Benjamin Venditti

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Existing interaction techniques for mobile AR often use the multi-touch capabilities of the device's display for object selection and manipulation. To provide full 3D manipulation by touch in an integral way, existing approaches use complex multi finger and hand gestures. However, they are difficult or impossible to use in one-handed handheld AR scenarios(More)
In this paper, we propose an efficient noise power and noise cross-power spectral density estimation method for distributed microphones. The proposal can be combined with coherence based two-microphone noise reduction systems. It utilizes a minimum statistic based noise PSD estimator for each channel and a joint voice activity detector. Evaluation results(More)
This paper proposes a frequency domain diversity approach for two or more microphone signals, for example, for in-car applications. The microphones should be positioned separately to insure diverse signal conditions and incoherent recording of noise. This enables a better compromise for the microphone position with respect to different speaker sizes and(More)
In telecommunications, diversity combining for multiple receiving antennas is a commonly used technique to achieve robustness for fading channels. This paper proposes a frequency domain diversity approach for two or more microphone signals, e.g. for in-car applications. The microphones should be positioned separately to insure diverse signal conditions.(More)
One of the primary tasks in a dense mobile augmented reality (AR) environment is to ensure precise selection of an object, even if it is occluded or highly similar to surrounding virtual scene objects. Existing interaction techniques for mobile AR usually use the multi-touch capabilities of the device for object selection. However, single touch input is(More)
Distributed microphone arrays enable a better compromise for the microphone position with respect to different speaker sizes. They also ensure robust noise reduction with respect to different noise sources. This paper proposes a frequency domain LMS (FLMS) based algorithm to combine the signals of two microphones. It is shown that noise correlation leads to(More)
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