A Non-parametric Approach to Detect Changes in Aerial Images
| Autor: | William Robson Schwartz, Erickson R. Nascimento, Marco Túlio Alves N. Rodrigues, Daniel Balbino |
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| Rok vydání: | 2015 |
| Předmět: |
Computer science
business.industry Kernel density estimation ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Nonparametric statistics Image processing Visual surveillance Robustness (computer science) Contextual information Computer vision Artificial intelligence business Civil infrastructure Change detection |
| Zdroj: | Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications ISBN: 9783319257501 CIARP |
| DOI: | 10.1007/978-3-319-25751-8_15 |
| Popis: | Detecting changes in aerial images acquired from a scene at different times, possibly with different cameras and at different view points, is a crucial step for many image processing and computer vision applications, such as remote sensing, visual surveillance and civil infrastructure. In this paper, we propose a novel approach to automatically detect changes based on local descriptors and a non-parametric image block modeling. Differently from most approaches, which are pixel-based, our approach combines contextual information and kernel density estimation to model the image regions to identify changes. The experimental results show the effectiveness of the proposed approach compared to other methods in the literature, demonstrating the robustness of our algorithm. The results also demonstrate that the approach can be employed to generate a summary containing mostly frames presenting significant changes. |
| Databáze: | OpenAIRE |
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