Data TypesData Types
• Volumetric DataVolumetric Data– Voxel gridsVoxel grids– OccupancyOccupancy– DensityDensity
• Surface DataSurface Data– Point cloudsPoint clouds– Range images (range maps)Range images (range maps)
Related FieldsRelated Fields
• Computer VisionComputer Vision– Passive range sensingPassive range sensing– Rarely construct complete, accurate Rarely construct complete, accurate
modelsmodels– Application: recognitionApplication: recognition
• MetrologyMetrology– Main goal: absolute accuracyMain goal: absolute accuracy– High precision, provable errors more High precision, provable errors more
important than scanning speed, complete important than scanning speed, complete coveragecoverage
– Applications: industrial inspection, quality Applications: industrial inspection, quality control, as-built modelscontrol, as-built models
Related FieldsRelated Fields
• Computer GraphicsComputer Graphics– Often want complete modelOften want complete model– Low noise, geometrically consistent Low noise, geometrically consistent
model more important than absolute model more important than absolute accuracyaccuracy
– Application: animated CG charactersApplication: animated CG characters
TerminologyTerminology
• Range acquisition, shape acquisition, Range acquisition, shape acquisition, rangefinding, range scanning, 3D rangefinding, range scanning, 3D scanningscanning
• Alignment, registrationAlignment, registration
• Surface reconstruction, 3D scan Surface reconstruction, 3D scan merging, scan integration, surface merging, scan integration, surface extractionextraction
• 3D model acquisition3D model acquisition
Range Acquisition TaxonomyRange Acquisition Taxonomy
RangeRangeacquisitionacquisition
ContactContact
TransmissiveTransmissive
ReflectiveReflectiveNon-opticalNon-optical
OpticalOptical
Industrial CTIndustrial CT
Mechanical Mechanical (CMM, jointed arm)(CMM, jointed arm)
RadarRadar
SonarSonar
UltrasoundUltrasound
MRIMRI
Ultrasonic trackersUltrasonic trackersMagnetic trackersMagnetic trackers
Inertial Inertial (gyroscope, accelerometer)(gyroscope, accelerometer)
Range Acquisition TaxonomyRange Acquisition Taxonomy
Opticalmethods
Passive
Active
Shape from X:stereomotionshadingtexturefocusdefocus
Active variants of passive methodsStereo w. projected textureActive depth from defocusPhotometric stereo
Time of flight
Triangulation
Optical Range Scanning Optical Range Scanning MethodsMethods
• Advantages:Advantages:– Non-contactNon-contact– SafeSafe– Usually inexpensiveUsually inexpensive– Usually fastUsually fast
• Disadvantages:Disadvantages:– Sensitive to transparencySensitive to transparency– Confused by specularity and interreflectionConfused by specularity and interreflection– Texture (helps some methods, hurts Texture (helps some methods, hurts
others)others)
StereoStereo
• Find feature in one image, search Find feature in one image, search along epipole in other image for along epipole in other image for correspondencecorrespondence
StereoStereo
• Advantages:Advantages:– PassivePassive– Cheap hardware (2 cameras)Cheap hardware (2 cameras)– Easy to accommodate motionEasy to accommodate motion– Intuitive analogue to human visionIntuitive analogue to human vision
• Disadvantages:Disadvantages:– Only acquire good data at “features”Only acquire good data at “features”– Sparse, relatively noisy data (correspondence is Sparse, relatively noisy data (correspondence is
hard)hard)– Bad around silhouettesBad around silhouettes– Confused by non-diffuse surfacesConfused by non-diffuse surfaces
• Variant: multibaseline stereo to reduce Variant: multibaseline stereo to reduce ambiguityambiguity
Shape from MotionShape from Motion
• ““Limiting case” of multibaseline Limiting case” of multibaseline stereostereo
• Track a feature in a video sequenceTrack a feature in a video sequence
• For For nn frames and frames and ff features, have features, have22nnff knowns, 6 knowns, 6nn+3+3ff unknowns unknowns
Shape from MotionShape from Motion
• Advantages:Advantages:– Feature tracking easier than Feature tracking easier than
correspondence in far-away viewscorrespondence in far-away views– Mathematically more stable (large Mathematically more stable (large
baseline)baseline)
• Disadvantages:Disadvantages:– Does not accommodate object motionDoes not accommodate object motion– Still problems in areas of low texture, in Still problems in areas of low texture, in
non-diffuse regions, and around silhouettesnon-diffuse regions, and around silhouettes
Shape from ShadingShape from Shading
• Given: image of surface with known, Given: image of surface with known, constant reflectance under known constant reflectance under known point lightpoint light
• Estimate normals, integrate to find Estimate normals, integrate to find surfacesurface
• Problem: ambiguityProblem: ambiguity
Shape from ShadingShape from Shading
• Advantages:Advantages:– Single imageSingle image– No correspondencesNo correspondences– Analogue in human visionAnalogue in human vision
• Disadvantages:Disadvantages:– Mathematically unstableMathematically unstable– Can’t have textureCan’t have texture
• Not really practicalNot really practical– But see photometric stereoBut see photometric stereo
Shape from TextureShape from Texture
• Mathematically similar to shape from Mathematically similar to shape from shading, but uses stretch and shrink of a shading, but uses stretch and shrink of a (regular) texture(regular) texture
Shape from TextureShape from Texture
• Analogue to human visionAnalogue to human vision
• Same disadvantages as shape from Same disadvantages as shape from shadingshading
Shape from Focus and DefocusShape from Focus and Defocus
• Shape from focus: at which focus Shape from focus: at which focus setting is a given image region setting is a given image region sharpest?sharpest?
• Shape from defocus: how out-of-Shape from defocus: how out-of-focus is each image region?focus is each image region?
• Passive versions rarely usedPassive versions rarely used
• Active depth from defocus can beActive depth from defocus can bemade practicalmade practical
Active Optical MethodsActive Optical Methods
• Advantages:Advantages:– Usually can get dense dataUsually can get dense data– Usually much more robust and Usually much more robust and
accurate than passive techniquesaccurate than passive techniques
• Disadvantages:Disadvantages:– Introduces light into scene (distracting, Introduces light into scene (distracting,
etc.)etc.)– Not motivated by human visionNot motivated by human vision
Active Variants of Passive Active Variants of Passive TechniquesTechniques
• Regular stereo with projected textureRegular stereo with projected texture– Provides features for correspondenceProvides features for correspondence
• Active depth from defocusActive depth from defocus– Known pattern helps to estimate Known pattern helps to estimate
defocusdefocus
• Photometric stereoPhotometric stereo– Shape from shading with multiple Shape from shading with multiple
known lightsknown lights
Pulsed Time of FlightPulsed Time of Flight
• Basic idea: send out pulse of light Basic idea: send out pulse of light (usually laser), time how long it takes (usually laser), time how long it takes to returnto return tcr
2
1tcr
2
1
Pulsed Time of FlightPulsed Time of Flight
• Advantages:Advantages:– Large working volume (up to 100 m.)Large working volume (up to 100 m.)
• Disadvantages:Disadvantages:– Not-so-great accuracy (at best ~5 mm.)Not-so-great accuracy (at best ~5 mm.)
• Requires getting timing to ~30 picosecondsRequires getting timing to ~30 picoseconds• Does not scale with working volumeDoes not scale with working volume
• Often used for scanning buildings, Often used for scanning buildings, rooms, archeological sites, etc.rooms, archeological sites, etc.
AM Modulation Time of FlightAM Modulation Time of Flight
• Modulate a laser at frequencyModulate a laser at frequencym m ,, it it
returns with a phase shift returns with a phase shift
• Note the ambiguity in the measured Note the ambiguity in the measured phase!phase! Range ambiguity of Range ambiguity of 11//22mmnn
2
2
2
1 n
ν
cr
m
2
2
2
1 n
ν
cr
m
AM Modulation Time of FlightAM Modulation Time of Flight
• Accuracy / working volume tradeoffAccuracy / working volume tradeoff(e.g., noise ~ (e.g., noise ~ 11//500 500 working volume)working volume)
• In practice, often used for room-sized In practice, often used for room-sized environments (cheaper, more environments (cheaper, more accurate than pulsed time of flight)accurate than pulsed time of flight)
Triangulation: Moving theTriangulation: Moving theCamera and IlluminationCamera and Illumination
• Moving independently leads to Moving independently leads to problems with focus, resolutionproblems with focus, resolution
• Most scanners mount camera and Most scanners mount camera and light source rigidly, move them as a light source rigidly, move them as a unitunit
Triangulation: Extending to 3DTriangulation: Extending to 3D
• Possibility #1: add another mirror (flying Possibility #1: add another mirror (flying spot)spot)
• Possibility #2: project a stripe, not a dotPossibility #2: project a stripe, not a dot
ObjectObject
LaserLaser
CameraCameraCameraCamera
Triangulation Scanner IssuesTriangulation Scanner Issues
• Accuracy proportional to working volume Accuracy proportional to working volume (typical is ~1000:1)(typical is ~1000:1)
• Scales down to small working vol. (e.g. 5 Scales down to small working vol. (e.g. 5 cm. working volume, 50 cm. working volume, 50 m. accuracy)m. accuracy)
• Does not scale up (baseline too large…)Does not scale up (baseline too large…)
• Two-line-of-sight problem (shadowing from Two-line-of-sight problem (shadowing from either camera or laser)either camera or laser)
• Triangulation angle: non-uniform resolution Triangulation angle: non-uniform resolution if too small, shadowing if too big (useful if too small, shadowing if too big (useful range: 15range: 15-30-30))
Triangulation Scanner IssuesTriangulation Scanner Issues
• Material properties (dark, specular)Material properties (dark, specular)
• Subsurface scatteringSubsurface scattering
• Laser speckleLaser speckle
• Edge curlEdge curl
• Texture embossingTexture embossing
Multi-Stripe TriangulationMulti-Stripe Triangulation
• To go faster, project multiple stripesTo go faster, project multiple stripes
• But which stripe is which?But which stripe is which?
• Answer #1: assume surface Answer #1: assume surface continuitycontinuity
Multi-Stripe TriangulationMulti-Stripe Triangulation
• To go faster, project multiple stripesTo go faster, project multiple stripes
• But which stripe is which?But which stripe is which?
• Answer #2: colored stripes (or dots)Answer #2: colored stripes (or dots)
Multi-Stripe TriangulationMulti-Stripe Triangulation
• To go faster, project multiple stripesTo go faster, project multiple stripes
• But which stripe is which?But which stripe is which?
• Answer #3: time-coded stripesAnswer #3: time-coded stripes
Time-Coded Light PatternsTime-Coded Light Patterns
• Assign each stripe a unique illumination Assign each stripe a unique illumination codecodeover time [Posdamer 82]over time [Posdamer 82]
SpaceSpace
TimeTime
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