Accession Number : ADA259494


Title :   Temporal Surface Reconstruction


Descriptive Note : Technical rept.


Corporate Author : MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB


Personal Author(s) : Heel, Joachim


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a259494.pdf


Report Date : 03 May 1991


Pagination or Media Count : 150


Abstract : This thesis investigates the problem of estimating the three- dimensional structure of a scene from a sequence of images. Structure information can be recovered from images through a number of visual mechanisms such as shading, motion and stereo. Image information is commonly available in a time-continuous fashion and this work proposes a method for estimating structure information in a temporally continuous manner for a variety of visual mechanisms. Structural information about a scene is represented in a dense depth map in which the distance to the scene is stored for each pixel location in the image. In addition, uncertainty about the structure values is represented explicitly by the estimate covariance. This representation is maintained over time by a stochastic recursive estimator, the Kalman filter. The estimator consists of two stages which are repeated for each new arriving image. The update stage improves the current depth estimate by incorporating the latest image measurement. It depends on the particular visual mechanism being employed and amounts to an iterative relaxation algorithm similar to conventional single- frame algorithms. The prediction stage transforms the current depth estimate into the next time-step to account for changes in the depth values that may occur if the camera moves relative to the (rigid) scene during the acquisition of the sequence.


Descriptors :   *IMAGE PROCESSING , *CONSTRUCTION , *COMPUTER VISION , ALGORITHMS , MEASUREMENT , UNCERTAINTY , ACQUISITION , PREDICTIONS , STRUCTURES , MOTION , KALMAN FILTERING , VALUE , VISUAL PERCEPTION , VISION , FRAMES , WORK , RELAXATION , MAPS , CAMERAS , IMAGES , ADDITION , NUMBERS , COVARIANCE , FILTERS , THESES , DEPTH , SEQUENCES , ESTIMATES , TIME , SURFACES , THREE DIMENSIONAL


Subject Categories : Computer Programming and Software
      Cybernetics


Distribution Statement : APPROVED FOR PUBLIC RELEASE