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MM11:AQSLong

Felix X. Yu, Rongrong Ji, Shih-Fu Chang. Active Query Sensing for mobile location search. In Proceeding of ACM International Conference on Multimedia (ACM MM), full paper, 2011.

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Abstract

While much exciting progress is being made in mobile visual search, one important question has been left unexplored in all current systems. When the .rst query fails to .nd the right target (up to 50% likelihood), how should the user form his/her search strategy in the subsequent interaction? In this paper, we propose a novel Active Query Sensing system to suggest the best way for sensing the surrounding scenes while forming the second query for location search. We accomplish the goal by developing several unique components an o.ine process for analyzing the saliency of the views associated with each geographical location based on score distribution modeling, predicting the visual search precision of individual views and locations, estimating the view of an unseen query, and suggesting the best subsequent view change. Using a scalable visual search system implemented over a NYC street view data set (0.3 million images), we show a performance gain as high as two folds, reducing the failure rate of mobile location search to only 12% after the second query. This work may open up an exciting new direction for developing interactive mobile media applications through innovative exploitation of active sensing and query formulation

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FelixX. Yu
Rongrong Ji
Shih-Fu Chang

BibTex Reference

@InProceedings{MM11:AQSLong,
   Author = {Yu, Felix X. and Ji, Rongrong and Chang, Shih-Fu},
   Title = {Active Query Sensing for mobile location search},
   BookTitle = {Proceeding of ACM International Conference on Multimedia (ACM MM), full paper},
   Year = {2011}
}

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