Path: utzoo!attcan!utgpu!jarvis.csri.toronto.edu!cs.utexas.edu!usc!ucsd!ucbvax!techunix.BITNET!dario
From: dario@techunix.BITNET (Dario Ringach)
Newsgroups: comp.ai.neural-nets
Subject: Contrast sensitivity of spatiotemporal models models
Keywords: spatiotemporal filtering, motion detection
Message-ID: <8977@discus.technion.ac.il>
Date: 8 Dec 89 10:11:19 GMT
Sender: daemon@ucbvax.BERKELEY.EDU
Reply-To: dario%techunix.bitnet@jade.berkeley.edu (Dario Ringach)
Organization: Technion, Israel Inst. Tech., Haifa Israel
Lines: 11

Almost all suggested motion detectors based on spatiotemporal energy
measurements are sensitive to the contrast of the stimulus, so that
they do not encode velocity information *directly*.  Assuming that
division is NOT a biological plausible operation, how can this problem
be solved by means of a simple, biological plausible, neural network?
Gradient methods suffer form the same problem in that division is needed
to get rid of contrast dependency...  Thanks in advance for any help!
--
BITNET: dario@techunix  |  Domain: dario@techunix.technion.ac.il
Dario Ringach, Technion, Israel Institute of Technology,
Dept. of Electrical Engineering, Box 52, 32000 Haifa, Israel