SmartBoxes for Interactive Urban Reconstruction Liangliang Nan 1, Andrei Sharf 1, Hao Zhang 2, Daniel Cohen-Or 3, Baoquan Chen 1 1 Shenzhen Institutes.

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SmartBoxes for Interactive Urban Reconstruction

Presentation transcript:

SmartBoxes for Interactive Urban Reconstruction Liangliang Nan 1, Andrei Sharf 1, Hao Zhang 2, Daniel Cohen-Or 3, Baoquan Chen 1 1 Shenzhen Institutes of Advanced Technology (SIAT), China 2 Simon Fraser University, Canada 3 University of Tel Aviv, Israel

Virtual BerlinVirtual Philadelphia 3D Cities

Acquisition of Urban Environments Cameras/videos Remote Sensing Systems 3D Digital City Auto-mounted LIDAR Airborne LIDAR

3D LiDAR scanner Street-level 60km/h 180 pitch [ m] range 100K points/second 5cm XY accuracy

Outdoor Urban Scanning

Imperfect Scans - Occlusions Point cloud contains holes due to various occlusions (shadows)

Imperfect Scans – Angle & Range Oblique scanning angle Laser energy attenuation on range

Urban Building Characteristics Repetitions, intra symmetry and regularity Axis-aligned basic primitives Dominant planes

SmartBoxes Box-up and Smart!

SmartBoxes Box prior shape fitting Smart context awareness Both Context Data

Live Demo

9

Related Work Procedural modeling of buildings and facades [Wonka2003;Muller2007] Automatic 3D reconstruction from 2D images [Zisserman2002;Xiao2009;Furukawa2009] Interactive modeling of architectural structures [Debevec1996;Schindler2003; Xiao2008;Sinha2008;Jiang2009] Primitive fitting to data [Gal2007; Schnabel 2009]

Preprocessing Automatic detection of planes and edges assuming dominant orthogonal axes –RANSAC planes –Line sweep edges

Snapping a Box 2D rubber band ROI Collect planes, edges, corners Find the best fitting box using data fitting force D(B,P)

Data fitting D(B,P) snap FacetEdge Data fitting force Data quality ( Confidence + Density ) Distance

Grouping Simple SmartBox Compound SmartBox Align to remove gaps and intersections –cluster and align close to co-linear edges

Drag-and-drop context C(B i-1, B i ) The context of B i B i-1 B i-2 B i-3 IntervalAlignmentScale Context BiBi

Drag-and-drop context C(B i-1, B i ) The context of B i –Interval term B i-1 B i-2 B i-3 BiBi

Drag-and-drop context C(B i-1, B i ) The context of B i –Alignment term BiBi B i-1 B i-2 B i-3

BiBi Drag-and-drop context C(B i-1, B i ) The context of B i –Scale term BiBi B i-1 B i-2 B i-3

Discrete objective minimization Find linear transformation T(excluding rotation) to minimize: Data fitting forceContextual force

Discrete objective minimization B i-1 B i-2 B i-3 Find linear transformation T(excluding rotation) to minimize: Data fitting forceContextual force

Balance between two forces

Emerging city of Shenzhen, China

Results: textured buildings

Manchester Civil Justice Centre (Manchester, UK) Habitat 67 (Montreal, Canada) The Crooked House (Sopot, Poland)

(Thank You)!