Transcription of Selective Search for Object Recognition
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Selective Search for Object Recognition
Selective Search for Object Uijlings 1,2, van de Sande 2, T. Gevers2, and Smeulders21 University of Trento, Italy2 University of Amsterdam, the NetherlandsTechnical Report 2012, submitted to IJCVA bstractThis paper addresses the problem of generating possible Object lo-cations for use in Object Recognition . We introduce Selective Searchwhich combines the strength of both an exhaustive Search andseg-mentation. Like segmentation, we use the image structure toguideour sampling process. Like exhaustive Search , we aim to captureall possible Object locations. Instead of a single technique to gen-erate possible Object locations, wediversifyour Search and use avariety of complementary image partitionings to deal with as manyimage conditions as possible. Our Selective Search resultsin asmall set of data-driven, class-independent, high qualitylocations,yielding 99% recall and a Mean Average Best Overlap of at10,097 locations.
Selective Search for Object Recognition J.R.R. Uijlings∗1,2, K.E.A. van de Sande†2, T. Gevers2, and A.W.M. Smeulders2 1University of Trento, Italy 2University of Amsterdam, the Netherlands Technical Report 2012, submitted to IJCV Abstract This paper addresses the problem of generating possible object …
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