14
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Visual simultaneous localization and mapping: a survey

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Related collections

          Most cited references104

          • Record: found
          • Abstract: not found
          • Conference Proceedings: not found

          A Combined Corner and Edge Detector

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Performance evaluation of local descriptors.

            In this paper, we compare the performance of descriptors computed for local interest regions, as, for example, extracted by the Harris-Affine detector. Many different descriptors have been proposed in the literature. It is unclear which descriptors are more appropriate and how their performance depends on the interest region detector. The descriptors should be distinctive and at the same time robust to changes in viewing conditions as well as to errors of the detector. Our evaluation uses as criterion recall with respect to precision and is carried out for different image transformations. We compare shape context, steerable filters, PCA-SIFT, differential invariants, spin images, SIFT, complex filters, moment invariants, and cross-correlation for different types of interest regions. We also propose an extension of the SIFT descriptor and show that it outperforms the original method. Furthermore, we observe that the ranking of the descriptors is mostly independent of the interest region detector and that the SIFT-based descriptors perform best. Moments and steerable filters show the best performance among the low dimensional descriptors.
              Bookmark
              • Record: found
              • Abstract: not found
              • Conference Proceedings: not found

              Video Google: a text retrieval approach to object matching in videos

                Bookmark

                Author and article information

                Journal
                Artificial Intelligence Review
                Artif Intell Rev
                Springer Nature
                0269-2821
                1573-7462
                January 2015
                November 2012
                : 43
                : 1
                : 55-81
                Article
                10.1007/s10462-012-9365-8
                8ecc67af-5f8f-4d72-8e4b-e379c6d1e815
                © 2015
                History

                Comments

                Comment on this article