Journal of Computer Science

Multi-View RGB-D Video Analysis and Fusion for 360 Degrees Unified Motion Reconstruction

Naveed Ahmed

DOI : 10.3844/jcssp.2017.795.804

Journal of Computer Science

Volume 13, Issue 12

Pages 795-804


We present a new method for capturing human motion over 360 degrees by the fusion of multi-view RGB-D video data from Kinect sensors. Our method is able to reconstruct the unified human motion from fused RGB-D and skeletal data over 360 degrees and create a unified skeletal animation. We make use of all three streams: RGB, depth and skeleton, along with the joint tracking confidence state from Microsoft Kinect SDK to find the correctly oriented skeletons and merge them together to get a uniform measurement of human motion resulting in a unified skeletal animation. We quantitatively validate the goodness of the unified motion using two evaluation techniques. Our method is easy to implement and provides a simple solution of measuring and reconstructing a 360 degree plausible unified human motion that would not be possible to capture with a single Kinect due to tracking failures, self-occlusions, limited field of view and subject orientation.


© 2017 Naveed Ahmed. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.