A Robust and Discriminative Feature Representation based on Compact Coding
Yue Jinpeng, Jiang Guang, Hu Hong, Shi Zhongzhi
Available Online November 2013.
- https://doi.org/10.2991/icmt-13.2013.149How to use a DOI?
- Visual feature Feature representation Compact coding
- As human vision system works, the visual features extracted from colours, textures, shapes, etc. are complement and should be synthesized to make a decision. Existing applications mainly base on one kind of features such as the wildly used texture feature. We put forward that complement features should be combined together to improve feature discriminabilty. And we propose a feature combining framework, which benefits from the recent fruitful research on compact coding of visual features. The compact codes are learned to be robust to complex image content variations. We combine colour histogram and texture under the framework, and experiments show that our method provides an effective way to the representation of features and has a wide application.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yue Jinpeng AU - Jiang Guang AU - Hu Hong AU - Shi Zhongzhi PY - 2013/11 DA - 2013/11 TI - A Robust and Discriminative Feature Representation based on Compact Coding BT - 3rd International Conference on Multimedia Technology(ICMT-13) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/icmt-13.2013.149 DO - https://doi.org/10.2991/icmt-13.2013.149 ID - Jinpeng2013/11 ER -