Generation of Object Candidates Through Simply Looking Around.

In this paper, we consider the generation of generic object candidates by a mobile robot that is endowed with a pan-tilt monocular camera. This is an important problem because these candidates serve as basis for the robot to categorize and/or recognize the objects in its surroundings. The previously proposed methods either do not have a means of enabling the robot to look around through moving its camera or do not take advantage of the temporal coherence of the video data. We present a novel approach that enables the robot to achieve both of these capabilities simultaneously. In this approach, the robot’s camera movements are governed by a family of controllers whose constructions depend on the set of object candidates that have been hitherto generated, but not directly looked at. In parallel, the robot discovers the object candidates through tracking segments and determining spatio-temporally coherent ones. The advantage of the proposed approach is that while the robot can explore its surroundings by simply looking around prior to more sophisticated exploration behavior involving possibly bodily locomotion the generated object candidates turn out to be consolidated across the visual stream in comparison to single-shot methods. This is demonstrated in extensive experimental results with a robot operating indoors varying in clutter as well as outdoors.