Authors:
Yves Rangoni
and
Eric Ras
Affiliation:
Public Research Centre Henri Tudor, Luxembourg
Keyword(s):
Binarisation, Tangible User Interface, Object Tracking, 2D Marker Recognition, Computer Vision Framework, Benchmark.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Cardiovascular Imaging and Cardiography
;
Cardiovascular Technologies
;
Computer Vision, Visualization and Computer Graphics
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Image Understanding
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Object Recognition
;
Pattern Recognition
;
Physiological Computing Systems
;
Signal Processing
;
Software Engineering
Abstract:
This paper proposes a comparative study of different binarisation techniques for 2D fiducial marker tracking.
The application domain is the recognition of objects for Tangible User Interface (TUI) using a tabletop
solution. In this case, the common technique is to use markers, attached to the objects, which can be identified
using camera-based pattern recognition techniques. Among the different operations that lead to a good
recognition of these markers, the step of binarisation of greyscale image is the most critical one. We propose
to investigate how this important step can be improved not only in terms of quality but also in term of computational
efficiency. State-of-the-art thresholding techniques are benchmarked on this challenging task. A
real-world tabletop TUI is used to perform an objective and goal oriented evaluation through the ReacTIVision
framework. A computational efficient implementation of one of the best window-based thresholders is
proposed in order to satisfy the
real-time processing of a video stream. The experimental results reveal that
an improvement of up to 10 points of the fiducial tracking recognition rate can be reached when selecting the
right thresholder over the embedded method while being more robust and still remaining time-efficient.
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