Range imaging

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Range imaging is the name for a collection of techniques which are used to produce a 2D image showing the distance to points in a scene from a specific point, normally associated with some type of sensor device.

The resulting image, the range image, has pixel values which correspond to the distance, e.g., brighter values mean shorter distance, or vice versa. If the sensor which is used for produce the range image is properly calibrated, the pixel values can be given directly in physical units such as meters.

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[edit] Different types of range cameras

The sensor device which is used for producing the range image is sometimes referred to as a range camera. Range cameras can operate according to a number of different techniques, some of which are presented here.

[edit] Stereo triangulation

A stereo camera system can be used for determining the depth to points in the scene, for example, from the center point of the line between their focal points. In order to solve the depth measurement problem using a stereo camera system, it is necessary to first find corresponding points in the different images. Solving the correspondence problem is one of the main problem when using this type of technique. For instance, it is difficult to solve the correspondence problem for image points which lie inside regions of homogeneous intensity or color. As a consequence, range imaging based on stereo triangulation can usually produce reliable depth estimates only for a subset of all points visible in the multiple cameras. The correspondence problem is minimized in a plenoptic camera design, though depth resolution is limited by the size of the aperture, making it better suited for close-range applications.[1]

The advantage of this technique is that the measurement is more or less passive; it does not require special conditions in terms of scene illumination. The other techniques mentioned here do not have to solve the correspondence problem but are instead dependent on particular scene illumination conditions.

[edit] Sheet of light triangulation

If the scene is illuminated with a sheet of light this creates a reflected line as seen from the light source. From any point out of the plane of the sheet, the line will typically appear as a curve, the exact shape of which depends both on the distance between the observer and the light source and the distance between the light source and the reflected points. By observing the reflected sheet of light using a camera (often a high resolution camera) and knowing the positions and orientations of both camera and light source, it is possible to determine the distances between the reflected points and the light source or camera.

By moving either the light source (and normally also the camera) or the scene in front of the camera, a sequence of depth profiles of the scene can be generated. These can be represented as a 2D range image.

[edit] Structured light

By illuminating the scene with a specially designed light pattern, structured light, depth can be determined using only a single image of the reflected light. The structured light can be in the form of horizontal and vertical lines, points, or checker board patterns.

[edit] Time-of-flight

The depth can also be measured using a standard time-of-flight techniques, more of less similar to a radar, where a light pulse is used instead of an RF pulse. For example, a scanning laser, such as a rotating laser head, can be used to obtain a depth profile for points which lie in the scanning plane. This approach also produce a type of range image, similar to a radar image.

[edit] Interferometry

By illuminating points with coherent light and measuring the phase shift of the reflected light relative to the light source it is possible to determine depth, at least up to modulo the wavelength of the light. Under the assumption that the true range image is a more or less continuous function of the image coordinates, the correct depth can be obtained using a technique called phase-unwrapping.

[edit] See also

[edit] References

  1. ^ Single Lens Stereo with a Plenoptic Camera, Adelson, E. H., and Wang J. Y. A., IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2): 99-106 (1992).
  • Bernd Jähne (1997). Practical Handbook on Image Processing for Scientific Applications. CRC Press. ISBN 0-8493-8906-2. 
  • Linda G. Shapiro and George C. Stockman (2001). Computer Vision. Prentice Hall. ISBN 0-13-030796-3. 
  • David A. Forsyth and Jean Ponce (2003). Computer Vision, A Modern Approach. Prentice Hall. ISBN 0-12-379777-2.