Probabilis)c Temporal Inference on Reconstructed 3D Scenes

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Transcription:

Probabilis)c Temporal Inference on Reconstructed 3D Scenes Grant Schindler Frank Dellaert Georgia Ins)tute of Technology

The World Changes Over Time How can we reason about )me in structure from mo)on problems?

Temporal Inference Problem 1. When was each photograph taken? 2. When did each building first appear? 3. When was each building removed? Set of Photographs: Set of Objects: Buildings 3

Temporal Inference Problem Temporal Inference Problem Given observa)ons Z and scene geometry X, what are the temporal parameters T? Structure (a, b) (x,y,z) Time Interval Posi)on Images Correspondences 3D Cameras t (x,y,z) (y,p,r) f Time Transla)on Rota)on Focal Length Structure from Mo?on 4

Overview 1891 1934 2007 1885 1953 1906 2009 1968 2009 Images Correspondences 3D Buildings Images + Time Structure + Time Intervals 4D 5

Overview 1891 1934 2007 1885 1953 1906 2009 1968 2009 Images Correspondences 3D Buildings Images + Time Structure + Time Intervals 4D 6

Overview 1891 1934 2007 1885 1953 1906 2009 1968 2009 Images Correspondences 3D Buildings Images + Time Structure + Time Intervals 4D 7

Overview 1891 1934 2007 1885 1953 1906 2009 1968 2009 Images Correspondences 3D Buildings Images + Time Structure + Time Intervals 4D 1937 2001 2009 8

3D Reconstruc)on Images 3D Point Cloud Structure from Mo?on Bundler So\ware by Noah Snavely (Snavely et al SIGGRAPH 2006) 1891 1934 2007 1885 1953 1906 2009 1968 2009 9

Grouping Points into Buildings 3D Point Cloud 3D Buildings Point Grouping Group points according to both: a. Distance < threshold in 3D b. Observed simultaneously in 1+ images Building Geometry 1. Convex hull of each group 2. Fit ground plane to camera centers 3. Extend convex hulls to ground 1891 1934 2007 1885 1953 1906 2009 1968 2009 10

3D Reconstruc)on: Points vs. Objects Lower Manhaban 454 images 83,860 points 960 Buildings 1928 2010 11

Reasoning About Time: From Constraint Sa)sfac)on Schindler et al. CVPR 2007. Inferring Temporal Order of Images from 3D Structure. Key Idea: Visibility of 3D points constrains image ordering Disadvantage: Only rela)ve image ordering Disadvantage: Perfect observa)ons required rules out fully automa)c reconstruc)on, inherently noisy

to Probabilis)c Temporal Inference Maximize T = )me parameters Z = observa)ons X = scene geometry Observa?on Probability Visibility Reasoning Image Date Prior Noisy Building Observa)ons Circa 1910 Undated Uncertain Dates 13

P(T) Image Date Prior Date Sources: EXIF tags database annota)ons Undated: Otherwise: Uniform Historical dates o\en uncertain Es)mated Date Uncertainty May 1970 Undated Circa 1910 14

Observa)on Probability Model Time Parameters Hypothesized Geometry Known Binary variable: Was object i observed in image j? X only Viewability: Is object i within the field of view of camera j? T only a t b Existence: Did object i exist at the )me image j was captured? X & T Occlusion: Is object i occluded by some other object(s) in image j? 15

Op)mizing Temporal Parameters Markov Chain Monte Carlo (MCMC) Sampling Propose to move an image date Analy)cally solve building date intervals Evaluate P(T Z,X) Accept or reject move 1941 Image # 1964 1971 1930 Time 2010 16

Op)mizing Temporal Parameters Markov Chain Monte Carlo (MCMC) Sampling Propose to move an image date Analy)cally solve building date intervals Evaluate P(T Z,X) Accept or reject move 1941 Image # 1977 1971 1930 Time 2010 17

Op)mizing Temporal Parameters Markov Chain Monte Carlo (MCMC) Sampling Propose to move an image date Analy)cally solve building date intervals Evaluate P(T Z,X) Accept or reject move 1941 Image # 1977 1968 1930 Time 2010 18

Op)mizing Temporal Parameters Markov Chain Monte Carlo (MCMC) Sampling Propose to move an image date Analy)cally solve building date intervals Evaluate P(T Z,X) Accept or reject move 80,000 samples = 1.3 hours for scene with 100 images 1941 Image # 1977 1968 1930 Time 2010 19

Results: Full Temporal Op)miza)on Synthe)c Scene 100 images, 30 buildings, 80 years 1/3 known date, 1/3 circa, 1/3 unknown Ini)al RMS Error: 19.31 years RMS Error of Our Solu)on: 2.87 years Image # Ground Truth MCMC Samples 1930 Time 2010 20

Results: Full Temporal Op)miza)on Downtown Atlanta (102 Images) Image # Given Date Estimates MCMC Samples Building Date Intervals 1956 Time 1975 Image Dates 21

Results: Full Temporal Op)miza)on Downtown Atlanta Original Date Label : Undated Image # Solu)on: 1956 1961 1956 Time 1975 22

Results: Leave One Out Image Da)ng Lower Manhaban Error < 5 years for 48% images P(T Z,X) 23

Results: Building Date Intervals 24

Conclusions and Future Work Automa)c, probabilis)c temporal inference method Results for synthe)c scene and 2 challenging real data sets Future Work: Feature correspondence across )me challenging Find more data, densely sampled in space and )me Design )me invariant features 25

Thank you!