Graph model-based salient object detection using objectness and multiple saliency cues
Graph model-based salient object detection using objectness and multiple saliency cues is a scholarly work, published in 2019 in ''Neurocomputing''. The main subjects of the publication include Laplacian matrix, object, salient, feature engineering, graph, artificial intelligence, computer vision, eye tracking, Video Sequences Saliency Map, benchmark, pattern recognition, and computer science. In this paper, by considering both objectness cue and saliency detection, authors propose a graph model-based bottom-up salient object detection framework by fusing multiple saliency maps using low-level features and objectness features under a manifold ranking framework.