Attentional Scene-Exploration and Object Discovery in Image and RGB-D Data

In this paper, we summarize our project work of the last two years, where we addressed the tasks of visually exploring a scene with visual attention mechanisms based on saliency computation, and of locating unknown objects in the environment. The latter is also called object discovery and consists in finding candidate objects without previous knowledge about the objects themselves or the scene. We follow an approach motivated from human perception and combine saliency and segmentation to generate object candidates. We show results on 2D images as well as on 3D sequences obtained from an RGB-D camera.