A Process for the SemiAutomated Generation of LifeSized, Interactive 3D Character Models for Holographic Projection By mixing digital data into the real world, Augmented Reality (AR) can deliver potent immersive and interactive experience to its users. In many application contexts, this requires the capability to deploy animated, high fidelity 3D character models. In this paper, we propose a novel approach to efficiently transform xe2x80x93 using 3D scanning xe2x80x93 an actor to a photorealistic, animated character. This generated 3D assistant must be able to move to perform recorded motion capture data, and it must be able to generate dialogue with lip sync to naturally interact with the users. The approach we propose for creating these virtual AR assistants utilizes photogrammetric scanning, motion capture, and free viewpoint video for their integration in Unity. We deploy the Occipital Structure sensor to acquire static highresolution textured surfaces, and a Vicon motion capture system to track series of movements. The proposed capturing process consists of the steps scanning, reconstruction with Wrap 3 and Maya, editing texture maps to reduce artefacts with Photoshop, and rigging with Maya and Motion Builder to render the models fit for animation and lipsync using LipSyncPro. We test the approach in Unity by scanning two human models with 23 captured animations each. Our findings indicate that the major factors affecting the result quality are environment setup, lighting, and processing constraints.

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.