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Creating Personalized Avatars

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Digital Hampi: Preserving Indian Cultural Heritage
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Abstract

Digital heritage applications use virtual characters extensively to populate reconstructions of heritage sites in virtual and augmented reality. Creating these believable characters requires a lot of effort. The characters have to be modelled, textured, rigged and animated. In this chapter, we present a framework that captures a point cloud of a real user using multiple depth cameras and subsequently deforms a template mesh to match the captured geometry. The topology of the template mesh is preserved during the deformation process. We compare the measurements of limb lengths and body part ratios with actual corresponding anthropological measurements from the real user, in order to validate our system. Furthermore, we use a single depth camera to capture the motion of a real performer that we can then use to animate the mesh. This semi-automatic process only requires commodity depth cameras (Microsoft Kinect cameras) and no other specialized hardware. We also present extensions to available open-source animation authoring environment in Blender that allow us to synthesize character animation from prerecorded motion data. We then briefly discuss the challenges involved in enhancing the appearance of the characters by the physically based animation of virtual garments.

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Acknowledgements

We would like to thank the MakeHuman [13] project for the human template models and the Blender Foundation for the open-source Blender [3] 3D content creation software. This research was supported by the Immersive Digital Heritage project (NRDMS/11/1586/2009) under the Digital Hampi initiative of the Department of Science and Technology, Government of India.

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Correspondence to Parag Chaudhuri .

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Mashalkar, J., Chaudhuri, P. (2017). Creating Personalized Avatars. In: Mallik, A., Chaudhury, S., Chandru, V., Srinivasan, S. (eds) Digital Hampi: Preserving Indian Cultural Heritage. Springer, Singapore. https://doi.org/10.1007/978-981-10-5738-0_17

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  • DOI: https://doi.org/10.1007/978-981-10-5738-0_17

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