Real-time video photomosaics with optimized image set and GPU

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.