Presentation on theme: "Kawada Industries Inc. has introduced the HRP-2P for Robodex 2002"— Presentation transcript:
1ROBOT 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.
2Structured 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
3Structured Light Range Finder 1. Sender (projects plane)2. Receiver (CCD Camera)Geometry Z- directionX- directionSensor image
41 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
6Commercially Available Person ScannersCultural HeritageRapid Prototyping
7Problems 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?
8Multiple 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
11Project 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
12Coded 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.
13Coded 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)
14Other Coding Methods Possible Joaquim Salvi,Pattern codification strategies in structured light systems
15The Kinect Working Principle Triangulation based depth sensorStatic pattern projectionHeavy exploitation of redundancyExtremely robust/conservative depth maps
16The 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
17The Sensor System Tx ~75mm DOF 0.5m – 8m FOV ~55° Res. 640x480 (at most)Internal max 1280x1024AccelerometerMicrophone ArrayTilt AxisStereo Processor
18The Projection Pattern IR Laser and Diffractive Optical Element create interference pattern Pattern is static and identical for all Kinects