Glob3 Mobile: Serving and rendering huge point clouds on mobile - - PowerPoint PPT Presentation

Glob3 Mobile: Serving and rendering huge point clouds on mobile devices and web pages

(aka: Feature Streaming server & Client)

Manuel de la Calle FOSS4G 2015 @mdelacalle mdelacalle@glob3mobile.com

Glob3 Mobile (G3M) is: an open source* API to build native maps applications that runs on any device

(*) github.com/glob3mobile/g3m

Multiplatform

native performance everywhere

2D/3D Maps

Any kind

• f data

Offline / Online

Camera and Models animations

Utilities

Streaming

Rendering and interaction with huge datasets Smooth experience Looking for the best Performance

• Optimize network usage, download only the data

relevant to the current visible area of the map

• Minimize the waiting time to view/interact

○ download the “most significative” features first ○ show the incoming data as soon as it’s available ○ when more detailed data arrives, update the view with more data

Why streaming geo features?

Architecture bird view

Data importation LOD Preprocessing Rendering

Data importation

• Import huge unsorted data into a Quadtree on disk
• No size limit (ok, not really, the disk space is the limit)
• The resulting Quadtree gives the first categorization of the data into “Tiles”
• Produces useful metadata like Bounding Box, Features Count, Density, etc

LOD (Level of Detail) Preprocessing

• produces the intermediate LOD levels
• sort the data in a “stream” friendly format
• most-significative features go first, least-significative go last
• LOD Strategies
• Shape preserving → for LiDAR point-clouds
• Sorting → for point-vector datasets with a clear sorting criteria
• Clustering → for point-vector datasets with all the features are “equals”

LOD Strategies

Shape preserving

• Selection of points where the most-significative are the ones that describe

the general shape of the point-cloud. The shape of the cloud is always preserved (inclusive in the less-resolution levels). Sorting

• The sorting criteria defines which features are the most and least

significative. Clustering

• The intermediate levels are filled with Clustering information that describes

the structure of the full-detailed-levels

LOD 0 LOD 1 LOD 2

Rendering

• download of metadata
• size, covered sector, min/max height, etc
• description of Quadtree nodes
• bounding box
• average point
• LOD Levels
• based on the projected size of the BB, estimate how many LOD levels are

needed

• download the next to the current loaded level
• cancel current download in case it's not more needed

Streaming 7

Demo time!

http://www.mapboo.com

http://point-cloud.glob3mobile.com Google play Apple Store

Glob3 Mobile: Serving and rendering huge point clouds on mobile devices and web pages

(aka: Feature Streaming server & Client)

Manuel de la Calle FOSS4G 2015 @mdelacalle mdelacalle@glob3mobile.com