC) is adopted to search for multiple peaks of the localization function rather than the maximal one...
Motivated by potential applications such as the use of multiple robots to collaboratively localize multiple objects/events of interest through audio cues, we propose a novel solution for blind source separation (BSS) and localization using multiple microphone arrays. Unlike the existing state-of-the-art where direction of arrivals (DOAs) and locations are estimated sequentially, the proposed approach...
In this paper, a new framework is proposed for autonomous universal surveillance based on video and audio data. ??Universal?? indicates no specification of targets of interest. Instead, regions of importance (ROIs) in a scene should be detected. Specifically, in the video domain, a frame-based main subject detection is proposed based on adaptive selection of low-level features. In the audio domain,...
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