Document Detail


Bayesian algorithms for simultaneous structure from motion estimation of multiple independently moving objects.
MedLine Citation:
PMID:  15646875     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In this paper, the problem of simultaneous structure from motion estimation for multiple independently moving objects from a monocular image sequence is addressed. Two Bayesian algorithms are presented for solving this problem using the sequential importance sampling (SIS) technique. The empirical posterior distribution of object motion and feature separation parameters is approximated by weighted samples. The first algorithm addresses the problem when only two moving objects are present. A singular value decomposition (SVD)-based sample clustering algorithm is shown to be capable of separating samples related to different objects. A pair of SIS procedures is used to track the posterior distribution of the motion parameters. In the second algorithm, a balancing step is added into the SIS procedure to preserve samples of low weights so that all objects have enough samples to propagate empirical motion distributions. By using the proposed algorithms, the relative motions of all the moving objects with respect to the camera can be simultaneously estimated. Both algorithms have been tested on synthetic and real-image sequences. Improved results have been achieved.
Authors:
Gang Qian; Rama Chellappa; Qinfen Zheng
Related Documents :
10673015 - Promoter sequences and algorithmical methods for identifying them.
17108385 - Correspondence-free determination of the affine fundamental matrix.
12850295 - Ordered subsets bayesian tomographic reconstruction using 2-d smoothing splines as priors.
12269575 - Deriving inherent optical properties from water color: a multiband quasi-analytical alg...
23292765 - Estimation of finite population duration distributions from longitudinal survey panels ...
10673015 - Promoter sequences and algorithmical methods for identifying them.
Publication Detail:
Type:  Comparative Study; Evaluation Studies; Journal Article; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  IEEE transactions on image processing : a publication of the IEEE Signal Processing Society     Volume:  14     ISSN:  1057-7149     ISO Abbreviation:  IEEE Trans Image Process     Publication Date:  2005 Jan 
Date Detail:
Created Date:  2005-01-13     Completed Date:  2005-02-10     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  9886191     Medline TA:  IEEE Trans Image Process     Country:  United States    
Other Details:
Languages:  eng     Pagination:  94-109     Citation Subset:  IM    
Affiliation:
Department of Electrical and Computer Engineering and the Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742, USA. gqian@cfar.umd.edu
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Algorithms*
Artificial Intelligence*
Cluster Analysis
Computer Graphics
Computer Simulation
Humans
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods
Information Storage and Retrieval / methods
Models, Biological
Models, Statistical
Movement / physiology*
Numerical Analysis, Computer-Assisted
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted
Subtraction Technique*
Video Recording / methods*
Walking / physiology

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Statistical processing of large image sequences.
Next Document:  Multidimensional, mapping-based complex wavelet transforms.