Visual location search using symmelets

Chong Po Liao, Jun-Wei Hsieh, Hui Fen Chiang, Yun Tsao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


SURF is a robust and useful feature detector to various vision-based applications but lacks of the ability to detect symmetric objects. This paper proposes a new symmetrical SURF descriptor to detect all possible symmetric pairs via a mirroring transformation. With this symmetrical descriptor, a novel feature named 'symmelet' is introduced and used in scene representation and effective mobile visual location search. A symmelet is a symmetrical pair formed by a SURF point and its symmetrical one. Three advantages can be gained from this symmelet-absed representation. Firstly, because the set of symmelets is small, a scene can be represented more compactly and searched more efficiently. Secondly, its symmetrical property can compare image/scene contents more accurately. Thirdly, the geometric structure of a scene can be easily constructed and verified and thus filter out many false matches. Then, given a query image captured by a mobile phone, the descried location can be very efficiently and accurately retrieved even though this phone is with quite limited computational power.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Number of pages5
ISBN (Electronic)9781467399616
StatePublished - 3 Aug 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: 25 Sep 201628 Sep 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


Conference23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States


  • Positioning
  • Symmelet
  • Symmetrical SURF

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