Accession Number : ADA311290
Title : Dense Structure from a Dense Optical Flow Sequence.
Descriptive Note : Technical rept.,
Corporate Author : CARNEGIE-MELLON UNIV PITTSBURGH PA ROBOTICS INST
Personal Author(s) : Xiong, Yalin ; Shafer, Steven A.
PDF Url : ADA311290
Report Date : APR 1995
Pagination or Media Count : 40
Abstract : This paper presents a structure from motion system which delivers dense structure information from a sequence of dense optical flows. Most traditional feature based approaches cannot be extended to compute dense structure due to impractical computational complexity. We demonstrate that by decomposing uncertainty information into independent and correlated parts we can decrease these complexities from 0 (N2) to 0(N), where is the number of pixels in the images. We also show that this dense structure from motion system requires only local optical flows, i.e. image matchings between two adjacent frames, instead of the trucking of features over a long sequence of frames.
Descriptors : *FLOW VISUALIZATION, *COMPUTER VISION, UNCERTAINTY, MOTION, KALMAN FILTERING, SEQUENCES, HIGH DENSITY.
Subject Categories : Bionics
Distribution Statement : APPROVED FOR PUBLIC RELEASE