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Mobile product recognition

Published: 25 October 2010 Publication History

Abstract

We present a mobile product recognition system for the camera-phone. By snapping a picture of a product with a camera-phone, the user can retrieve online information of the product. The product is recognized by an image-based retrieval system located on a remote server. Our database currently comprises more than one million entries, primarily products packaged in rigid boxes with printed labels, such as CDs, DVDs, and books. We extract low bit-rate descriptors from the query image and compress the location of the descriptors using location histogram coding on the camera-phone. We transmit the compressed query features, instead of a query image, to reduce the transmission delay. We use inverted index compression and fast geometric re-ranking on our database to provide a low delay image recognition response for large scale databases. Experimental timing results on different parts of the mobile product recognition system is reported in this work.

References

[1]
Google goggles. http://www.google.com/mobile/goggles/.
[2]
Kooaba. http://www.kooaba.com.
[3]
Snaptell. http://www.snaptell.com.
[4]
H. Bay, T. Tuytelaars, and L. V. Gool. SURF: speeded up robust features. In European Conference on Computer Vision, pages 404--417, Graz, Austria, May 2006.
[5]
V. Chandrasekhar, G. Takacs, D. Chen, S. S. Tsai, R. Grzeszczuk, and B. Girod. CHoG: Compressed Histogram of Gradients. In Conference on Computer Vision and Pattern Recognition, 2009.
[6]
V. Chandrasekhar, G. Takacs, D. Chen, S. S. Tsai, J. Singh, and B. Girod. Transform coding of feature descriptors. In SPIE Visual Communications and Image Processing, San Jose, CA, USA, January 2009.
[7]
V. Chandrasekhar, G. Takacs, D. M. Chen, S. S. Tsai, Y. Reznik, R. Grzeszczuk, and B. Girod. Quantization schemes for CHoG. In International Workshop on Mobile Vision, 2010.
[8]
D. M. Chen, S. S. Tsai, V. Chandrasekhar, G. Takacs, R. Vedantham, R. Grzeszczuk, and B. Girod. Inverted index compression for scalable image matching. In Data Compression Conference, Snowbird, UT, USA, 2010.
[9]
D. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91--110, November 2004.
[10]
K. Mikolajczyk and C. Schmid. Scale and ane invariant interest point detectors. International Journal of Computer Vision, 60(1):63--86, October 2004.
[11]
D. Nister and H. Stewenius. Scalable recognition with a vocabulary tree. In Conference on Computer Vision and Pattern Recognition, pages 2161--2168, New York, NY, USA, June 2006.
[12]
S. S. Tsai, D. Chen, J. Singh, and B. Girod. Rate-efficient, real-time CD cover recognition on a camera-phone. In ACM International Conference on Multimedia, Vancouver, Canada, October 2008.
[13]
S. S. Tsai, D. M. Chen, G. Takacs, V. Chandrasekhar, R. Vedantham, R. Grzeszczuk, and B. Girod. Location coding for mobile image retrieval. In Proc. 5th International Mobile Multimedia Communications Conference, 2009.
[14]
S. S. Tsai, D. M. Chen, G. Takacs, V. Chandrasekhar, R. Vedantham, R. Grzeszczuk, and B. Girod. Fast geometric re-ranking for image-based retrieval. In International Conference on Image Processing, 2010.

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  • (2023)A Qualitative and Quantitative Analysis of Research in Mobility Technologies for Visually Impaired PeopleIEEE Access10.1109/ACCESS.2023.329107411(82496-82520)Online publication date: 2023
  • (2022)A Deep Learning Framework for Grocery Product Detection and RecognitionFood Analytical Methods10.1007/s12161-022-02384-215:12(3498-3522)Online publication date: 13-Aug-2022
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cover image ACM Conferences
MM '10: Proceedings of the 18th ACM international conference on Multimedia
October 2010
1836 pages
ISBN:9781605589336
DOI:10.1145/1873951
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 25 October 2010

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Author Tags

  1. content-based image retrieval
  2. mobile visual search

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  • Demonstration

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MM '10
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MM '10: ACM Multimedia Conference
October 25 - 29, 2010
Firenze, Italy

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

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  • (2023)Real-Time Supermarket Product Recognition on Mobile Devices Using Scalable Pipelines2023 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP49359.2023.10223137(420-424)Online publication date: 8-Oct-2023
  • (2023)A Qualitative and Quantitative Analysis of Research in Mobility Technologies for Visually Impaired PeopleIEEE Access10.1109/ACCESS.2023.329107411(82496-82520)Online publication date: 2023
  • (2022)A Deep Learning Framework for Grocery Product Detection and RecognitionFood Analytical Methods10.1007/s12161-022-02384-215:12(3498-3522)Online publication date: 13-Aug-2022
  • (2021)Content Based Image and Video Retrieval A Compressive ReviewInternational Journal of Engineering and Advanced Technology10.35940/ijeat.E2783.061052110:5(243-247)Online publication date: 30-Jun-2021
  • (2020)Augmenting Public Bookcases to Support Book Sharing22nd International Conference on Human-Computer Interaction with Mobile Devices and Services10.1145/3379503.3403542(1-11)Online publication date: 5-Oct-2020
  • (2020)Automatic Product Region Extraction based on analysis of Images Uploaded to C2C Online MarketJournal of Organizational Computing and Electronic Commerce10.1080/10919392.2020.178835930:4(323-334)Online publication date: 13-Jul-2020
  • (2020)Video Retrieval Using Query Images and CNN FeaturesAdvances in Smart Technologies Applications and Case Studies10.1007/978-3-030-53187-4_13(112-120)Online publication date: 4-Aug-2020
  • (2020)Text Detection Using Maximally Stable External Regions and Stroke Width Variation4th International Conference on Internet of Things and Connected Technologies (ICIoTCT), 201910.1007/978-3-030-39875-0_38(358-365)Online publication date: 15-Feb-2020
  • (2019)Visual Arts Search on Mobile DevicesACM Transactions on Multimedia Computing, Communications, and Applications10.1145/332633615:2s(1-23)Online publication date: 3-Jul-2019
  • (2019)Segmentation based Non-learning Product Detection for Product Recognition on Store Shelves2019 Nicograph International (NicoInt)10.1109/NICOInt.2019.00009(9-16)Online publication date: Jul-2019
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