Video tracking using learned hierarchical features

Video tracking using learned hierarchical features

In this paper, we propose an approach to learn hierarchical features for visual object tracking. First, we offline learn features robust to diverse motion patterns from auxiliary video sequences. The hierarchical features are learned via a two-layer convolutional neural network. Embedding the tempor...

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Bibliographic Details
Main Authors: Wang, Gang, Chan, Kap Luk, Liu, Ting, Yang, Qingxiong, Wang, Li
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2015
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Online Access:https://hdl.handle.net/10356/107287
http://hdl.handle.net/10220/25473
http://dx.doi.org/10.1109/TIP.2015.2403231

Internet

https://hdl.handle.net/10356/107287
http://hdl.handle.net/10220/25473
http://dx.doi.org/10.1109/TIP.2015.2403231

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