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Real-Time Video Photomosaics with Optimized Image Set and GPU
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- Authors
- Yoon-Seok Choi, Soonchul Jung, Jae Woo Kim, Bon-Ki Koo
- Issue Date
- 2014-09
- Citation
- Journal of Real-Time Image Processing, v.9, no.3, pp.569-578
- ISSN
- 1861-8200
- Publisher
- Springer
- Language
- English
- Type
- Journal Article
- Abstract
- 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. © 2013 Springer-Verlag Berlin Heidelberg.
- KSP Keywords
- CUDA GPU, Computation cost, Feature selection(FS), GPU Acceleration, Genetic feature selection, High-quality, Limited resources, Mobile Application(APP), Pattern searching, Real-time video, Rectangular cells