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IFTrace: Video segmentation of deformable objects using the Image Foresting Transform
(Academic Press Inc. Elsevier B.V., 2012-02-01)
We introduce IFTrace, a method for video segmentation of deformable objects. The algorithm makes minimal assumptions about the nature of the tracked object: basically, that it consists of a few connected regions, and has ...
IFTrace: Video segmentation of deformable objects using the Image Foresting Transform
(Academic Press Inc. Elsevier B.V., 2012-02-01)
We introduce IFTrace, a method for video segmentation of deformable objects. The algorithm makes minimal assumptions about the nature of the tracked object: basically, that it consists of a few connected regions, and has ...
IFTrace: Video segmentation of deformable objects using the Image Foresting Transform
(Academic Press Inc Elsevier ScienceSan DiegoEUA, 2012)
IFTrace: Video segmentation of deformable objects using the Image Foresting Transform
(Academic Press Inc. Elsevier B.V., 2014)
Video Segmentation Learning Using Cascade Residual Convolutional Neural Network
(Ieee, 2019-01-01)
Video segmentation consists of a frame-by-frame selection process of meaningful areas related to foreground moving objects. Some applications include traffic monitoring, human tracking, action recognition, efficient video ...
Exploiting convolutional neural networks for superpixel based contextual description
(Universidade Federal de Minas GeraisUFMG, 2018-12-12)
Remote sensing is an important technique for acquiring consistent, repeated high resolution observations of large-scale phenomena and processes. However, the ever increasing amount of data brought by the continuing improvement ...