A coarse-to-fine strategy for multiclass shape detection
Multiclass shape detection, in the sense of recognizing and localizing instances from multiple shape classes, is formulated as a two-step process in which local indexing primes global interpretation. During indexing a list of instantiations (shape identities and poses) is compiled, constrained only...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 26(2004), 12 vom: 13. Dez., Seite 1606-21 |
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| Format: | Aufsatz |
| Sprache: | English |
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2004
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article |
| Zusammenfassung: | Multiclass shape detection, in the sense of recognizing and localizing instances from multiple shape classes, is formulated as a two-step process in which local indexing primes global interpretation. During indexing a list of instantiations (shape identities and poses) is compiled, constrained only by no missed detections at the expense of false positives. Global information, such as expected relationships among poses, is incorporated afterward to remove ambiguities. This division is motivated by computational efficiency. In addition, indexing itself is organized as a coarse-to-fine search simultaneously in class and pose. This search can be interpreted as successive approximations to likelihood ratio tests arising from a simple ("naive Bayes") statistical model for the edge maps extracted from the original images. The key to constructing efficient "hypothesis tests" for multiple classes and poses is local ORing; in particular, spread edges provide imprecise but common and locally invariant features. Natural tradeoffs then emerge between discrimination and the pattern of spreading. These are analyzed mathematically within the model-based framework and the whole procedure is illustrated by experiments in reading license plates |
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| Beschreibung: | Date Completed 12.01.2005 Date Revised 02.12.2004 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1939-3539 |