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Grasping and manual interaction for robots so far has largely been approached with an emphasis on physics and control aspects. Given the richness of human manual interaction, we argue for the consideration of the wider field of “manual intelligence” as a perspective for manual action research that brings the cognitive nature of human manual skills to the(More)
We implemented a system, called the VICON-EyeTracking Visualizer, that combines mobile eye tracking data with motion capture data to calculate and visualize the 3D gaze vector within the motion capture co-ordinate system. To ensure that both devices were temporally synchronized we used previously developed software by us. By placing reflective markers on(More)
We propose a task-specific digital holographic capture system for three-dimensional scenes, which can reduce the amount of data sent from the camera system to the receiver and can effectively reconstruct partially occluded objects. The system requires knowledge of the object of interest, but it does not require a priori knowledge of either the occlusion or(More)
We present a digital signal processing technique that reduces the speckle content in reconstructed digital holograms. The method is based on sequential sampling of the discrete Fourier transform of the reconstructed image field. Speckle reduction is achieved at the expense of a reduced intensity and resolution, but this trade-off is shown to be greatly(More)
One of the principal successes of computer vision over the past thirty years has been the development of robust techniques for the estimation of the structure of a 3D scene given multiple views of that scene. Since holograms permit reconstruction of arbitrary views of the scene they provide a novel avenue of extension to these traditional computer vision(More)
To enable the creation of manual interaction databases, aiding the replication of dexterous capabilities with anthropomorphic robot hands by utilizing information about how humans perform complex manipulation tasks, requires the capability to record and analyze large amounts of manual interaction sequences. For this goal we have studied and compared three(More)
We present a novel dataglove mapping technique based on parameterisable models that handle both the cross coupled sensors of the fingers and thumb, and the under-specified abduction sensors for the fingers. Our focus is on realistically reproducing the posture of the hand as a whole, rather than on accurate fingertip positions. The method proposed in this(More)