Acquisition of 3D structure of selectable quality from image streams

Abstract

In this paper we present a computational approach for extracting three-dimensional structure of controllable resolution, depth of field, and accuracy, all made available at real-time speeds. This approach utilizes the spatial and the temporal gradients of the streams of images acquired using an actively controlled camera. Depending on the requirements of a particular task, appropriate parameters such as disparity value sought , the inter-frame camera displacement, and number of frames in a stream, are chosen to control the resolution, depth of field, and accuracy. The acquisition and processing of the image stream are done in real-time on a pipeline architecture based processor. Extensive experiments are presented to demonstrate the accuracy, controllability of depth of field and resolution, and ability to perform successfully in a variety of scenes. The system operated with no latency between the image acquisition and processing. The total acquisition and processing time in these experiments is in the range of 0.27 to 1.56 sec. The depth results have an accuracy of 85% to 92%. 0-8186-6410-X/94 $4.00 Q 1994 IEEE

Multispectral Image Processing: The Nature Factor

“…Hyperstereo vision has also been used in robotics applications including navigation. 8,16,19 To illustrate how wide baseline stereo vision could be adapted to enhanced night time vehicular navigation a set of experiments were performed using a pair of Inframetrics, Inc. Model 610 infrared imagers with 2.5 m baseline separation. In order to illustrate how a driver could use a stereo display headset for navigation, a passenger in the vehicle wore a pair of stereoscopic display goggles designed for viewing asynchronous video signals on a see through LCD display shown in Fig.…”