Spatial Pooling of Heterogeneous Features for Image Classification

In image classification tasks, one of the most successful algorithms is the bag-of-features (BoFs) model. Although the BoF model has many advantages, such as simplicity, generality, and scalability, it still suffers from several drawbacks, including the limited semantic description of local descript...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 23; no. 5; pp. 1994 - 2008
Main Authors:	Xie, Lingxi, Tian, Qi, Wang, Meng, Zhang, Bo
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.05.2014 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Accuracy Algorithms Applied sciences Basic converters Construction Exact sciences and technology Feature extraction Image classification Image edge detection Image processing Information, signal and communications theory Mathematical models Oxygen steel making Pattern recognition Quantization (signal) Shape Signal and communications theory Signal processing Signal representation. Spectral analysis Signal, noise Telecommunications and information theory Texture Vectors Visualization BoF model geometric phrases pooling complementary descriptors spatial weighting Image classification Performance evaluation State of the art Image processing Scalability Pattern recognition Signal representation Shape detection Algorithm Modeling Texture Interest region Weighting Semantics Image representation Edge detection
ISSN:	1057-7149, 1941-0042, 1941-0042
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!