Visual information contained in images is usually represented by low-level feature descriptors focusing on different types of information, such as color, texture, and shape. An adequate feature descriptor is able to discriminate between regions with different characteristics and allows similar regions to be grouped together even when captured under noisy conditions. However, it is usually difficult to have a single feature descriptor adequate for many application domains; this has motivated researchers to develop a variety of feature extraction methods.
In: Iberoamerican Congress on Pattern Recognition (CIARP 2017), pp. 77-85, 2017.
In: IEEE Transactions on Circuits and Systems for Video Technology, 27 (3), pp. 673-682, 2017.
In: IAPR International Conference on Pattern Recognition (ICPR), pp. 1-6, 2016.
In: 14th Iberoamerican Congress on Pattern Recognition (CIARP), pp. 1-8, 2015.
Scalable Feature Extraction for Visual Surveillance Inproceedings
In: Iberoamerican Congress on Pattern Recognition (CIARP), pp. 375-382, Springer International Publishing, 2014.
In: Neurocomputing, pp. 1-10, 2013.
In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012.
EDVD - Enhanced Descriptor for Visual and Depth Data Inproceedings
In: IAPR International Conference on Pattern Recognition, 2012.
In: Conference on Graphics, Patterns and Images, 2012.
Evaluation of Feature Descriptors for Texture Classification Journal Article
In: Journal of Electronic Imaging, 21 (2), pp. 1-17, 2012.
In: IEEE International Conference on Image Processing, 2012.
In: IEEE Workshop on Applications of Computer Vision, pp. 121-128, 2012.
In: IEEE International Conference on Image Processing, pp. 1033-1036, 2011.