Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Image Based Localization in Urban Environments
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Proceedings of the 18th international conference on World wide web
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Avoiding confusing features in place recognition
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Handling urban location recognition as a 2D homothetic problem
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Active query sensing for mobile location search
MM '11 Proceedings of the 19th ACM international conference on Multimedia
City-scale landmark identification on mobile devices
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Mobile product search with Bag of Hash Bits and boundary reranking
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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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 a scalable visual search system implemented over a NYC street view dataset (0.3 million images), we show a performance gain by reducing the failure rate of mobile location search to only 12% after the second query. We have also implemented an end-to-end functional system, including user interfaces on iPhones, client-server communication, and a remote search server. This work may open up an exciting new direction for developing interactive mobile media applications through the innovative exploitation of active sensing and query formulation.