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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Main Authors: | , , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2015
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Subjects: | |
Online Access: | 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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Institution: | Nanyang Technological University |
Language: | English |