In this paper we present a public dataset to evaluate trackers used for human and robot manipulation tasks. For these tasks both high DOF motion and high accuracy is needed. We describe in detail, both the process of recording the sequences and how ground truth data was generated for the videos. The videos are tagged with challenges that a tracker would face while tracking the object. As an initial example, we evaluate the performance of six published trackers [5], [11], [12], [13], [15], [6] and analyse their result. We describe a new evaluation metric to test sensitivity of trackers to speed. A total of 100 annotated and tagged sequences are reported. All the videos, ground truth data, original implementation of trackers and evaluation scripts are made publicly available on the website so others can extend the results on their trackers and evaluation.

Pointing to indicate direction or position is one of the intuitive communication mechanisms used by humans in all life stages. Our aim is to develop a natural human-robot command interface using pointing gestures for human-robot interaction (HRI). We propose an interface based on the Kinect sensor for selecting by pointing (SEPO) in a 3D real-world situation, where the user points to a target object or location and the interface returns the 3D position coordinates of the target. Through our interface we perform three experiments to study precision and accuracy of human pointing in typical household scenarios: pointing to a “wall”, pointing to a “table”, and pointing to a “floor”. Our results prove that the proposed SEPO interface enables users to point and select objects with an average 3D position accuracy of 9:6 cm in household situations.