JOURNAL ARTICLE

A robust region-based global camera estimation method for video sequences

Abstract

Global motion estimation (GME) plays an important role in video object segmentation. This paper presents a computationally efficient three stage affine GME algorithm, using radius-based Fourier Descriptors from histogram-based image segmented regions. Then a variance-cut KD tree is used for initial matching between FDs. and an efficient two-step outlier method is applied to remove incorrect outliers. Experiments with different video sequences are used to demonstrate the performance of the proposed approach.

Keywords:
Computer science Outlier Artificial intelligence Histogram Computer vision Affine transformation Segmentation Motion estimation Matching (statistics) Image segmentation Video tracking Block-matching algorithm Pattern recognition (psychology) Image (mathematics) Object (grammar) Mathematics

Metrics

2
Cited By
0.26
FWCI (Field Weighted Citation Impact)
15
Refs
0.60
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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