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Selective Search for Object Recognition

Int J Comput VisDOI Search for Object RecognitionJ. R. R. Uijlings K. E. A. van de Sande T. Gevers A. W. M. SmeuldersReceived: 5 May 2012 / Accepted: 11 March 2013 Springer Science+Business Media New York 2013 AbstractThis paper addresses the problem of generatingpossible Object locations for use in Object Recognition . Weintroduce Selective Search which combines the strength ofboth an exhaustive Search and segmentation. Like segmen-tation, we use the image structure to guide our samplingprocess. Like exhaustive Search , we aim to capture all possi-ble Object locations. Instead of a single technique to generatepossible Object locations, we diversify our Search and use avariety of complementary image partitionings to deal withas many image conditions as possible.

Hence without prior recognition it is hard to decide that a face and a sweater are part of one object ( Tu et al. 2005). This has led to the opposite of the traditional approach: to do localisation through the identification of an object. This recent approach in object recognition has made enor-mousprogressinlessthanadecade(DalalandTriggs2005;

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