Title :
SFINX: a multisensor fusion and mining system
Author :
Z. Dimitrijevic;G. Wu;E.Y. Chang
fDate :
6/25/1905 12:00:00 AM
Abstract :
In a surveillance system, video signals are generated by multiple cameras with or without spatially and temporally overlapping coverage. These signals need to be transmitted, processed, fused, stored, indexed, and then summarized as semantic events to allow efficient and effective querying and mining. SfinX aims to build several core components for multisensor fusion and mining. This paper first depicts SfinX´ architecture and its core components, namely, data fusion, event detection, event characterization, event recognition, and storage. In particular, we survey representative methods and discuss plausible research directions for event recognition and storage.
Keywords :
"Cameras","Hidden Markov models","Video surveillance","Network servers","Event detection","Fuses","Video compression","Pattern recognition","Training data","Fusion power generation"
Conference_Titel :
Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Conference of the Fourth International Conference on
Print_ISBN :
0-7803-8185-8
DOI :
10.1109/ICICS.2003.1292636