Constructing immersive virtual space for HAI with photos

1. Constructing immersive virtual space for HAI with photos Shingo Mori YoshimasaOhmoto Toyoaki Nishida Graduate School of Informatics Kyoto University GrC2011 2011/11/09

2. Abstract • We automatically construct immersivevirtual spaces for human agent interaction • Scenes are drawn by external photo images • Depth maps are reconstructed to express occlusion • Rough 3D models are added for agents • Processing time is about 4.7 days to reconstruct a 20m×20mvirtualspace

3. Introduction • We want to observe HHI using HAI in a virtual space • For example, for a virtual sightseeing task: • we can select faraway place such as foreign country • we can easily prepare an environment to observe • Our Goal: creating a system to construct an environment for such a task

4. Introduction • To do the sightseeing task and observe interaction, the environment should look like the real world • virtual spaces should be immersive • scenes recreated by real world photos are needed • spatial relationship between agent and object should be correct • users can walk freely on some level • How to construct such a virtual space?

5. Related Work • Model Based Rendering (MBR) • can reconstruct 3D models • make arbitrary consistent views easily • weak at trees or texture-less surfaces • [1-3] are good methods but, • [1] can’t use outside scenes because they use Manhattan World Assumption • [2,3] need expensive equipment or lots of time and effort [1] Furukawa et al. 2010, Reconstructing build-ing interiors from images [2] Pollefeys et al. 2008,Detailed real-time urban 3d reconstruction from video [3] Ikeuchi et al,2004, Bayon digital archival project

6. Related Work • Image Based Rendering (IBR) • make a new viewpoint image by interpolation • draw clearly complex structures such as natural objects • weak at occlusion • [4-5] have good image quality but, • they don’t consider agents • movable space is restricted [4]Google Street View [5] Ibuki , 2009, Reduction of Unnatural Feeling in Free-viewpoint Rendering Using View-Dependent Deformable 3-D Mesh Model (Japanese)

7. Our Method • To make the immersive environment, we use IBR • because high image quality is needed to show the scene • use panorama images and omnidirectional display to show environment

8. Our Method • To collect photo images • divide a space in into a 1-2m grid • shoot about 18 photos in each grid • We use interpolation when moving from one shooting point to another obstacle 1-2 meter shooting direction shooting point

9. Our Method • 3D geometry is needed for agents • use Structure from Motion and stereo method in a similar way [1,5] • create depth map for occlusion between objects and agents • This information is used for better IBR • camera position & rotation • 3D position of a point cloud

10. System Pipeline Photos ：Input ：Process System of Constructing Virtual Space ：Output Structure from Motion camera parameter Segmentation segmented image Use previous work Multi view Stereo CMVS patches rough 3D model Tackle in this research Creating Depth Map Creating Panorama depth map panorama image panorama depth map Show a Immersive Virtual Space Interpolation interpolated image

11. Structure from Motion (SfM) • Estimate camera parameters (projection matrix) from multiple photos • we use Bundler[6] camera position points clout and camera position camera position photos [6]Snavely et al. 2006, Photo tourism: exploring photo collections in 3D

12. Multi view Stereo • Reconstruct 3D geometry • we use CMVS[7] and Poisson Surface Reconstruction[8] • get a point cloud (patches) and rough 3D model photos and translate matrix patches and rough 3D model [7] Furukawaet al. 2010, Towards internet-scale multi-view stereo [8] Kazhdan et al. 2006, Poisson surface reconstruction

13. Create Depth Map • Deal with holes and outliers of the point cloud • Using an assumption that the real world is constructed by a planar surface • reconstruct surface from projected patches • Vertical surface can be almost reconstruct project patches raw image segmented image depth map

14. Create Panorama Image • To show a scene in an omnidirectional display, we create panorama images • we use Microsft ICE[9] • canonicalizedirection of panorama image from camera rotation [9]MicrosoftCorporation, Microsoft image composite editor http://research.microsoft.com/en-us/um/redmond/groups/ ivm/ice.html. panorama image and depth map

15. Interpolation • To move freely, we create interpolated images between near panorama images • correctly move direction and distance about object two raw panorama images about 1-2m away from each other project patches to use as feature point find corresponding point interpolate by morphing(medium point between raw images)

16. Demo

17. Processing Time • We experimented with 3 spaces • Most of the processing time is SfM • We can drastically improveif we use [10] • Each shooting times are about one hour [10]Agarwal et al.2009, Building rome in a day

18. Conclusion • Conclusion • create a system to automatically construct virtual spaces for HAI • unify various methods to create the system • Future work • expand virtual spaces • research how natural and useful it for HAI • observe HAI and feed back to the real world