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What and Who
Title:Prediction of search targets from fixations in open-world settings
Speaker:Hosnieh Sattar
coming from:International Max Planck Research School for Computer Science - IMPRS
Speakers Bio:
Event Type:IMPRS Research Seminar
Visibility:D1, D2, D3, D4, D5, SWS, RG1, MMCI
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Level:Public Audience
Date, Time and Location
Date:Monday, 23 November 2015
Duration:45 Minutes
Building:E1 4
Previous work on predicting the target of visual search from human
fixations only considered closed-world settings in which training labels
are available and predictions are performed for a known set of potential
targets. In this work we go beyond the state of the art by studying search
target prediction in an open-world setting in which we no longer assume
that we have fixation data to train for the search targets. We present a
dataset containing fixation data of 18 users searching for natural images
from three image categories within synthesised image collages of about 80
images. In a closed-world baseline experiment we show that we can predict
the correct target image out of a candidate set of five images. We then
present a new problem formulation for search target prediction in the
open-world setting that is based on learning compatibilities between
fixations and potential targets.

Name(s):Andrea Ruffing
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Created:Andrea Ruffing/MPI-INF, 11/18/2015 11:16 AM Last modified:Uwe Brahm/MPII/DE, 11/24/2016 04:13 PM
  • Andrea Ruffing, 11/18/2015 11:55 AM -- Created document.