Finding Visual Attention in an Image: Learning through Hierarchal Inheritance Approach

Finding visually attractive region in an image is one of the interesting research area due to its real time applications. Generally we take the images to capture objects (visually attractive region). In this paper the proposed approach regards the important object detection in an image. The proposed algorithm contains multiple phases: preparing the super-pixel using ensemble decision trees to estimate the adjacency probability between the regions, and forming the saliency vector (visually attractive region) using the learned weights through hierarchal inheritance approach. The proposed approach is tested on several popular benchmark data-sets and performed well among the present approaches. The results were compared and shown in section 6.