To the Graduate Council: I am submitting herewith a thesis written by ...

Chapter 3: Data Collection and Modeling 27replacing one of the cameras by a moving light source (preferably a laser light source).This technique is called active triangulation where a pattern of light (energy) isprojected on the scene and is detected to obtain range measurements. Time of flightrange finders determine range by measuring the time required for a signal to travel,reflect and return. Holographic interferometry uses split beam interference to producean image which when processed further, yields the range image. A moiré interferencepattern is created when two gratings with regularly spaced patterns are superimposedon each other. “Moiré” sensors project such gratings onto surfaces, and measure thephase differences of the observed interference pattern. Distance hence becomes afunction of such phase differences. Focusing and defocusing have also been used toderive range information. These methods infer range from two or more images of thesame scene, acquired under varying focus settings. For example, shape from focussensors vary the focus of a motorized lens continuously, and measure the amount ofblur for each focus value. Once the best focused image is determined, a model linkingfocus values and distance is used to approximate distance. The decision model makesuse of the law of thin lenses and computes range based on the focal length of thecamera and the image plane distance from the lens’ center. While triangulationmethods and time of flight methods have been extensively used for computer visiontasks, methods based on holography, focusing and diffraction are sidelined because oftheir fundamental performance limitations and their inability to meet real-timeimaging requirements of speed and accuracy. We direct the reader to [Besl, 1988] and[Trucco and Verri, 1998] for further reading on range image acquisition andprocessing.We concentrate on triangulation-based range sensors. The main reason behind thischoice is that such sensors are based on intensity cameras, giving us a chance toexploit the concepts that we know on intensity imaging. They also give accurate 3Dcoordinate maps and are easy to understand and build for real-time imaging.3.1.2 Range Sensing Using the IVP Range ScannerThe IVP RANGER system as shown in Figure 3.1 consists of two differentsubsystems; the Smart Camera and the PC Interface. Each Smart Camera contains aSmart Vision sensor, a control processor (Intel 386) and an IVP HSSI (High speedserial interface). The Smart Camera is connected to the system PC via a COM port andan HSSI Interface on a PCI board called the SC adapter. The IVP Ranger isimplemented on the MAPP2200 (MAPP stands for Matrix Array Picture Processor),MAPP 2500 and LAPP1530 (Linear Array Picture Processor) Smart Vision Sensorsfrom the IVP. The total integration of the sensor, A/D converter and the processor onthe same parallel architecture allows image processing at a very high speed. The SmartCamera acquires the range profiles autonomously and outputs the profiles to the hostvia the HSSI interface. The host PC can then manipulate these profiles.