Robot Vision SS 2007 Matthias Rüther 1 710.088 ROBOT VISION 2VO 1KU Matthias Rüther.
ROBOT VISION Lesson 1a: Structured Light 3D Reconstruction Matthias Rüther, Christian Reinbacher
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Transcript of ROBOT VISION Lesson 1a: Structured Light 3D Reconstruction Matthias Rüther, Christian Reinbacher
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Robot Vision SS 2013 Matthias Rüther 1
ROBOT VISION Lesson 1a: Structured Light 3D Reconstruction
Matthias Rüther, Christian Reinbacher
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Robot Vision SS 2013 Matthias Rüther 2
Structured Light Methods
Goal: Robust 3D Reconstruction through triangulation
Project artificial pattern on the object
Pattern alleviates the correspondence problem
Variants:– Laser Pattern (point, line)
– Structured projector pattern (several lines, pattern sequence)
– Random projector pattern
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Robot Vision SS 2013 Matthias Rüther 3
Structured Light Range Finder
1. Sender (projects plane)2. Receiver (CCD Camera)
X- directionGeometry Z- direction Sensor image
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Robot Vision SS 2013 Matthias Rüther 4
1 plane -> 1 object profile
Object motion by conveyor band:=> synchronization: measure distance along conveyor=> y-accuracy determined by distance measurement
Scanning Units (e.g.: rotating mirror) are rare (accurate measurement of mirror motion is hard, small inaccuracy there -> large inaccuracy in geometry
Move the sensor: e.g. railways: sensor in wagon coupled to speed measurement
To get a 3D profile:• Move the object• Scanning Unit for projected plane• Move the Sensor
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Robot Vision SS 2013 Matthias Rüther 5
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Robot Vision SS 2013 Matthias Rüther 6
Commercially Available
Person Scanners
Cultural Heritage
Rapid Prototyping
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Robot Vision SS 2013 Matthias Rüther 7
Problems of Laser Profile
Occlusions:
Object points need to be seen from Laser and Camera viewpoint
Sharpness and Contrast:
Both camera and laser need to be in focus
Speckle noise:
Laser always shows “speckle noise”, caused by interference of coherent light.
-> where is the center of the stripe?
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Robot Vision SS 2013 Matthias Rüther 8
Multiple Sheets of Light
Project multiple Laser planes simultaneously to reduce measurement time.
Problem:Separation of stripes in the image
Application:Smoothness check of flat surfaces
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Robot Vision SS 2013 Matthias Rüther 9
Pattern projection
CameraCamera: IMAG
CCD,
Res:750x590, f:16
mm
ProjectorProjector: Liquid Crystal Display (LCD 640), f: 200mm, Distance to object plane: 120cm
Projected light stripes
Range Image
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Robot Vision SS 2013 Matthias Rüther 10
Projector
Lamp
Lens system
LCD - Shutter
Pattern structure
Example
Focusing lens (e.g.: 150mm)
Line projector (e.g.: LCD-640)
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Robot Vision SS 2013 Matthias Rüther 11
Depth decoding
Project Temporal sequence of n binary masks. At each pixel, the temporal sequence of intensities (I1, …, In) gives a binary number which denoted the corresponding projector column.
Project Acquire Decode Triangulate
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Robot Vision SS 2013 Matthias Rüther 12
Coded Light + Phase Shift
Binary code is limited to pixel accuracy (or less).
Increase accuracy to sub-pixel by projecting sine wave after code and measuring phase shift between projected and captured pattern. Decode phase from four samples of sine period, shifted by pi/2.
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Robot Vision SS 2013 Matthias Rüther 13
Coded Light + Phase Shift
Increase accuracy to sub-pixel by projecting sine wave after code and measuring phase shift between projected and captured pattern. Decode phase from four samples of sine period, shifted by pi/2.
Image column (x)
code
Image column (x)
phase +
0
2
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Robot Vision SS 2013 Matthias Rüther 14
Other Coding Methods Possible
Joaquim Salvi,
Pattern codification strategies in structured light systems
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Robot Vision SS 2013 Matthias Rüther 15
The Kinect Working Principle
Triangulation based depth sensor
Static pattern projection
Heavy exploitation of redundancy
Extremely robust/conservative depth maps
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Robot Vision SS 2013 Matthias Rüther 16
The Sensor System
IR Camera: CMOS, rolling shutter, 1.3MP, ½“, 10bit
RGB Camera: CMOS, rolling shutter, 1.3MP, 1/4“, 10bit
Accelerometer
IR Bandpass
IR Lens: F~6mm FOV~55°
RGB Lens: F~2.9mm, FOV~65°
Laser 830nm, 60mW class 3B without optics, 1 with optics, no amplitude modulation
Diffractive Optical Element (DOE)
Peltier ElementTemperature Stabilization
Microphone Array Tilt AxisStereo Processor
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Robot Vision SS 2013 Matthias Rüther 17
The Sensor System
Tx ~75mm
DOF 0.5m – 8m
FOV ~55°
Res. 640x480 (at most)
Internal max 1280x1024
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Robot Vision SS 2013 Matthias Rüther 18
The Projection Pattern
IR Laser and Diffractive Optical Element create interference pattern
Pattern is static and identical for all Kinects