Similarity estimation techniques from rounding algorithms
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Proceedings of the international conference on Multimedia
Compact hashing with joint optimization of search accuracy and time
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
TouchPaper: an augmented reality application with cloud-based image recognition service
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
TouchPaper: making print interactive
Proceedings of the 20th ACM international conference on Multimedia
Mobile product image search by automatic query object extraction
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
When Amazon Meets Google: Product Visualization by Exploring Multiple Web Sources
ACM Transactions on Internet Technology (TOIT)
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The advent of smart phones has provided an excellent plat- form for mobile visual search. Most of previous mobile visual search systems adopt the framework of "bag of words",in which words indicate quantized codes of visual features. In this work, we propose a novel mobile visual search system based on "bag of hash bits". Using new ideas for hash bit selection, multi-hash table generation, and hamming-distance soft scoring, we overcome the problem of bit inefficiency affecting the traditional hashing approaches, and achieve promising accuracy outperforming state of the art. The framework is also general in that general feature type can be used for generating the hash bits. Demos and experiments over a large scale product image set demonstrate the effectiveness of our approach.