Transcription of Selective Search for Object Recognition
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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.
ing and recognizing objects based on their parts. They first generate a set of part hypotheses using a grouping method based on Arbeláez et al. (2011). Each part hypothesis is described by both appearance and shape features. Then, an object is recognized and carefully delineated by using its parts, achieving good results for shape recognition ...
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