Geographical Information Systems & Location-based Augmented Reality A Review of Techniques, Challenges, and Possibilities Johnny Luce Design Director and co-founder, augzoo LLC.
Today’s Agenda Define Augmented Reality (AR), with emphasis on location-based AR Describe various techniques used to achieve location-based AR Look at considerations for creating and storing content for location-based AR Explore user experience and possible use cases location-based AR
Marker required to activate Marker-based Augmented Reality Augmentation anchored to marker Markers: Image or QR code Easiest form of augmented reality Affected by lighting conditions Strict image requirements
Markerless Augmented Reality Simultaneous Localization and Mapping (SLAM) Points used to calculate distance and angles Uses Computer Vision to align content to surfaces Computationally intense Affected by lighting conditions Error prone
Markerless Augmented Reality Simultaneous Localization and Mapping (SLAM) Points used to calculate distance and angles Uses Computer Vision to align content to surfaces Computationally intense Affected by lighting conditions Error prone
Location-based Augmented Reality Provides full 360° experiences Most computationally intense Uses GPS + SLAM plus + metadata Can be independent of lighting Very error prone
Pose Measured in Quaternions Difficult to measure accurately Roll, Pitch, and Yaw of the device Computationally intense Most important for believable 3D environments
Motion Tracking Tracks unique points over time Points used to calculate angle and distance Computer Vision technique Computationally intense Affected by lighting conditions
Collision Decection Adds depth and realism Can be very hard to calculate The computational problem of detecting the intersection of two or more objects
Sensor Fusion Goal Hardware Data Location / Position Global positioning System, Wifi, RFID GIS and CAD files Elevation and Altitude Barometer, Wifi, RFID Markers, GIS and CAD files Pose / Heading Magnetometer, Camera, Infrared, Gyroscope, Accelerometer Markers, GIS and CAD files Occlusion and Collision Camera,Infrared GIS and CAD files The process of merging data from multiple sensors such that to reduce the amount of uncertainty.
Data: Raster Stores elevation and or color values Each Pixel represents area, or resolution Images: GeoTIFF and MrSID, et al. Requires lots of disk space
Data: Vector Points are defined by X,Y or Latitude, Longitude Points can be ordered as lines Stored in database or file: .KML. .SVG, .JSON Lines can be closed to form areas Good for features and locations Metadata to define features
Data: Mesh Often has images for color: dtx, png, tiff... Cartesian position, rotation, and scale Hand-crafted. Many formats: .obj, fbx, kmz... Provide high quality content Expensive and time consuming to produce Computationally intense
User Experience Don’t do AR just because it is novel. Use appropriately Make tasks simple, clear, meaningful Environmental and spatial interactions are not always intuitive
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