Paper
26 January 2006 Formation of stereoscopic image pairs from a sequence of frames
Author Affiliations +
Proceedings Volume 6056, Three-Dimensional Image Capture and Applications VII; 605609 (2006) https://doi.org/10.1117/12.641994
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
Transverse relative motion between an object and an observer, as well as specific rotations of that object provide a means of forming stereoscopic pairs from a sequence of 2D images of the object. An algorithm that transforms consecutive frames in this sequence in a manner that results in a series of optimally viewable stereoscopic pairs has been developed. This operation is done without any human intervention, and without any a priori knowledge or control of the subject's motion. Orientations of the stereoscopic axis found in the sequence will generally not be aligned with that of the viewer, and may change throughout the sequence. In order to perceive the stereo effect to an optimal degree, the frames must be rotated to bring this axis into alignment with that of the viewer. Current techniques for this purpose assume precise knowledge of the subject's orientation and angular velocity, or require subjective human intervention. The algorithm is based upon vector algebra of a displacement field derived from correlations made between a "reference" frame and its corresponding "comparison" frame. Possible applications of this technique include ground-based imaging of orbiting satellites and space probe imagery, and could result in new mapping techniques and new methods of creating 3D imagery.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark A. Wessels "Formation of stereoscopic image pairs from a sequence of frames", Proc. SPIE 6056, Three-Dimensional Image Capture and Applications VII, 605609 (26 January 2006); https://doi.org/10.1117/12.641994
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KEYWORDS
Algorithm development

Eye

Satellites

Image acquisition

3D image processing

Cameras

Edge detection

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