Keywords

computer vision, user interface, device, optical flow, motion, tracking, egomotion, navigation

Abstract

We present a novel, real-time, markerless vision-based tracking system, employing a rigid orthogonal configuration of two pairs of opposing cameras. Our system uses optical flow over sparse features to overcome the limitation of vision-based systems that require markers or a pre-loaded model of the physical environment. We show how opposing cameras enable cancellation of common components of optical flow leading to an efficient tracking algorithm that captures five degrees of freedom including direction of translation and angular velocity. Experiments comparing our device with an electromagnetic tracker show that its average tracking accuracy is 80% over 185 frames, and it is able to track large range motions even in outdoor settings. We also present how opposing cameras in vision-based inside-looking-out systems can be used for gesture recognition. To demonstrate our approach, we discuss three different algorithms for recovering motion parameters at different levels of complete recovery. We show how optical flow in opposing cameras can be used to recover motion parameters of the multi-camera rig. Experimental results show gesture recognition accuracy of 88.0%, 90.7% and 86.7% for our three techniques, respectively, across a set of 15 gestures.

Notes

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Graduation Date

2010

Advisor

daVitoria Lobo, Niels

Degree

Master of Science (M.S.)

College

College of Engineering and Computer Science

Department

Electrical Engineering and Computer Science

Degree Program

Computer Science

Format

application/pdf

Identifier

CFE0003163

URL

http://purl.fcla.edu/fcla/etd/CFE0003163

Language

English

Release Date

August 2010

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

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