Surveying by motion tracking: Surveying by motion tracking: modelling 3D subterranean modelling 3D subterranean

landscape from video imagerylandscape from video imagery

Anna Mason, David Mountain and Jonathan RaperAnna Mason, David Mountain and Jonathan Raper

Study AreasStudy Areas

1. Requirements

2. Equipment Tests

3. Field Work

Conditions a caver might experience…Dark Wet

ConfinedFoggy

Dirty

Camera Tracking and Line SurveyingCamera Tracking and Line Surveying

Records: 1. Cave passage dimensions 2. 3D shape for vertical and

horizontal transects3. Reliable visual reference

Bullet camera

Line Survey

Records:1. Absolute distance, bearing

and inclination 2. Vertical and horizontal

dimensions3. Field sketches of shape

Camera tracking with 2D3’s Boujou4Camera tracking with 2D3’s Boujou4

Calculates optimal estimates of camera rotation and Calculates optimal estimates of camera rotation and movement in relation to objects as they are tracked movement in relation to objects as they are tracked throughout an image sequencethroughout an image sequence

Offers:Offers:

1.1. Automatic tracking or interactive tracking Automatic tracking or interactive tracking

2.2. Tracking with environmental markers or without Tracking with environmental markers or without

Cluster of 3D points on a marker

Data captured using bullet camera & Data captured using bullet camera & Boujou4,Boujou4,

Chislehurst CavesChislehurst Cavesa)

c)

User defined coordinate plane

Gap indicating a passage junction

Bend caused by correction of lens distortion

b)

2D Feature Tracking

2D view

3D view

Smooth curved surface

Camera tracking might not always be Camera tracking might not always be

effectiveeffective

If there are few points for a corner If there are few points for a corner detection algorithm to detectdetection algorithm to detect

Could use: Scene manipulation before filming Interactive feature tracking eg.

POIs, survey data, CAD model Camera information Colour correction of imagery – not

recommended, but may make difficult imagery useable

How can you tell?How can you tell?

Virtual camera positions Virtual camera positions do not reflect the real do not reflect the real world camera’s true world camera’s true direction or path travelleddirection or path travelled

Noisy camera pathNoisy camera path High reprojection errorsHigh reprojection errors

Not good

Spikes

Cameras in odd places

Noisy camera path

Camera tracking using Boujou4Camera tracking using Boujou4

c)

Camera path

Last frame

Camera path follows the direction and path the real world camera travelled. Camera path noise realistically reflects the terrain

Start point

First Frame

3D Polyface Meshes3D Polyface Meshes

a) 3D view of a mesh in Boujou4.

b) The same mesh mapped to the line survey results (red and blue lines) in GIS.

3D modelling, 3D modelling, Chislehurst CavesChislehurst Caves

ResultsResults

Scale differences range 0.2cm to approximately 20.3cm.

Mean of four measurements was 13.3cm.

Within 10-15% of the exact Within 10-15% of the exact measurements suggested measurements suggested as acceptable when as acceptable when sketching cave passage sketching cave passage shape (Day, 2002). shape (Day, 2002).

Mine passage connecting Upwood Shaft to Highclere Shaft at Chislehurst, Bromley

HighclereAir Shaft

UpwoodAir Shaft

© Crown Copyright Ordnance Survey 2008

0 0.06 0.12 0.18KM

Cave survey sketches Cave survey sketches Vs 3D meshesVs 3D meshes

Club Rooms, Air Shafts, Gaping Gill, Club Rooms, Air Shafts, Gaping Gill, Chislehurst Chislehurst North YorkshireChislehurst Chislehurst North Yorkshire

Typical star shaped phreatic cave morphology

FieldSketches

Vertical Cross

Sections

Shallow half ellipse Arched ellipse

Study AreasStudy Areas

1. Requirements

2. Testing Equipment3. Field Work

Camera Tracking and Line SurveyingCamera Tracking and Line Surveying

Records 3D shape for vertical and horizontal transects Reliable visual reference

Bullet camera

Line Survey

Records absolute distance, bearing and inclination measurements

Accurate representation of shapeAccurate representation of shapeAccurate measurement of dimensions Accurate measurement of dimensions /volume/volume Accurate measurement of relative scaleAccurate measurement of relative scale

Benefits to GIS and CavingBenefits to GIS and Caving New source of 3D data New source of 3D data Low cost accurate surveying Low cost accurate surveying

technique compatible with technique compatible with GIS, CAD Animation, AR, VR and Visualisation software

Camera tracking research, Camera tracking research, eg. eg.

Exploration rovers in hostile environments

Robotic surgery Navigation Animation Virtual TV

Further StudiesFurther Studies Comparison with laser Comparison with laser

ranging and finding ranging and finding equipmentequipment

Compatibility with cave Compatibility with cave surveying software surveying software

Test more equipment, eg. Test more equipment, eg. infraredinfrared

Limitations Limitations

Image QualityImage Quality

Camera lens and light must be Camera lens and light must be tailored to fit the scene:tailored to fit the scene:

6mm fixed lens and 6degrees

Scale must be defined by the Scale must be defined by the useruser

Use h or d or a marker

Optimal camera moves create Optimal camera moves create parallax parallax

Dolly rather than pan

Tracking cornersTracking corners Begin/end with survey

stations

Price ?Price ?

ReferencesReferences DAY, A.J., (2002) Cave Surveying – A DAY, A.J., (2002) Cave Surveying – A

guide to the equipment, techniques guide to the equipment, techniques and methodology of the BCRA and methodology of the BCRA system, Cave Studies Series No.11. system, Cave Studies Series No.11. Buxton, UK: British Caving Research Buxton, UK: British Caving Research Association (BCRA)Association (BCRA)

DOBBERT, T. (2005) Matchmoving: DOBBERT, T. (2005) Matchmoving: The invisible art of camera tracking, The invisible art of camera tracking, Sybex Inc., Alameda, CASybex Inc., Alameda, CA

HARTLEY, R. and ZISSERMAN, A. HARTLEY, R. and ZISSERMAN, A. (2004) Multiple View Geometry in (2004) Multiple View Geometry in Computer Vision (Second Edition), Computer Vision (Second Edition), Cambridge, UK: Cambridge Cambridge, UK: Cambridge University PressUniversity Press

Thank youThank you

AcknowledgementsAcknowledgements

BCRA, 2D3, David Mountain and Jonathan Raper (City University), BCRA, 2D3, David Mountain and Jonathan Raper (City University), John FarrerJohn Farrer (Peak Cavern), Terry Hunt (Chislehurst Caves), Craven Peak Cavern), Terry Hunt (Chislehurst Caves), Craven Potholing Club (Peak Cavern), Adam Evans, Rod Legear, Paul Potholing Club (Peak Cavern), Adam Evans, Rod Legear, Paul ChambersChambers