Evaluation of Multi-Platform Mobile AR Frameworks for Roman Mosaic Augmentation
Presentation for the paper "Evaluation of Multi-Platform Mobile AR Frameworks for Roman Mosaic Augmentation" at the 16th EUROGRAPHICS Workshop on Graphics and Cultural Heritage (EG GCH), Vienna, Austria, 2018.
EUROGRAPHICS Workshop on Graphics and Cultural Heritage (2018) Vienna, Austria, November 12-15, 2018 Jorge C. S. Cardoso, André Belo CISUC/DEI, Universidade de Coimbra
Roman Mosaic Heritage present in the geographical axis constituted by ◦ the Ruins of the Roman city of Conímbriga, ◦ the Roman Villa of Rabaçal, and ◦ the Monumental Complex of Santiago da Guarda.
creative activities within the museums, interpretative centers and archaeological sites ◦ Integrated into the CREATOUR national project as a pilot initiative • Alternative experiences of sharing knowledge about the Roman Mosaic Heritage • Mosaic as a modern expression of creativity brought into the present and reinterpreted
technical information about the mosaics, for example, when they were uncovered, what was the latest conservation or restoration work, etc. ◦ Display image overlays of the conservation or restoration works on mosaics over time. ◦ Provide a platform for the visualization of virtual restoration of the existing mosaics. ◦ Highlight mosaics with graphical information regarding various motifs ▪ geometric patterns, animals, plants, compositions, mythological figures, etc. ◦
on Android, iOS, etc.) ▪ Single code base ▪ Lower development effort • What AR development frameworks are available for multi-platform mobile development? • Which AR development frameworks are most suitable for detecting real mosaics?
of the application over each of the mosaic targets • Three camera movements: ◦ Camera face down, turn up towards the target, then turn left, then right ◦ Horizontal pan left/right ◦ “Zoom in/out”
of the application over each of the mosaic targets • We analysed the various videos and extracted 3 metrics ◦ Recognition delay ◦ Minimum required target area ◦ Visual alignment and stability
targets were recognized ◦ This was expected ◦ Targets were captured from a distance ◦ Not much effort in capturing targets • Wikitude performed very poorly ◦ Unexpected ◦ Requires further study as to why
three frameworks: CraftAR, PixLive, Wikitude ◦ Wikitude failed, but more testing is required to dismiss it • Study allowed us to understand strong and weak points of these AR frameworks ◦ AR frameworks’ performance varies greatly depending on the type of image they are recognizing ◦ AR frameworks have different performance compromises ▪ No single one is best at every performance attribute • Virtual Heritage application developers should test different frameworks before commiting to one