There are many di erent methods for acquiring shape data. Essentially, each method uses some mechanism or phenomenon for interacting with the surface or volume of the object of interest. There are non-contact methods, where light, sound or magnetic elds are used, while in others the surface is touched by using mechanical probes at the end of an arm (tactile methods). In each case an appropriate analysis must be performed to determine positions of points on the object’s surface from physical readings obtained. For example, in laser range fi nders, the time-of- ight is used to determine the distance traveled, and in image analysis the relative locations of landmarks in multiple images are related to position. Each method has strengths and weaknesses which require that the data acquisition system be carefully selected for the shape capture functionality desired. This section will discuss the principles of various methods and the next section will address the practical problems of acquiring data. Jarvis’ paper is a very good survey on the dif erent methods of data acquisition. Optical methods of shape capture are probably the broadest and most popular with relatively fast acquisition rates. There are ve important categories of optical methods we discuss here: triangulation, ranging, interferometry, structured lighting and image analysis. Triangulation is a method which uses location and angles between light sources and photo sensing devices to deduce position. A high energy light source is focused
and projected at a prespeci ed angle at the surface of interest. A photosensitive device, usually a video camera, senses the reaction of the surface and then by using geometric triangulation from the known angle and distances, the position of a surface point relative to a reference plane can be calculated. The light source and the camera can be mounted on a traveling platform which then produces multiple scans of the surface. These scans are therefore relative measurements of the surface of interest. Various di erent high energy light sources are used, but lasers are the most common. Triangulation can acquire data at very fast rates. The accuracy is determined by the resolution of the photo sensitive device and the distance between the surface and the scanner. Motavalli and Bidanda present a reverse engineering strategy using laser triangulation. Moss et al present a detailed discussion of a classic laser triangulation system used to capture shape data from facial surfaces. A discussion of accuracy and applications is also included. The use of laser
triangulation on a coordinate measuring machine is presented by Modjarrad. These references give a broad survey of methods, approaches to and limitations of triangulation. Ranging methods measure distances by sensing time-of-light of light beams; practical methods are usually based on lasers and pulsed beams. Interferometry methods measure distances in terms of wavelengths using interference patterns. This can be a very accurate method of measurement since visible light has a wavelength of the order of hundreds of nanometers, while most reverse engineering applications distances are in the centimeter to meter range. In principle, other parts of the electromagnetic spectrum could also be used. In practice, a high energy light source is used to provide both a beam of monochromatic light to probe the object and a reference beam for comparison with the reflected light. Moring et al describe a range nder based on time-of- light calculations. The article presents some information on accuracy and performance. Jarvis presents an in-depth article on time-of- light range nders giving detailed results and analysis.
Structured lighting involves projecting patterns of light upon a surface of interest and capturing an image of the resulting pattern as reflected by the surface. The image must then be analyzed to determine coordinates of data points on the surface. A popular method of structured lighting is shadow Moir e, where an interference pattern is projected onto a surface producing lighted contour lines. These contour lines are captured in an image and are analyzed to determine distances between the lines. This distance is proportional to the height of the surface at the point of interest and so the coordinates of surface points can be deduced. Structured lighting can acquire large amounts of data with a single image frame, but the analysis to determine positions of data can be rather complex. Will and Pennington use grids projected onto the surface of objects to determine point locations. Wang and Aggarwal use a similar approach but use stripes of light and multiple images. The nal optical shape capture method of interest is image analysis. This is similar to structured lighting methods in that frames are analyzed to determine coordinate data. However, the analysis does not rely on projected patterns. Instead, typically, stereo pairs are used to provide enough information to determine height and coordinate position. This method is often referred to as a passive method since no structured lighting is used. Active methods are distinguished from passive methods in that arti cial light is used in the acquisition of data. Correlation of image pairs and landmarks within the images are big di culties with this method and this is why active methods are preferred. Another image analysis approach deals with lighting models, where an image is compared to a 3-dimensional model. The model is modi ed until the shaded images match the real images of the object of interest. Finally, intensity patterns within images can be used to determine coordinate information. There is a vast amount of literature on stereo imaging, and we just cite four papers that address this technique. Nishihara uses a real-time binocular stereo matching algorithm for making rapid range measurements. Posdamer and Altschuler describe a method for real time measurement of surface data using stereo methods. Also, see Woodham’s work on shape from shading. Finally, a
contribution by Rockwood and Winget in this special issue describes an energy minimization approach of a mesh to match a collection of 2D images. Tactile methods represent another popular approach to shape capture. Tactile methods touch a surface using mechanical arms. Sensing devices in the joints of the arm determine the relative coordinate locations. These methods are mostly limited by the measuring device limitations. For example, a 3-axis milling machine can be tted with a touch probe and used as a tactile measuring system. However, it is
not very e ective for concave surfaces. There are many di erent robotic devices which are used for tactile measurement. These methods are among the most robust (i.e. less noise, more accurate, more repeatable, etc.), but they are also the slowest method for data acquisition. Probably the most popular method is the use of coordinate measuring machines (CMM). These machines can be programmed to follow paths along a surface and collect very accurate, nearly noise-free data. Xiong gives an in depth discussion of measurement and pro le error in tactile measurement. Sahoo and Menq use tactile systems for sensing complex sculptured surfaces. Butler provides a
comparison of tactile methods and their performance. The nal type of data acquisition methods we will examine are acoustic, where sound is reflected from a surface, and magnetic, where a magnetic eld touches the surface. Acoustic methods have been used for decades for distance measuring. Sonar is used extensively for this purpose. Automatic focus cameras often use acoustic methods to determine range. The method is essentially the same as time-of- light, where a sound source is reflected o a surface and then distance between the source and surface is determined knowing the speed of sound. Acoustic interference or noise is often a problem as well as determining focused point locations. Dynamic imaging is used extensively in ultra-sound devices where a transducer can sweep a cross-section through an object to capture material data internal to an object. Magnetic fi eld measurement involves sensing the strength of a magnetic fi eld source. Magnetic touch probes are used which usually sense the location and orientation of a stylus within the eld. A trigger allows the user to only record specfic point data once the stylus is positioned at a point of interest. Magnetic resonance is used in similar applications to ultra-sound when internal material properties are to be measured. MRI (magnetic resonance) activates atoms in the material to be measured and then measures the response. Watanabe uses an ultrasonic sensor for object recognition and Tsujimura et al  place the ultrasonic device on a manipulator. To sum up, all measuring methods must interact with the surface or internal material using some phenomenon, either light, sound, magnetism or physical contact. The speed with which the phenomenon operates as well as the speed of the sensor device determines the speed of the data acquisition. The amount of analysis needed
to compute the measured data and the accuracy are also basically determined by the sensor type selected.