Model-based recognition of 2D objects under perspective distortion
| Autor: | S. Wirtz, K. Falkowski, Dietrich Paulus |
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| Rok vydání: | 2012 |
| Předmět: |
Perspective distortion
Theoretical computer science Computer science Heuristic 3D single-object recognition Pattern recognition (psychology) Cognitive neuroscience of visual object recognition State space Computer Vision and Pattern Recognition Computer Graphics and Computer-Aided Design Object detection Hash table |
| Zdroj: | Pattern Recognition and Image Analysis. 22:419-432 |
| ISSN: | 1555-6212 1054-6618 |
| DOI: | 10.1134/s105466181202023x |
| Popis: | We report on a case study showing on recognition of objects under perspective distortion in projected 2d images. We use symbolic descriptions and yield similar results as heuristic or statistical methods. The knowledge is modeled in so-called TGraphs which are typed, attributed, and ordered directed graphs. We combine the search in the state space with a maximum weight bipartite graph-matching and in consequence we reduce the numerous amount of hypotheses. Furthermore we use hash tables to increase the runtime efficiency. As a result we reduce the runtime up to a factor of five in comparison to the system without hash tables and achieve a detection rate of 90.6% for a data set containing 968 perspective images of poker cards and domino tiles. Therefore, we show that model-based object recognition using symbolic descriptions is on a competitive basis. |
| Databáze: | OpenAIRE |
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