## 3 Overview of Approach  
The proposed approach is overviewed in Figure 1. Our approach starts with understanding the studied craft process, defining pertinent activities, and recording them using video and/or MoCap.  
Afterwards, AnimIO is used to segment the recording and produce animation files and libraries of animation files. These libraries are imported in Unity3D and retargeted to avatars to be utilized within VR presentations.  
Process description: we start with interviews with the practitioners that will provide the demonstrations. This preparation is required to appropriately organize the acquisition of data, to understand the content and context of the recordings, and to provide instructions to practitioners regarding the recording protocol. Practitioners can be asked to explain the process and each task, to facilitate the annotation and motion segmentation of the data afterwards.  
Recording: In this phase, practitioners are recorded by (a) one or more video cameras imaging the scene from multiple viewpoints and/or (b) a motion capture suit. Depending on the number and type of recording modalities, recordings are synchronised and consolidated. In the case of multiple videos, multiple sources are consolidated via a multi-view Computer Vision algorithm; in our case [25]. We do not deal with the case of consolidating input from visual tracking and MoCap modalities, as MoCap is always more accurate. The synchronisation between multiple video sources is treated by vendor-dependent camera synchronisation utilities. A special case of synchronisation is that between a video and a MoCap recording of the same event. Even though only the MoCap recording is utilised in the 3D animation output, video facilitates understanding of MoCap data by non-domain experts. Currently, this is achieved by external utilities and comprises a goal of future work.  
Motion segmentation. The recordings are pre-processed for synchronization and AnimIO is operated to create multimodal motion segments. These segments contain synchronous recordings from multiple modalities and, in particular, video streams from multiple viewpoints or MoCap recordings. This is the phase where AnimIO is designed to be utilized by curators to encode their knowledge. This encoding refers to the annotation of motion data per activity executed. As such, AnimIO is designed to facilitate the temporal delimitation of motion segments by individual human limbs, while respecting constraints stemming from their hierarchical configuration.  
Animation libraries: An animation library is a collection of animation files. Animation files are motion segments, typically containing the recording on an individual action by one or multiple recording modalities. The motion data are encoded in the skeletal model configuration. For each joint, a 3D location and a 3D rotation are encoded as an individual stream. The definition of the skeletal hierarchy is determined in the header of the animation file. Motion data can be previewed within AnimIO in two different forms: (a) skeletal animation and (b) simplified skeletal animation. It is important to note that in AnimIO 3D viewer, motion data can be previewed in different angles, scale, and locations, thus taking full advantage of the 3D information for close inspection.  
Figure 1: Overview of the proposed approach.  
Motion Retargeting: This maps 3D motion data from the animation file to a rigged avatar model in Unity3D and ensures that all aspects of the animation are appropriately transferred to the avatar through a bone-mapping procedure.  
VR preview: This is the integration of the created animations to a VR environment, to preview the recorded craft processes performed by an avatar.