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Selective Search for Object Recognition

Uijlings, J. R. R. ; van de Sande, K. E. A. ; Gevers, T. ; Smeulders, A. W. M.

International journal of computer vision, 2013-09, Vol.104 (2), p.154-171 [Periódico revisado por pares]

Boston: Springer US

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Título:
Selective Search for Object Recognition
Autor: Uijlings, J. R. R. ; van de Sande, K. E. A. ; Gevers, T. ; Smeulders, A. W. M.
Assuntos: Applied sciences ; Artificial Intelligence ; Computer Imaging ; Computer programs ; Computer Science ; Computer science; control theory; systems ; Datasets ; Exact sciences and technology ; Image Processing and Computer Vision ; Image processing systems ; Information management ; Localization ; Object recognition ; Pattern Recognition ; Pattern Recognition and Graphics ; Pattern recognition. Digital image processing. Computational geometry ; Recall ; Sampling ; Search engines ; Searching ; Segmentation ; Software ; Studies ; Vision
É parte de: International journal of computer vision, 2013-09, Vol.104 (2), p.154-171
Notas: ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
Descrição: This paper addresses the problem of generating possible object locations for use in object recognition. We introduce selective search which combines the strength of both an exhaustive search and segmentation. Like segmentation, we use the image structure to guide our sampling process. Like exhaustive search, we aim to capture all possible object locations. Instead of a single technique to generate possible object locations, we diversify our search and use a variety of complementary image partitionings to deal with as many image conditions as possible. Our selective search results in a small set of data-driven, class-independent, high quality locations, yielding 99 % recall and a Mean Average Best Overlap of 0.879 at 10,097 locations. The reduced number of locations compared to an exhaustive search enables the use of stronger machine learning techniques and stronger appearance models for object recognition. In this paper we show that our selective search enables the use of the powerful Bag-of-Words model for recognition. The selective search software is made publicly available (Software: http://disi.unitn.it/~uijlings/SelectiveSearch.html ).
Editor: Boston: Springer US
Idioma: Inglês

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Selective Search for Object Recognition

Uijlings, J. R. R. ; van de Sande, K. E. A. ; Gevers, T. ; Smeulders, A. W. M.

Boston: Springer US

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