Fast cortical keypoints for real-time object recognition

Terzic, Kasim; Rodrigues, J. M. F.; du Buf, J. M. H.

http://hdl.handle.net/10400.1/3375

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Autores

Terzic, Kasim

Rodrigues, J. M. F.

du Buf, J. M. H.

Resumo(s)

Best-performing object recognition algorithms employ a large number features extracted on a dense grid, so they are too slow for real-time and active vision. In this paper we present a fast cortical keypoint detector for extracting meaningful points from images. It is competitive with state-of-the-art detectors and particularly well-suited for tasks such as object recognition. We show that by using these points we can achieve state-of-the-art categorization results in a fraction of the time required by competing algorithms.

Palavras-chave

Computer vision Object recognition Image classification Gabor filters Real time systems

URI

http://hdl.handle.net/10400.1/3375

Citação

Terzic, Kasim; Rodrigues, J.M.F.; Buf, J. M. H.Fast cortical keypoints for real-time object recognition, Trabalho apresentado em IEEE Int. Conf. on Image Processing, In IEEE Int. Conf. on Image Processing, Melbourne, Australia, 2013.

Projetos de investigação

A neuro-dynamic framework for cognitive robotics: scene representations, behavioural sequences, and learning.

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Editora

IEEE

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