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On Building Immersive Audio Applications Using Robust ...
https://asp-eurasipjournals.springeropen.com/articles/10.1155/ASP/2006/40960#:~:text=A%20joint%20audio-video%20localization%20method%20needed%20in%20the,the%20acoustic%20field%20again%20at%20the%20receiving%20chamber.
Joint Audio-Video Signal Processing for Object ...
https://link.springer.com/chapter/10.1007%2F978-3-662-04619-7_10
This chapter presents a joint audio-video signal processing methodology for object localizing and tracking. The approach is based on a decentralized Kalman filter structure modified such that different sensor measurement models can be incorporated.
Joint audio-video object localization and tracking | IEEE ...
https://ieeexplore.ieee.org/document/911196
Abstract:There has been a tremendous amount of research on object localization either involving microphone arrays or video cameras. Considerable less attention has been paid, however, to object localization and tracking based on joint audio-video processing thus far. This may be related to the lack of suitable algorithms for object localization simultaneously using …
Ob ject Localization by Joint Audio-Video Signal Processing
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.142.132
In this paper we introduce a method for the estimation of object positions based on joint audio-video information. The key technique is a modified decentralized Kalman filter (MDKF), where the object localization problem is viewed as state estimation. First, the position of the object is estimated based on audio and video information separately.
Joint audio-video object localization and tracking: A ...
https://www.researchgate.net/publication/3321354_Joint_audio-video_object_localization_and_tracking_A_presentation_general_methodology
Before elaborating on joint audio-video processing, we review some previous work the areas of audio and video object localization. Then a recursive sensor …
Object Localization by Joint Audio-Video Signal Processing.
https://www.researchgate.net/publication/220839228_Object_Localization_by_Joint_Audio-Video_Signal_Processing
Joint Audio-Video Object Localization Using A Recursive Multi-State Multi-Sensor Estimator December 1999 · Acoustics, Speech, and Signal Processing, …
S.Spors, “Object localization by joint audio-video signal ...
https://citeseer.ist.psu.edu/showciting?cid=9143979
This paper presents a object localization and tracking algorithm integrating audio and video based object localization results. A face tracking algorithm and a microphone array are used to compute two single-modality speaker position estimates.
S.Spors, “Object localization by joint audio-video signal ...
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.643.9967
In this paper we introduce a method for the estimation of object positions based on joint audio-video information. The key tech-nique is a modied decentralized Kalman l-ter (MDKF), where the object localization problem is viewed as state estimation. First, the position of the object is estimated based on audio and video information separately.
Joint audio-video object localization and tracking - NASA/ADS
https://ui.adsabs.harvard.edu/abs/2001ISPM...18...22S/abstract
adshelp[at]cfa.harvard.edu The ADS is operated by the Smithsonian Astrophysical Observatory under NASA Cooperative Agreement NNX16AC86A
Localization, Detection and Tracking of Multiple Moving ...
https://www.arxiv-vanity.com/papers/1904.12769/
This paper investigates the joint localization, detection, and tracking of sound events using a convolutional recurrent neural network (CRNN). We use a CRNN previously proposed for the localization and detection of stationary sources, and show that the recurrent layers enable the spatial tracking of moving sources when trained with dynamic scenes. The tracking …
JointAudio-VisualTrackingUsingParticleFilters
https://asp-eurasipjournals.springeropen.com/track/pdf/10.1155/S1110865702206058.pdf
Joint Audio-Visual Tracking Using Particle Filters 1155 improvement (simple beamforming-based speech signal en-hancement for the speech recognition engine). We present a probabilistic framework for combining results from the two modes and develop a particle filter based joint audio-video tracking algorithm. The availability of independent modali-
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