RGB-D cameras, which give an RGB image together with depths, are becoming increasingly
popular for robotic perception. In this paper, we address the task of detecting commonly …

In this paper, a novel active vision strategy is proposed for optimizing the viewpoint of a
robot's vision sensor for a given success criterion. The strategy is based on extremum …

This paper presents a novel viewpoint selection criterion for active object recognition and
pose estimation whose key advantage resides in its low computational cost with respect to …

Grasp synthesis for unknown objects is a challenging problem as the algorithms are
expected to cope with missing object shape information. This missing information is a …

Object detection is a basic skill for a robot to perform tasks in human environments. In order
to build a good object classifier, a large training set of labeled images is required; this is …

Object recognition problems in computer vision are often based on single image data
processing. In various applications this processing can be extended to a complete sequence …

RGB-D cameras, which give an RGB image to-gether with depths, are becoming
increasingly popular for robotic perception. In this paper, we address the task of detecting …

While prior relevant research in active object recognition/pose estimation has mostly
focused on single-camera systems, we propose two multi-camera solutions to this problem …

We propose a novel general framework with a boosting algorithm to achieve active object
classification by view selection. The proposed framework actively decides the next best view …

Most current solutions to active perception planning struggle with complex state
representations or fast and efficient sensor parameter selection strategies. The goal is to find …