Enhanced Geometric Techniques for Point Marking in ModelFree Augmented Reality Specifying points in threedimensional (3D) space is an essential function in many augmented reality (AR) applications. When an environment model is not available, a straightforward solution is to perform geometric triangulation using two rays. However, naive implementations suffer from low accuracy caused by technical limitations of AR devices and human motor constraints. To overcome these issues, we designed and evaluated two enhanced geometric techniques for 3D point marking. VectorCloud uses multiple rays to reduce the effects of pointing jitter, and ImageRefinement improves the accuracy by allowing users to refine the 3D direction of the two rays. We conducted studies to understand the characteristics of these techniques in both ecologically valid outdoor settings using a mobile AR display and in more controlled setting using virtual reality simulation. Our experiments demonstrate that both techniques improve the precision of 3D point marking, and that ImageRefinement is superior to VectorCloud overall. These results are particularly relevant in the design of mobile AR systems intended for use in large outdoor areas.

Tangible and Visible 3D Object Reconstruction in Augmented Reality Many crucial applications in the fields of filmmaking, game design, education, and cultural preservation xe2x80x94 among others xe2x80x94 involve the modeling, authoring, or editing of 3D objects and scenes. The two major methods of creating 3D models are 1) modeling, using computer software, and 2) reconstruction, generally using highquality 3D scanners. Scanners of sufficient quality to support the latter method remain unaffordable to the general public. Since the emergence of consumergrade RGBD cameras, there has been a growing interest in 3D reconstruction systems using depth cameras. However, most such systems are not userfriendly, and require intense efforts and practice if good reconstruction results are to be obtained. In this paper, we propose to increase the accessibility of depthcamerabased 3D reconstruction by assisting its users with augmented reality (AR) technology. Specifically, the proposed approach will allow users to rotatemove a target object freely with their hands and see the object being overlapped with its reconstructing model during the reconstruction process. As well as being more instinctual than conventional reconstruction systems, our proposed system will provide useful hints on complete 3D reconstruction of an object, including the best capturing range; reminder of moving and rotating the object at a steady speed; and which model regions are complex enough to require zoomingin. We evaluated our system via a user study that compared its performance against those of three other stateof theart approaches, and found our system outperforms the other approaches. Specifically, the participants rated it highest in usability, understandability, and model satisfaction.