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Proceedings Paper

Scene recognition with audio-visual sensor fusion
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Paper Abstract

Several surveillance applications are characterized by the ability to gather information about the scene from more than one sensor modality, and heterogeneous sensor data must then be fused by the decision-maker. In this paper, we discuss the issues relevant to developing a model for fusion of information from audio and visual sensors, and present a framework to enhance decision-making capabilities. In particular, our methodology focuses on the issues of temporal reasoning, uncertainty representations, and coupling between features inferred from data streams coming from different sensors. We propose a conditional probability-based representation for uncertainty, along with fuzzy rules to assist decision-making, and a matrix representation of the coupling between sensor data streams. We also develop a fusion algorithm that utilizes these representations.

Paper Details

Date Published: 28 March 2005
PDF: 10 pages
Proc. SPIE 5813, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005, (28 March 2005); doi: 10.1117/12.605751
Show Author Affiliations
Deepak Devicharan, Syracuse Univ. (United States)
Kishan G. Mehrotra, Syracuse Univ. (United States)
Chilukuri Krishna Mohan, Syracuse Univ. (United States)
Pramod K. Varshney, Syracuse Univ. (United States)
Long Zuo, Syracuse Univ. (United States)

Published in SPIE Proceedings Vol. 5813:
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005
Belur V. Dasarathy, Editor(s)

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