Real-time video photomosaics with optimized image set and GPU
| Autor: | Bon-Ki Koo, Jae Woo Kim, Yoon-Seok Choi, Soonchul Jung |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
business.industry
Computer science Computation ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Feature selection Image (mathematics) Non-photorealistic rendering Computer graphics Set (abstract data type) CUDA Computer graphics (images) Pattern recognition (psychology) Computer vision Artificial intelligence business Information Systems |
| Zdroj: | Journal of Real-Time Image Processing. 9:569-578 |
| ISSN: | 1861-8219 1861-8200 |
| DOI: | 10.1007/s11554-013-0384-8 |
| Popis: | We propose a real-time approach to automatically generate photomosaic videos from a set of optimized images by taking advantage of CUDA GPU acceleration. Our approach divides an input image into smaller cells--usually rectangular cells--and replaces each cell with a small image of an appropriate color pattern. Photomosaics require a large set of tile images with a variety of patterns to create high-quality digital mosaic images. Because a large database of images requires longer processing time and larger storage space for searching patterns from the database, this requirement causes problems in developing a real-time system or mobile applications that have limited resources. This paper deals with a real-time video photomosaics using genetic feature selection method for building an optimized image set and taking advantage of CUDA to accelerate pattern searching that minimizes computation cost. |
| Databáze: | OpenAIRE |
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