Authors:
Wei Wang
;
Weili Li
;
Xiaoqing Yin
;
Yu Liu
and
Maojun Zhang
Affiliation:
National University of Defense Technology, China
Keyword(s):
Foreground Segmentation, Moving Cameras, Trajectory Classification, Marker-controlled Watershed Segmentation.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Cardiovascular Imaging and Cardiography
;
Cardiovascular Technologies
;
Clustering
;
Computer Vision, Visualization and Computer Graphics
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Image and Video Analysis
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
;
Signal Processing
;
Software Engineering
;
Theory and Methods
;
Video Analysis
Abstract:
A foreground segmentation method, including image enhancement, trajectory classification and object segmentation,
is proposed for moving cameras under low illumination conditions. Gradient-field-based image
enhancement is designed to enhance low-contrast images. On the basis of the dense point trajectories obtained
in long frames sequences, a simple and effective clustering algorithm is designed to classify foreground
and background trajectories. By combining trajectory points and a marker-controlled watershed algorithm,
a new type of foreground labeling algorithm is proposed to effectively reduce computing costs and improve
edge-preserving performance. Experimental results demonstrate the promising performance of the proposed
approach compared with other competing methods.