Visual location search using symmelets

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.