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Kinsight: Localizing and Tracking Household Objects Using Depth-Camera Sensors.
- Source :
- 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems; 1/ 1/2012, p67-74, 8p
- Publication Year :
- 2012
-
Abstract
- We solve the problem of localizing and tracking household objects using a depth-camera sensor network. We design and implement Kin sight that tracks household objects indirectly -- by tracking human figures, and detecting and recognizing objects from human-object interactions. We devise two novel algorithms: (1) Depth Sweep -- that uses depth information to efficiently extract objects from an image, and (2) Context Oriented Object Recognition -- that uses location history and activity context along with an RGB image to recognize object sat home. We thoroughly evaluate Kinsight's performance with a rich set of controlled experiments. We also deploy Kinsightin real-world scenarios and show that it achieves an average localization error of about 13 cm. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISBNs :
- 9781467316934
- Database :
- Complementary Index
- Journal :
- 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems
- Publication Type :
- Conference
- Accession number :
- 86545265
- Full Text :
- https://doi.org/10.1109/DCOSS.2012.27