This paper presents a method for measuring the entire three dimensional (3D) shape of an object, which is applicable for 3D digitizing into a solid modeler. The method realizes automatic acquisition of the complete surface model of the object without contact. The method employs two range finders and a turntable cooperatively: a range finder and the turntable measure the surface data of the object rapidly, and then another hand-eye range finder finds deficits in the surface data due to self-occlusion, and corrects them. This method realizes sensory fusion in acquisition of range data. Several 3D-shape data provided by two range finders are integrated into voxel data. The voxe representation allows us to handle the entire shape of an arbitrary object. The experimental system based on this method demonstrates the good flexibility and performance of the method for 3D digitizing.

This paper presents an intuitive interaction technique for data exchange between multiple co-located devices. In the proposed system, CrossOverlayDesktop, desktop graphics of the devices are graphically overlaid with each other (i.e., alpha-blended). Users can exchange file data by the usual drag-and-drop manipulation through an overlaid area. The overlaid area is determined by the physical six degrees of freedom (6-DOF) correlation of the devices and thus changes according to users' direct movements of the devices. Because familiar operations such as drag-and-drop can be applied to file exchange between multiple devices, seamless, consistent, and thus intuitive multi-user collaboration is realized. Furthermore, dynamic overlay of desktop graphics allows users to intuitively establish communication, identify connected devices, and perform access control. For access control of the data, users can protect their own data by simply dragging them out of the overlaid area, because only the overlaid area becomes a public space. Several proof-of-concept experiments and evaluations were conducted. Results show the effectiveness of the proposed interaction technique.

In this study, we introduce a system for tracking multiple people using multiple active cameras. Our main objective is to surveille as many targets as possible, at any time, using a limited number of active cameras. In our context, an active camera is a statically located pan-tilt-zoom camera. In this research, we aim to optimize the camera configuration to achieve maximum coverage of the targets. We first devise a method for efficient tracking and estimation of target locations in the environment. Our tracking method is able to track an unknown number of targets and easily estimate multiple future time-steps, which is a requirement for active cameras. Next, we present an optimization of camera configuration with variable time-step that is optimal given the estimated object likelihoods for multiple future frames. We confirmed our results using simulation and real videos, and show that without introducing any significant computational complexities, it is possible to use active cameras to the point that we can track and observe multiple targets very effectively.