Title

Recovering 3D motion of multiple objects using adaptive Hough transform

Authors

Authors

T. Y. Tian;M. Shah

Comments

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Abbreviated Journal Title

IEEE Trans. Pattern Anal. Mach. Intell.

Keywords

multiple-motion analysis; segmentation; structure-from-motion; robust; estimation; adaptive Hough transform; OPTICAL-FLOW; MOVING-OBJECTS; ALGORITHM; Computer Science, Artificial Intelligence; Engineering, Electrical &; Electronic

Abstract

We present a method to determine 3D motion and structure of multiple objects from two perspective views, using adaptive Hough transform. In our method, segmentation is determined based on a 3D rigidity constraint. Instead of searching candidate solutions over the entire five-dimensional translation and rotation parameter space, we only examine the two-dimensional translation space. We divide the input image into overlapping patches, and, for each sample of the translation space, we compute the rotation parameters of patches using least-squares fit. Every patch votes for a sample in the five-dimensional parameter space. For a patch containing multiple motions, we use a redescending M-estimator to compute rotation parameters of a dominant motion within the patch. To reduce computational and storage burdens of standard multidimensional Hough transform, we use adaptive Hough transform to iteratively refine the relevant parameter space in a ''coarse-to-fine'' fashion. Our method can robustly recover 3D motion parameters, reject outliers of the flow estimates, and deal with multiple moving objects present in the scene. Applications of the proposed method to both synthetic and real image sequences are demonstrated with promising results.

Journal Title

Ieee Transactions on Pattern Analysis and Machine Intelligence

Volume

19

Issue/Number

10

Publication Date

1-1-1997

Document Type

Article

Language

English

First Page

1178

Last Page

1183

WOS Identifier

WOS:A1997YB67800015

ISSN

0162-8828

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