TY - GEN
T1 - Joint localization and fingerprinting of sound sources for auditory scene analysis
AU - Kaghaz-Garan, Scott
AU - Umbarkar, Anurag
AU - Doboli, Alex
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/11
Y1 - 2014/11/11
N2 - In the field of scene understanding, researchers have mainly focused on using video/images to extract different elements in a scene. The computational as well as monetary cost associated with such implementations is high. This paper proposes a low-cost system which uses sound-based techniques in order to jointly perform localization as well as fingerprinting of the sound sources. A network of embedded nodes is used to sense the sound inputs. Phase-based sound localization and Support-Vector Machine classification are used to locate and classify elements of the scene, respectively. The fusion of all this data presents a complete "picture" of the scene. The proposed concepts are applied to a vehicular-traffic case study. Experiments show that the system has a fingerprinting accuracy of up to 97.5%, localization error less than 4 degrees and scene prediction accuracy of 100%.
AB - In the field of scene understanding, researchers have mainly focused on using video/images to extract different elements in a scene. The computational as well as monetary cost associated with such implementations is high. This paper proposes a low-cost system which uses sound-based techniques in order to jointly perform localization as well as fingerprinting of the sound sources. A network of embedded nodes is used to sense the sound inputs. Phase-based sound localization and Support-Vector Machine classification are used to locate and classify elements of the scene, respectively. The fusion of all this data presents a complete "picture" of the scene. The proposed concepts are applied to a vehicular-traffic case study. Experiments show that the system has a fingerprinting accuracy of up to 97.5%, localization error less than 4 degrees and scene prediction accuracy of 100%.
UR - https://www.scopus.com/pages/publications/84915754776
U2 - 10.1109/ROSE.2014.6952982
DO - 10.1109/ROSE.2014.6952982
M3 - Conference contribution
AN - SCOPUS:84915754776
T3 - ROSE 2014 - 2014 IEEE International Symposium on RObotic and SEnsors Environments, Proceedings
SP - 49
EP - 54
BT - ROSE 2014 - 2014 IEEE International Symposium on RObotic and SEnsors Environments, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 12th IEEE International Symposium on Robotic and Sensors Environments, ROSE 2014
Y2 - 16 October 2014 through 18 October 2014
ER -