Object-based visual query suggestion

Hamzaoui, Amel; Letessier, Pierre; Joly, Alexis; Buisson, Olivier; Boujemaa, Nozha

doi:10.1007/s11042-012-1340-5

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Cited by 3 publications

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“…We proposed in [3] to solve these user perception issues by a new visual query suggestion paradigm. Rather than letting the user select any region of interest, the system will suggest only visual query regions that actually contain relevant matches in the dataset.…”

Section: Proposed Approachmentioning

confidence: 99%

Small objects query suggestion in a large web-image collection

Letessier

Hervé

Champ

et al. 2013

Proceedings of the 21st ACM International Conference on Multimedia

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International audienceState-of-the-art visual search methods allow retrieving efficiently small rigid objects in very large image datasets (e.g. logos, paintings, etc.). User's perception of the classical query-by-window paradigm is however affected by the fact that many submitted queries actually return nothing or only junk results. We demonstrate in this demo that the perception can be radically different if the objects of interest are rather suggested to the user by pre-computing relevant clusters of instances. Impressive results involving very small objects discovered in a web collection of 110K images are demonstrated through a simple interactive GUI

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Section: Proposed Approachmentioning

confidence: 99%