[CPCC] TALK: Application-Specific Compression [June 2 1:30 PM]

Ender Ayanoglu ayanoglu at uci.edu
Fri May 28 15:55:50 PDT 2004


	           APPLICATION-SPECIFIC COMPRESSION FOR
		CLASSIFICATION, RECOGNITION AND LOCALIZATION

		 		June 2, 2004
				 Wednesday
				  1:30 PM
				   ET 331

				     by

                          Prof. Antonio Ortega
                    Dept. of Electrical Engineering
                   University of Southern California
                       http://sipi.usc.edu/~ortega

Abstract:

Most of the work to date on signal compression, both practical and
theoretical, has focused on coding signals based on fidelity
criteria. The underlying assumption is that signals are compressed so
as to be stored or transmitted, and ultimately rendered.

Ubiquitous wired or wireless access to networks and the decreasing
cost of signal acquisition equipment (e.g., video cameras), make it
likely that distributed signal processing system will become popular
(consider for example, sensor networks, distributed multimedia
databases, etc).

Many of these distributed systems will be such that signal processing
and acquisition are not co-located, so signal data needs to be
transfered, preferably in compressed format. A common characteristic
in these scenarios is that signals to be compressed will not be stored
or displayed in their entirety; instead, decoded signals will be
processed, and then discarded. Thus, the main objective of encoding
algorithms used in this context should be to use as few bits as
possible, without altering the outcome of the processing, as compared
to processing performed on the original (non-compressed) data.

In this talk we present several examples of our recent work into
application-specific compression, where non-standard criteria are used
to optimize the compression performance. In particular we provide
examples in distributed speech recognition, distributed image
acquisition for a centralized database storage and distributed
acoustic source localization.

Work done in collaboration with Urbashi Mitra, Shrikanth Narayanan,
Naveen Srinivasamurthy, Lavanya Vasudevan and Hua Xie, all at USC.

Speaker's biography:

Antonio Ortega is an Associate Professor in the Electrical Engineering
department at the University of Southern California.  He received the
Telecommunications Engineering degree from the Universidad Politecnica
de Madrid (UPM), Madrid, Spain in 1989 and the Ph.D. in Electrical
Engineering from Columbia University, New York, NY in 1994.  He has
been a recipient of the NSF Career award, of the 1997 IEEE
Communications Society Leonard G. Abraham Prize Paper Award (joint
work with C.-Y. Hsu and A. R.  Reibman) and of the IEEE Signal
Processing Society 1999 Magazine Award (joint work with K.
Ramchandran.)  He is a senior member of IEEE, has been an associate
editor for the IEEE Transactions on Image Processing and the IEEE
Signal Processing Letters; he currently chairs the IEEE Signal Processing
Society Image and Multidimensional Signal Processing Technical Committee.


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