# ROBOT VISION Lesson 1a: Structured Light 3D Reconstruction Matthias Rüther, Christian Reinbacher - PowerPoint PPT Presentation

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ROBOT VISION Lesson 1a: Structured Light 3D Reconstruction Matthias Rüther, Christian Reinbacher. Structured Light Methods. Goal: Robust 3D Reconstruction through triangulation Project artificial pattern on the object Pattern alleviates the correspondence problem Variants:

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ROBOT VISION Lesson 1a: Structured Light 3D Reconstruction Matthias Rüther, Christian Reinbacher

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### 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

### Structured Light Range Finder

1. Sender (projects plane)

Sensor image

Geometry Z- direction

X- direction

1 plane -> 1 object profile

• To get a 3D profile:

• Move the object

• Scanning Unit for projected plane

• Move the Sensor

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

### Commercially Available

Person Scanners

Cultural Heritage

Rapid Prototyping

### 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?

### 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

Pattern projection

Range Image

Projected light stripes

• Camera: IMAG CCD, Res:750x590, f:16 mm

• Projector: Liquid Crystal Display (LCD 640), f: 200mm, Distance to object plane: 120cm

### Projector

Lamp

Lens system

LCD - Shutter

Pattern structure

Line projector (e.g.: LCD-640)

Focusing lens (e.g.: 150mm)

Example

### Depth decoding

Project Temporal sequenceof n binarymasks. Ateachpixel, the temporal sequenceofintensities (I1, …, In) gives a binarynumberwhichdenotedthecorrespondingprojectorcolumn.

Project  Acquire  Decode  Triangulate

### 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.

### 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.

code

Image column (x)

phase

+

2

0

Image column (x)

### Other Coding Methods Possible

Joaquim Salvi,

Pattern codification strategies in structured light systems

### The Kinect Working Principle

• Triangulation based depth sensor

• Static pattern projection

• Heavy exploitation of redundancy

• Extremely robust/conservative depth maps

### The Sensor System

IR Lens:

F~6mm FOV~55°

Diffractive Optical

Element (DOE)

Laser

830nm, 60mW

class 3B without optics, 1 with optics,

no amplitude modulation

IR Bandpass

RGB Lens:

F~2.9mm, FOV~65°

IR Camera:

CMOS, rolling shutter, 1.3MP, ½“, 10bit

RGB Camera:

CMOS, rolling shutter, 1.3MP, 1/4“, 10bit

Peltier Element

Temperature Stabilization

Stereo Processor

Microphone Array

Accelerometer

Tilt Axis

### The Sensor System

• Tx ~75mm

• DOF 0.5m – 8m

• FOV ~55°

• Res. 640x480 (at most)

• Internal max 1280x1024

Stereo Processor

Microphone Array

Accelerometer

Tilt Axis

### The Projection Pattern

IR Laser and Diffractive Optical Element create interference pattern

Pattern is static and identical for all Kinects