Visual Occlusion in Outdoor Augmented Reality Using TOF Camera and OpenGL Frame Buffer

Augmented Reality (AR) has the potential of being an effective visualization tool for planning and operations design in construction, manufacturing, and other process-oriented engineering domains. One of the primary challenges in creating AR visualizations is to project graphical 3D objects onto a user’s view of the real world and create a sustained illusion that the virtual and real objects co-exist across time in the same augmented space. However regardless of the spatial relationship between the real and virtual objects, traditional AR scene composing algorithm displays the real world merely as a background, and superimposes virtual objects in the foreground. This creates incorrect visual occlusion artifacts, that in effect breaks the illusion that real and virtual objects co-exist in AR. The research implements and demonstrates a robust depth sensing and frame buffer algorithm for resolving incorrect occlusion problems in outdoor AR applications. A high-accuracy Time-of-flight (TOF) camera capable of suppressing background illumination (e.g. bright sunlight) in ubiquitous environments is used to capture the depth map of real-world in real time. The preprocessed distance information is rendered into depth buffer, that allows the interpolation of visual or hidden elements in the OpenGL color buffer to generate the composite AR scene. An optimized approach taking advantage of OpenGL texture and GLSL fragment processor is also proposed to speed up sampling distance value and rendering into frame buffer. The designed algorithm is validated in several indoor and outdoor experiments using SMART AR framework. The AR space with occlusion effect enabled demonstrates convincing spatial cues and graphical realism.

[1]  Vincent Lepetit,et al.  A semi-automatic method for resolving occlusion in augmented reality , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[2]  Sang Hwa Lee,et al.  Real-Time Occlusion Culling for Augmented Reality , 2010 .

[3]  Matthias M. Wloka,et al.  Resolving occlusion in augmented reality , 1995, I3D '95.

[4]  Vineet R. Kamat,et al.  Scalable Algorithm for Resolving Incorrect Occlusion in Dynamic Augmented Reality Engineering Environments , 2010, Comput. Aided Civ. Infrastructure Eng..

[5]  Cheng Wang,et al.  Real-Time Occlusion Handling in Augmented Reality Based on an Object Tracking Approach , 2010, Sensors.

[6]  Patrick Hébert,et al.  Handling Occlusions in Real-time Augmented Reality : Dealing with Movable Real and Virtual Objects , 2006, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06).

[7]  S. Burak Gokturk,et al.  A Time-Of-Flight Depth Sensor - System Description, Issues and Solutions , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[8]  Vineet R. Kamat,et al.  Automated Generation of Operations Level Construction Animations in Outdoor Augmented Reality , 2009 .

[9]  Tinku Acharya,et al.  Image Processing: Principles and Applications , 2005, J. Electronic Imaging.

[10]  Vineet R. Kamat,et al.  Robust mobile computing framework for visualization of simulated processes in Augmented Reality , 2010, Proceedings of the 2010 Winter Simulation Conference.

[11]  T. Vincenty DIRECT AND INVERSE SOLUTIONS OF GEODESICS ON THE ELLIPSOID WITH APPLICATION OF NESTED EQUATIONS , 1975 .

[12]  Tom McREYNOLDS,et al.  Advanced Graphics Programming Using OpenGL , 2005 .

[13]  Mani Golparvar-Fard,et al.  Visualization of construction progress monitoring with 4D simulation model overlaid on time-lapsed photographs , 2009 .

[14]  Oliver Grau 3D in Content Creation and Post‐Production , 2006 .

[15]  Reinhard Koch,et al.  MixIn3D: 3D Mixed Reality with ToF-Camera , 2009, Dyn3D.

[16]  Reinhard Koch,et al.  A Comparison of PMD-Cameras and Stereo-Vision for the Task of Surface Reconstruction using Patchlets , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[17]  Marie-Odile Berger Resolving occlusion in augmented reality: a contour based approach without 3D reconstruction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Vineet R. Kamat,et al.  Evaluation of Augmented Reality for Rapid Assessment of Earthquake-Induced Building Damage , 2007 .