A GPU based Real-Time CUDA implementation for obtaining Visual Saliency
Rahul Agrawal, Soumyajit Sen Gupta, Jayanta Mukherjee, Ritwik Kumar Layek · 2014
We present a GPU-based implementation of the saliency model proposed by Achanta et al. [1] to perform real-time and detailed saliency map generation. We map all the components of the algorithm to GPU-based kernels and data structures. The parallel version of the algorithm is able to accurately simulate the desired results in a very low time. We describe the streaming pipeline and address many issues in terms of obtaining high throughput on multi-core GPUs. We highlight the parallel performance of the algorithm on three different generations of GPUs. On a high-end NVIDIA Tesla K20m, we observe up to 600x order of magnitude performance improvement as compared to a single-threaded CPU-based algorithm, and about 300x order of magnitude improvement over a CPU-based OpenCV implementation.