A novel mismatching elimination algorithm based on distribution of features
| Autor: | Chuanjia Liu, Chengtao Cai, Qidan Zhu |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Matching (graph theory)
business.industry Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition 02 engineering and technology 01 natural sciences Image (mathematics) Visualization Visual field 010309 optics Catadioptric system Distribution (mathematics) 0103 physical sciences 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Algorithm Feature detection (computer vision) |
| Zdroj: | CSCWD |
| DOI: | 10.1109/cscwd.2016.7566021 |
| Popis: | Catadioptric panoramic image's application to computer visual field gains its popularity in recent years. However, due to its complicated imaging relationship, most existing mismatching elimination algorithms cannot directly operate on the unprocessed panoramic images. Those above algorithms usually need to unwarp the panoramic images before further processing. In order to solve the above problems, based on the distribution characteristics of features in the panoramic image, a novel mismatching elimination algorithm is proposed in this paper. Under different scene conditions, the novel algorithm can eliminate the mismatching features and improve the matching accuracy effectively. Experiments on the image databases confirm its effectiveness. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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