Please use this identifier to cite or link to this item: https://doi.org/10.1109/TMM.2006.879875
Title: Experiential sampling on multiple data streams
Authors: Kankanhalli, M.S. 
Wang, J.
Jain, R.
Keywords: Dynamical systems
Experiential computing
Experiential sampling
Sampling
Visual attention
Issue Date: 2006
Source: Kankanhalli, M.S., Wang, J., Jain, R. (2006). Experiential sampling on multiple data streams. IEEE Transactions on Multimedia 8 (5) : 947-955. ScholarBank@NUS Repository. https://doi.org/10.1109/TMM.2006.879875
Abstract: Multimedia systems must deal with multiple data streams. Each data stream usually contains significant volume of redundant noisy data. In many real-time applications, it is essential to focus the computing resources on a relevant subset of data streams at any given time instant and use it to build the model of the environment. We formulate this problem as an experiential sampling problem and propose an approach to utilize computing resources efficiently on the most informative subset of data streams. In this paper, we generalize our experiential sampling framework to multiple data streams and provide an evaluation measure for this technique. We have successfully applied this framework to the problems of traffic monitoring, face detection and monologue detection. © 2006 IEEE.
Source Title: IEEE Transactions on Multimedia
URI: http://scholarbank.nus.edu.sg/handle/10635/39296
ISSN: 15209210
DOI: 10.1109/TMM.2006.879875
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