Research on Salient Object Detection using Deep Learning and Segmentation Methods

Abstract

Detecting and segmenting salient objects in natural scenes, often referred to as salient object detection has attracted a lot of interest in computer vision and recently various heuristic computational models have been designed. While many models have been proposed and several applications have emerged, yet a deep understanding of achievements and issues is lacking. The aim of this review work is to study about the details of methods in salient object detection. It not only focuses on the methods to detect saliency objects, but also reviews the works related to spatio temporal video attention detection technique in video sequences. It also discusses the open issues in terms of evaluation metrics and dataset bias in model performance and suggests future research directions. The evaluation metrics are classified into mean absolute error (MAE), Accuracy and Run-Time complexity