Title :
Pose tracking from natural features on mobile phones
Author :
Wagner, Daniel ; Reitmayr, Gerhard ; Mulloni, Alessandro ; Drummond, Tom ; Schmalstieg, Dieter
Author_Institution :
Graz Univ. of Technol., Graz
Abstract :
In this paper we present two techniques for natural feature tracking in real-time on mobile phones. We achieve interactive frame rates of up to 20 Hz for natural feature tracking from textured planar targets on current-generation phones. We use an approach based on heavily modified state-of-the-art feature descriptors, namely SIFT and Ferns. While SIFT is known to be a strong, but computationally expensive feature descriptor, Ferns classification is fast, but requires large amounts of memory. This renders both original designs unsuitable for mobile phones. We give detailed descriptions on how we modified both approaches to make them suitable for mobile phones. We present evaluations on robustness and performance on various devices and finally discuss their appropriateness for augmented reality applications.
Keywords :
augmented reality; feature extraction; image texture; mobile computing; mobile handsets; pose estimation; target tracking; Ferns feature descriptor; SIFT feature descriptor; augmented reality; current-generation phone; mobile phone; natural feature tracking; pose tracking; textured planar target; Application software; Augmented reality; Computer vision; Detectors; Image edge detection; Mobile computing; Mobile handsets; Personal communication networks; Real time systems; Target tracking; H.5.1 [Information Interfaces and Presentation]: Multimedia Information Systems — Artificial, augmented, and virtual realities; I.4.8 [Image Processing and Computer Vision]: Scene Analysis — Tracking; mobile phones; natural features; pose tracking;
Conference_Titel :
Mixed and Augmented Reality, 2008. ISMAR 2008. 7th IEEE/ACM International Symposium on
Conference_Location :
Cambridge
Print_ISBN :
978-1-4244-2840-3
Electronic_ISBN :
978-1-4244-2859-5
DOI :
10.1109/ISMAR.2008.4637338