FAMINet: Learning Real-Time Semisupervised Video Object Segmentation With Steepest Optimized Optical Flow

Semisupervised video object segmentation (VOS) aims to segment a few moving objects in a video sequence, where these objects are specified by annotation of the first frame. The optical flow has been considered in many existing semisupervised VOS methods to improve the segmentation accuracy. However,...

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Vydané v:	IEEE transactions on instrumentation and measurement Ročník 71; s. 1 - 16
Hlavní autori:	Liu, Ziyang, Liu, Jingmeng, Chen, Weihai, Wu, Xingming, Li, Zhengguo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptive optics Algorithms Annotations Feature extraction Integrated optics Motion segmentation Online memorizing optical flow Optical flow (image analysis) Optical imaging Optical network units Pedestrians Real time relaxed steepest descent Segmentation semisupervised video object segmentation (VOS) Streaming media
ISSN:	0018-9456, 1557-9662
On-line prístup:	Získať plný text
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