A component-wise analysis of constructible match cost functions for global stereopsis
Match cost functions are common elements of every stereopsis algorithm that are used to provide a dissimilarity measure between pixels in different images. Global stereopsis algorithms incorporate assumptions about the smoothness of the resulting distance map that can interact with match cost functi...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1998. - 33(2011), 11 vom: 15. Nov., Seite 2147-59 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2011
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article |
| Zusammenfassung: | Match cost functions are common elements of every stereopsis algorithm that are used to provide a dissimilarity measure between pixels in different images. Global stereopsis algorithms incorporate assumptions about the smoothness of the resulting distance map that can interact with match cost functions in unpredictable ways. In this paper, we present a large-scale study on the relative performance of a structured set of match cost functions within several global stereopsis frameworks. We compare 272 match cost functions that are built from component parts in the context of four global stereopsis frameworks with a data set consisting of 57 stereo image pairs at three different variances of synthetic sensor noise. From our analysis, we infer a set of general rules that can be used to guide derivation of match cost functions for use in global stereopsis algorithms |
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| Beschreibung: | Date Completed 24.02.2012 Date Revised 01.12.2011 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1939-3539 |
| DOI: | 10.1109/TPAMI.2011.67 |