Z-Tiles: Building Blocks for Modular, Pressure-Sensing Floorspaces Bruce Richardson, Krispin Leydon, Mikael Fernström, Joseph A. Paradiso

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Presentation transcript:

Z-Tiles: Building Blocks for Modular, Pressure-Sensing Floorspaces Bruce Richardson, Krispin Leydon, Mikael Fernström, Joseph A. Paradiso

Introduction New Pressure- Sensitive Floorspace Successor to Litefoot (1998) & Magic Carpet (1997) Paradiso et al. (1997) The Magic Carpet: Physical Sensing for Immersive Environments. CHI97 Griffith and Fernstrom (1998) LiteFoot: A Floor Space for Recording Dance and Controlling Media. ICMC98.

Authors Bruce Richardson Interaction Design Centre, UL. Krispin Leydon Interaction Design Centre, UL. Mikael Fernström Interaction Design Centre, UL. Joe Paradiso MIT Media Lab, Boston

Requirement Scalable => Modular and interchangable

Requirement Managable => Self-organising and reconfigurable

Requirement Real-Time => Fast scanning and fast output Scan at 100 Hz Low latency data routing Minimal network overhead

Sensor Units

Z-Tile Circuitry

Z-Tile Architecture

Floor Prototype

Data Bottleneck Many wires vs. One wire Bottleneck at connection point

Options 1. Output only changed pressure readings 2. Group similar pressure readings

Options 1. Output only changed pressure readings 2. Group similar pressure readings

Blob Matching

Considerations 100 pressure scans/sec 10ms maximum computation time Minimum number of parameters Accurate blob matching Trade off Close fit vs Fewer parameters

Ellipse Matching Circles: Loose fit, few parameters Polygons: Tight fit, many parameters

Ellipses Ellipses - good compromise

Simple Matching

Average -> Centre

Axes -> Bounding Box

Resultant Ellipse

Results Pressures distilled to blobs 5 parameters per blob Implemented on a microcontroller >800 scans processed per second Rate achieved at 1/10 speed

Evaluation Processing time to spare Difficulty with diagonal blobs Therefore, look for better match

Angled Ellipses Pressure ReadingsWe have We want

General Method Determine centre as before Locate 2 most distant points Set this as major axis

General Method contd Rotate points so axis is horizontal Use bounding box to determine major and minor axes lengths

Results Implemented on microcontroller Integer-only calculations Lookups for rotations Computation time 1- 2ms

Summary Blob detection to reduce data 2 ellipse-matching algorithms Run time on hardware: <2ms

Future Work Integrate blob detection algorithm into tile software Detect blobs across tiles

Questions?