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Active query sensing: Suggesting the best query view for mobile visual search

Active query sensing: Suggesting the best query view for mobile visual search Active Query Sensing: Suggesting the Best Query View for Mobile Visual Search RONGRONG JI, FELIX X. YU, TONGTAO ZHANG, and SHIH-FU CHANG, Columbia University While much exciting progress is being made in mobile visual search, one important question has been left unexplored in all current systems. When searching objects or scenes in the 3D world, which viewing angle is more likely to be successful? More particularly, if the first query fails to find the right target, how should the user control the mobile camera to form the second query? In this article, we propose a novel Active Query Sensing system for mobile location search, which actively suggests the best subsequent query view to recognize the physical location in the mobile environment. The proposed system includes two unique components: (1) an offline process for analyzing the saliencies of different views associated with each geographical location, which predicts the location search precisions of individual views by modeling their self-retrieval score distributions. (2) an online process for estimating the view of an unseen query, and suggesting the best subsequent view change. Specifically, the optimal viewing angle change for the next query can be formulated as an online information theoretic approach. Using http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) Association for Computing Machinery

Active query sensing: Suggesting the best query view for mobile visual search

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2012 by ACM Inc.
ISSN
1551-6857
DOI
10.1145/2348816.2348819
Publisher site
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Abstract

Active Query Sensing: Suggesting the Best Query View for Mobile Visual Search RONGRONG JI, FELIX X. YU, TONGTAO ZHANG, and SHIH-FU CHANG, Columbia University While much exciting progress is being made in mobile visual search, one important question has been left unexplored in all current systems. When searching objects or scenes in the 3D world, which viewing angle is more likely to be successful? More particularly, if the first query fails to find the right target, how should the user control the mobile camera to form the second query? In this article, we propose a novel Active Query Sensing system for mobile location search, which actively suggests the best subsequent query view to recognize the physical location in the mobile environment. The proposed system includes two unique components: (1) an offline process for analyzing the saliencies of different views associated with each geographical location, which predicts the location search precisions of individual views by modeling their self-retrieval score distributions. (2) an online process for estimating the view of an unseen query, and suggesting the best subsequent view change. Specifically, the optimal viewing angle change for the next query can be formulated as an online information theoretic approach. Using

Journal

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) – Association for Computing Machinery

Published: Sep 1, 2012

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