Active Sequential Hypothesis Testing with Application to a Visual Search Problem

Vaidhiyan, Nidhin Koshy and Arun, SP and Sundaresan, Rajesh (2012) Active Sequential Hypothesis Testing with Application to a Visual Search Problem. In: IEEE International Symposium on Information Theory , JUL 01-06, 2012 , Cambridge, MA.

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Abstract

We consider a visual search problem studied by Sripati and Olson where the objective is to identify an oddball image embedded among multiple distractor images as quickly as possible. We model this visual search task as an active sequential hypothesis testing problem (ASHT problem). Chernoff in 1959 proposed a policy in which the expected delay to decision is asymptotically optimal. The asymptotics is under vanishing error probabilities. We first prove a stronger property on the moments of the delay until a decision, under the same asymptotics. Applying the result to the visual search problem, we then propose a ``neuronal metric'' on the measured neuronal responses that captures the discriminability between images. From empirical study we obtain a remarkable correlation (r = 0.90) between the proposed neuronal metric and speed of discrimination between the images. Although this correlation is lower than with the L-1 metric used by Sripati and Olson, this metric has the advantage of being firmly grounded in formal decision theory.

Item Type:	Conference Paper
Series.:	IEEE International Symposium on Information Theory
Publisher:	IEEE
Additional Information:	Copy right for this article belongs to IEEE, NEW YORK, USA
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering > Electrical Communication Engineering - Technical Reports
Date Deposited:	07 Feb 2013 09:20
Last Modified:	07 Feb 2013 09:20
URI:	http://eprints.iisc.ac.in/id/eprint/45757

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