GMS: Grid-Based Motion Statistics for Fast, Ultra-Robust Feature Correspondence

Incorporating smoothness constraints into feature matching is known to enable ultra-robust matching. However, such formulations are both complex and slow, making them unsuitable for video applications. This paper proposes GMS (Grid-based Motion Statistics), a simple means of encapsulating motion smo...

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Bibliographic Details
Published in:2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 2828 - 2837
Main Authors: JiaWang Bian, Wen-Yan Lin, Matsushita, Yasuyuki, Sai-Kit Yeung, Tan-Dat Nguyen, Ming-Ming Cheng
Format: Conference Proceeding
Language:English
Published: IEEE 01.07.2017
Subjects:
Coherence
Real-time systems
Robustness
Silicon
Three-dimensional displays
ISSN:1063-6919, 1063-6919
Online Access:Get full text
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Summary:Incorporating smoothness constraints into feature matching is known to enable ultra-robust matching. However, such formulations are both complex and slow, making them unsuitable for video applications. This paper proposes GMS (Grid-based Motion Statistics), a simple means of encapsulating motion smoothness as the statistical likelihood of a certain number of matches in a region. GMS enables translation of high match numbers into high match quality. This provides a real-time, ultra-robust correspondence system. Evaluation on videos, with low textures, blurs and wide-baselines show GMS consistently out-performs other real-time matchers and can achieve parity with more sophisticated, much slower techniques.
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2017.302