Authors:
Tommi Tykkälä
1
;
Hannu Hartikainen
2
;
Andrew I. Comport
3
and
Joni-Kristian Kämäräinen
4
Affiliations:
1
Lappeenranta University of Technology (LUT Kouvola), Finland
;
2
Aalto University, Finland
;
3
CNRS-I3S/University of Nice Sophia-Antipolis, France
;
4
Tampere University of Technology, Finland
Keyword(s):
Dense Tracking, Dense 3D Reconstruction, Real-time Tracking, RGB-D, Kinect.
Related
Ontology
Subjects/Areas/Topics:
Active and Robot Vision
;
Applications
;
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Enterprise Information Systems
;
Entertainment Imaging Applications
;
Geometry and Modeling
;
Human and Computer Interaction
;
Human-Computer Interaction
;
Image and Video Analysis
;
Image Registration
;
Image-Based Modeling
;
Motion, Tracking and Stereo Vision
;
Optical Flow and Motion Analyses
;
Pattern Recognition
;
Software Engineering
;
Stereo Vision and Structure from Motion
;
Tracking and Visual Navigation
Abstract:
In this work, a real-time image-based camera tracking solution is developed for television broadcasting studio environments. An affordable vision-based system is proposed which can compete with expensive matchmoving systems. The system requires merely commodity hardware: a low cost RGB-D sensor and a standard laptop. The main contribution is avoiding time-evolving drift by tracking relative to a pre-recorded keyframe
model. Camera tracking is defined as a registration problem between the current RGB-D measurement and the nearest keyframe. The keyframe poses contain only a small error and therefore the proposed method is virtually driftless. Camera tracking precision is compared to KinectFusion, which is a recent method for simultaneous camera tracking and 3D reconstruction. The proposed method is tested in a television broadcasting studio, where it demonstrates driftless and precise camera tracking in real-time.