Efficient Non-Consecutive Feature Tracking for Robust Structure-From-Motion.
IEEE Trans Image Process
; 25(12): 5957-5970, 2016 Dec.
Article
en En
| MEDLINE
| ID: mdl-27623586
Structure-from-motion (SfM) largely relies on feature tracking. In image sequences, if disjointed tracks caused by objects moving in and out of the field of view, occasional occlusion, or image noise are not handled well, corresponding SfM could be affected. This problem becomes severer for large-scale scenes, which typically requires to capture multiple sequences to cover the whole scene. In this paper, we propose an efficient non-consecutive feature tracking framework to match interrupted tracks distributed in different subsequences or even in different videos. Our framework consists of steps of solving the feature "dropout" problem when indistinctive structures, noise or large image distortion exists, and of rapidly recognizing and joining common features located in different subsequences. In addition, we contribute an effective segment-based coarse-to-fine SfM algorithm for robustly handling large data sets. Experimental results on challenging video data demonstrate the effectiveness of the proposed system.
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01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
IEEE Trans Image Process
Asunto de la revista:
INFORMATICA MEDICA
Año:
2016
Tipo del documento:
Article
Pais de publicación:
Estados Unidos