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Compression of 3D object based video is relevant for 3D Immersive applications. Nevertheless, the perceptual aspects of the degradation introduced by codecs for meshes and point clouds are not well understood. In this paper we evaluate the subjective and objective degradations introduced by such codecs in a state of art 3D immersive virtual room. In the 3D immersive virtual room, users are captured with multiple cameras, and their surfaces are reconstructed as photorealistic colored/textured 3D meshes or point clouds. To test the perceptual effect of compression and transmission, we render degraded versions with different frame rates in different contexts (near/far) in the scene. A quantitative subjective study with 16 users shows that negligible distortion of decoded surfaces compared to the original reconstructions can be achieved in the 3D virtual room. In addition, a qualitative task based analysis in a full prototype field trial shows increased presence, emotion, user and state recognition of the reconstructed 3D Human representation compared to animated computer avatars.

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Disaster Risk Reduction (DRR) is a complex field in which a huge amount of data is used to plan preventive measures, get prepared to natural disasters, and effectively respond when they strike. This work focuses on the definition of a co-design methodology to integrate a crowdsourcing solution in the DRR processes. We define the proposed methodology, and implement it involving operators and experts in the DRR domain (crisis managers, technical services, first responders). We show how a participatory design approach helps in the design of a crowdsourcing solution that experts are willing to integrate into their DRR procedures.