Feature Extraction

Feature Extraction

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 it 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.

Software

  • Circular Center Symmetric-Pairs of Pixels (CCS-POP) available for download here.

 

Publications

1.Bastos, Igor L. O; Soares, Larissa Rocha; Schwartz, William Robson (2017): Pyramidal Zernike Over Time: A spatiotemporal feature descriptor based on Zernike Moments. In: Iberoamerican Congress on Pattern Recognition (CIARP 2017), pp. 77-85, 2017. (Type: Inproceeding | Links | BibTeX)
2.Colque, Rensso Mora; Caetano, Carlos; Toledo, Matheus; Schwartz, William Robson (2017): Histograms of Optical Flow Orientation and Magnitude and Entropy to Detect Anomalous Events in Videos. In: IEEE Transactions on Circuits and Systems for Video Technology, 27 (3), pp. 673-682, 2017. (Type: Article | Links | BibTeX)
3.Caetano, Carlos; Santos, Jefersson A. dos; Schwartz, William Robson (2016): Optical Flow Co-occurrence Matrices: A Novel Spatiotemporal Feature Descriptor. In: IAPR International Conference on Pattern Recognition (ICPR), pp. 1-6, 2016. (Type: Inproceeding | Links | BibTeX)
4.Pessoa, Ramon F.; Schwartz, William Robson; Santos, Jefersson A. dos (2015): A Study on Low-Cost Representations for Image Feature Extraction on Mobile Devices. In: 14th Iberoamerican Congress on Pattern Recognition (CIARP), pp. 1-8, 2015. (Type: Inproceeding | Links | BibTeX)
5.Jr., Nazare, Antonio C.,; Renato, Ferreira,; Robson, Schwartz, William (2014): Scalable Feature Extraction for Visual Surveillance. In: Iberoamerican Congress on Pattern Recognition (CIARP), pp. 375-382, Springer International Publishing, 2014. (Type: Inproceeding | Links | BibTeX)
6.Siqueira, F. R. de; Schwartz, W. R.; Pedrini, H. (2013): Multi-Scale Gray Level Co-Occurrence Matrices for Texture Description. In: Neurocomputing, pp. 1-10, 2013. (Type: Article | Links | BibTeX)
7.Nascimento, E. R.; Oliveira, G. L.; Campos, M. F. M.; Schwartz, A. W. Vieira, W. R. (2012): BRAND: A Robust Appearance and Depth Descriptor for RGB-D Images. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012. (Type: Inproceeding | Links | BibTeX)
8.Nascimento, E. R.; Schwartz, W. R.; Campos, M. F. M. (2012): EDVD - Enhanced Descriptor for Visual and Depth Data. In: IAPR International Conference on Pattern Recognition, 2012. (Type: Inproceeding | Links | BibTeX)
9.Nascimento, E. R.; Schwartz, W. R.; Oliveira, G. L.; Vieira, A. W.; Campos, M. F. M.; Mesquita, D. B. (2012): Appearance and Geometry Fusion for Enhanced Dense 3D Alignment. In: Conference on Graphics, Patterns and Images, 2012. (Type: Inproceeding | Links | BibTeX)
10.Schwartz, W. R.; Pedrini, H. (2012): Evaluation of Feature Descriptors for Texture Classification. In: Journal of Electronic Imaging, 21 (2), pp. 1-17, 2012. (Type: Article | Links | BibTeX)
11.Silva, R. D. da; Schwartz, W. R.; Pedrini, H. (2012): Scalar Image Interest Point Detection and Description Based on Discrete Morse Theory and Geometric Descriptors. In: IEEE International Conference on Image Processing, 2012. (Type: Inproceeding | Links | BibTeX)
12.Choi, J.; Guo, H.; Schwartz, W. R.; Davis, L. S. (2012): A Complementary Local Feature Descriptor for Face Identification. In: IEEE Workshop on Applications of Computer Vision, pp. 121-128, 2012. (Type: Inproceeding | Links | BibTeX)
13.Schwartz, W. R.; Silva, R. D. da; Davis, L. S.; Pedrini, H. (2011): A Novel Feature Descriptor Based on the Shearlet Transform. In: IEEE International Conference on Image Processing, pp. 1033-1036, 2011. (Type: Inproceeding | Links | BibTeX)