Presentation on theme: "Kawada Industries Inc. has introduced the HRP-2P for Robodex 2002"— Presentation transcript:
1 ROBOT VISION Lesson 1a: Structured Light 3D Reconstruction Matthias Rüther, Christian Reinbacher Kawada Industries Inc. has introduced the HRP-2P for Robodex 2002. This humanoid appears to be very impressive. It is 154 cm (60") tall, weighs 58kg (127 lbs) and has 30 DOF. Here is a news release. Notice the LACK of a battery pack. Here is a new story about HRP2.
2 Structured Light Methods Goal: Robust 3D Reconstruction through triangulationProject artificial pattern on the objectPattern alleviates the correspondence problemVariants:Laser Pattern (point, line)Structured projector pattern (several lines, pattern sequence)Random projector pattern
3 Structured Light Range Finder 1. Sender (projects plane)2. Receiver (CCD Camera)Geometry Z- directionX- directionSensor image
4 1 plane -> 1 object profile To get a 3D profile:Move the objectScanning Unit for projected planeMove the SensorObject motion by conveyor band:=> synchronization: measure distance along conveyor=> y-accuracy determined by distance measurementScanning Units (e.g.: rotating mirror) are rare (accurate measurement of mirror motion is hard, small inaccuracy there -> large inaccuracy in geometryMove the sensor: e.g. railways: sensor in wagon coupled to speed measurement
6 Commercially Available Person ScannersCultural HeritageRapid Prototyping
7 Problems of Laser Profile Occlusions:Object points need to be seen from Laser and Camera viewpointSharpness and Contrast:Both camera and laser need to be in focusSpeckle noise:Laser always shows “speckle noise”, caused by interference of coherent light.-> where is the center of the stripe?
8 Multiple Sheets of Light Project multiple Laser planes simultaneously to reduce measurement time.Problem:Separation of stripes in the imageApplication:Smoothness check of flat surfaces1) peak at position xo2) left side und right side of the peal using a threshold Vt3) center points
11 Project Acquire Decode Triangulate Depth decodingProject 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
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.
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.codeImage column (x)phase+2Image column (x)
14 Other Coding Methods Possible Joaquim Salvi,Pattern codification strategies in structured light systems
15 The Kinect Working Principle Triangulation based depth sensorStatic pattern projectionHeavy exploitation of redundancyExtremely robust/conservative depth maps
16 The Sensor System IR Lens: F~6mm FOV~55° Diffractive Optical Element (DOE)Laser830nm, 60mWclass 3B without optics, 1 with optics,no amplitude modulationIR BandpassRGB Lens:F~2.9mm, FOV~65°IR Camera:CMOS, rolling shutter, 1.3MP, ½“, 10bitRGB Camera:CMOS, rolling shutter, 1.3MP, 1/4“, 10bitPeltier ElementTemperature StabilizationStereo ProcessorMicrophone ArrayAccelerometerTilt Axis
17 The Sensor System Tx ~75mm DOF 0.5m – 8m FOV ~55° Res. 640x480 (at most)Internal max 1280x1024AccelerometerMicrophone ArrayTilt AxisStereo Processor
18 The Projection Pattern IR Laser and Diffractive Optical Element create interference pattern Pattern is static and identical for all Kinects