A Study on Content-Based Classification and Retrieval of Audio Database
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
Ubiquitous Home: Real-Life Testbed for Home Context-Aware Service
TRIDENTCOM '05 Proceedings of the First International Conference on Testbeds and Research Infrastructures for the DEvelopment of NeTworks and COMmunities
Towards event detection in an audio-based sensor network
Proceedings of the third ACM international workshop on Video surveillance & sensor networks
Unsupervised content discovery in composite audio
Proceedings of the 13th annual ACM international conference on Multimedia
Extracting information from multimedia meeting collections
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
New direct approaches to robust sound source localization
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Interactive experience retrieval for a ubiquitous home
Proceedings of the 3rd ACM workshop on Continuous archival and retrival of personal experences
IEEE Transactions on Signal Processing
State of the art of smart homes
Engineering Applications of Artificial Intelligence
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We present a system for video retrieval based on analyzing audio data from a large number of microphones in a home-like environment. Silence elimination on individual microphones is followed by noise reduction based on regions consisting of multiple microphones, to identify audio segments. An algorithm based on the energy distribution of sounds in the house is used to localize sound sources, thereby removing sounds heard in regions other than they are generated. A set of time domain features are used to classify these sounds for video retrieval. The algorithms were evaluated with 200 minutes of audio data from each microphone, gathered during an experiment where a family lived in the ubiquitous home. It was possible to achieve an overall accuracy of above 80% from all algorithms.