Challenges of Large-Scale Augmented Reality on Smartphones

Smartphones have been identified as most promising future devices for an Augmented Reality (AR) mass market. However, their use puts considerable constraints on the design and composition of AR applications. The key problem is to find a registration mechanism for accurate six degree of freedom (6DOF) self-localization with respect to the environment. Approaches based on Computer Vision (CV) have been shown to be promising, but the feasibility of many CV methods on smartphones is questionable. In this paper we discuss current and future challenges faced in developing AR on smartphones, in particular for large and unconstrained outdoor environments. We focus on the registration task, giving a survey and an assessment of existing approaches from AR and CV. From this survey, we identify a set of important issues still seeking for practical solutions, both in terms of the fundamental registration problem and for making AR on smartphones a unique experience. As will become apparent, despite recent advances, we are still far from arriving at a universal solution to the problem.

[1]  Alexei A. Efros,et al.  IM2GPS: estimating geographic information from a single image , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[2]  Steven Zhiying Zhou,et al.  Positioning, tracking and mapping for outdoor augmentation , 2010, 2010 IEEE International Symposium on Mixed and Augmented Reality.

[3]  Wei Zhang,et al.  Image Based Localization in Urban Environments , 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

[4]  Dieter Schmalstieg,et al.  Wide area localization on mobile phones , 2009, 2009 8th IEEE International Symposium on Mixed and Augmented Reality.

[5]  G. Klein,et al.  Parallel Tracking and Mapping for Small AR Workspaces , 2007, 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality.

[6]  David W. Murray,et al.  Parallel Tracking and Mapping on a camera phone , 2009, 2009 8th IEEE International Symposium on Mixed and Augmented Reality.

[7]  Richard Szeliski,et al.  City-Scale Location Recognition , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Daniel P. Huttenlocher,et al.  Location Recognition Using Prioritized Feature Matching , 2010, ECCV.

[9]  Tom Drummond,et al.  Going out: robust model-based tracking for outdoor augmented reality , 2006, 2006 IEEE/ACM International Symposium on Mixed and Augmented Reality.

[10]  Kurt Konolige,et al.  Real-time Localization in Outdoor Environments using Stereo Vision and Inexpensive GPS , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[11]  Marc Levoy,et al.  The Frankencamera: an experimental platform for computational photography , 2010, ACM Trans. Graph..

[12]  Supun Samarasekera,et al.  Real-time global localization with a pre-built visual landmark database , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[13]  David W. Murray,et al.  Real-time localization and mapping with wearable active vision , 2003, The Second IEEE and ACM International Symposium on Mixed and Augmented Reality, 2003. Proceedings..

[14]  Jana Kosecka,et al.  Landmark-Based Pedestrian Navigation with Enhanced Spatial Reasoning , 2009, Pervasive.

[15]  Mubarak Shah,et al.  Accurate Image Localization Based on Google Maps Street View , 2010, ECCV.

[16]  Douglas C. Schmidt,et al.  Addressing Challenges with Augmented Reality Applications on Smartphones , 2010, MOBILWARE.

[17]  Bernd Girod,et al.  Outdoors augmented reality on mobile phone using loxel-based visual feature organization , 2008, MIR '08.

[18]  Dieter Schmalstieg,et al.  Pose tracking from natural features on mobile phones , 2008, 2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality.

[19]  Michel Dhome,et al.  Real-time vehicle global localisation with a single camera in dense urban areas: Exploitation of coarse 3D city models , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[20]  Roberto Cipolla,et al.  An Image-Based System for Urban Navigation , 2004, BMVC.

[21]  Yang Song,et al.  Tour the world: Building a web-scale landmark recognition engine , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[22]  Marc Pollefeys,et al.  Handling Urban Location Recognition as a 2D Homothetic Problem , 2010, ECCV.

[23]  Alexei A. Efros,et al.  Image sequence geolocation with human travel priors , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[24]  Jan-Michael Frahm,et al.  From structure-from-motion point clouds to fast location recognition , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[25]  Michel Dhome,et al.  Real Time Localization and 3D Reconstruction , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[26]  Xin Chen,et al.  City-scale landmark identification on mobile devices , 2011, CVPR 2011.

[27]  James J. Little,et al.  Global localization using distinctive visual features , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[28]  Dieter Schmalstieg,et al.  First steps towards handheld augmented reality , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..

[29]  Tomás Pajdla,et al.  Avoiding Confusing Features in Place Recognition , 2010, ECCV.

[30]  Jana Kosecka,et al.  Probabilistic location recognition using reduced feature set , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..