Context-Aware Saliency Map Generation Using Semantic Segmentation

Saliency map detection is a method for detecting important regions of an image. Many applications, such as image classification and recognition, use saliency detection. We propose that context detection could have an essential role in image saliency detection. Context detection requires extraction of high-level features. In this paper, a saliency map is proposed, based on image context detection using semantic segmentation as a high-level feature. Saliency map from semantic information is fused with color and contrast based saliency maps. The final saliency map is then generated. Simulation results for Pascal-voc11 image dataset show 99% accuracy in context detection. Also, final saliency map produced by our proposed method shows acceptable results in detecting salient points.