z-tiles: building blocks for modular, pressure-sensing floorspaces bruce richardson, krispin leydon,...

Z-Tiles: Building Blocksfor Modular,

Pressure-Sensing Floorspaces

Bruce Richardson, Krispin Leydon, Mikael Fernström, Joseph A. Paradiso

http://www.idc.ul.ie/ztiles/

Introduction

• New Pressure-

Sensitive Floorspace

• Successor to

Litefoot (1998) &

Magic Carpet (1997)

Paradiso et al. (1997) The Magic Carpet: Physical Sensing for Immersive Environments. CHI’97Griffith and Fernstrom (1998) LiteFoot: A Floor Space for Recording Dance and Controlling Media. ICMC’98.

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

QuickTime™ and aDV - PAL decompressor

are needed to see this picture.

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 Readings We have We want

General Method

• Determine centre

as before

• Locate 2 most

distant points

• Set this as major

axis

General Method cont’d

• 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?

http://www.idc.ul.ie/

http://www.idc.ul.ie/ztiles/