IEEE Signal Processing Magazine · 2001 · 82 citations · 46 references
ComputingRobotics EngineeringComputer VisionMachine VisionSensor FusionKalman FilteringSensor Fusion For LocalizationSimultaneous LocalizationSound LocalizationAudio Signal ProcessingDecentralized Kalman FilteringKalman Filter FusionKalman Filter-based LocalizationMicrophone ArraysObject LocalizationSensor Fusion Localization
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 multimicrophone outputs and color image sequences. In this article, we propose a solution to this problem. Before elaborating on joint audio-video processing, we review some previous work the areas of audio and video object localization. Then a recursive sensor fusion method based on decentralized Kalman filtering is introduced. Unfortunately, the decentralized Kalman filter cannot be directly used for joint audio-video object localization due to specific properties of the audio sensor. By properly adjusting the local audio position estimator, however, we manage to keep the overall architecture. We stress the general methodology.
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