2 research outputs found
Multi-view data capture for dynamic object reconstruction using handheld augmented reality mobiles
We propose a system to capture nearly-synchronous frame streams from multiple
and moving handheld mobiles that is suitable for dynamic object 3D
reconstruction. Each mobile executes Simultaneous Localisation and Mapping
on-board to estimate its pose, and uses a wireless communication channel to
send or receive synchronisation triggers. Our system can harvest frames and
mobile poses in real time using a decentralised triggering strategy and a
data-relay architecture that can be deployed either at the Edge or in the
Cloud. We show the effectiveness of our system by employing it for 3D skeleton
and volumetric reconstructions. Our triggering strategy achieves equal
performance to that of an NTP-based synchronisation approach, but offers higher
flexibility, as it can be adjusted online based on application needs. We
created a challenging new dataset, namely 4DM, that involves six handheld
augmented reality mobiles recording an actor performing sports actions
outdoors. We validate our system on 4DM, analyse its strengths and limitations,
and compare its modules with alternative ones.Comment: Accepted in Journal of Real-Time Image Processin