In this paper we present a system for progressive encoding, storage, transmission, and web based visualization of large point cloud datasets. Point cloud data is typically recorded on-set during a film production, and is later used to assist with various stages of the post-production process. The remote visualization of this data (on or off-set, either via desktop or mobile device) can be difficult, as the volume of data can take a long time to be transferred, and can easily overwhelm the memory of a typical 3D web or mobile client. Yet web-based visualization of this data opens up many possibilities for remote and collaborative workflow models. In order to facilitate this workflow, we present a system to progressively transfer point cloud data to a WebGL based client, updating the visualisation as more information is downloaded and maintaining a coherent structure at lower resolutions. Existing work on progressive transfer of 3D assets has focused on well-formed triangle meshes, and thus is unsuitable for use with raw LIDAR data. Our work addresses this challenge directly, and as such the principal contribution is that it is the first published method of progressive visualization of point cloud data via the web.
Within Human-Computer Interaction, there has recently been an important turn to embodied and voice-based interaction. In this chapter, we discuss our ongoing research on building online Embodied Conversational Agents (ECAs), specifically, their interactive 3D web graphics aspects. We present ECAs based on our technological pipeline, which integrates a number of free online editors, such as Adobe Fuse CC or MakeHuman, and standards, mainly BML (Behaviour Markup Language). We claim that making embodiment available for online ECAs is attainable, and advantageous over current alternatives, mostly desktop-based. In this chapter we also report on initial results of activities aimed to explore the physical appearance of ECAs for older people. A group of them (N=14) designed female ECAs. Designing them was easy and great fun. The perspective on older-adult HCI introduced in this chapter is mostly technological, allowing for rapid online experimentations to address key issues, such as anthropomorphic aspects, in the design of ECAs with, and for, older people.
A typical high-end film production generates several terabytes of data per day, either as footage from multiple cameras or as background information regarding the set (laser scans, spherical captures, etc). The EU project IMPART (impart.upf.edu) has been researching solutions that improve the integration and understanding of the quality of the multiple data sources to support creative decisions onset or near it, and an enhanced post-production as well. The main results covered in this paper are: a public multisource production dataset made available for research purposes, monitoring and quality assurance of multicamera set-ups, multisource registration, anthropocentric visual analysis for semantic content annotation, acceleration of 3D reconstruction, and integrated 2D-3D web visualization tools.
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