Extração de Característica

As informações visuais contidas nas imagens geralmente são representadas por descritores de recursos de baixo nível, com foco em diferentes tipos de informações, como cor, textura e forma. Um descritor de característica adequado é capaz de discriminar entre regiões com características diferentes e permite que regiões similares sejam agrupadas, mesmo quando capturadas sob condições ruidosas. No entanto, geralmente é difícil ter um descritor de recurso único adequado para muitos domínios de aplicativo, isso motivou os pesquisadores a desenvolver uma variedade de métodos de extração de características.

Softwares

 

  • Circular Center Symmetric-Pairs of Pixels (CCS-POP) está disponível para download aqui.

Publicações Relacionadas

Igor Leonardo Oliveira Bastos; Larissa Rocha Soares; William Robson Schwartz

Pyramidal Zernike Over Time: A spatiotemporal feature descriptor based on Zernike Moments Inproceedings

Em: Iberoamerican Congress on Pattern Recognition (CIARP 2017), pp. 77-85, 2017.

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Rensso Victor Hugo Mora Colque; Carlos Antonio Caetano Junior; Matheus Toledo Lustosa de Andrade; William Robson Schwartz

Histograms of Optical Flow Orientation and Magnitude and Entropy to Detect Anomalous Events in Videos Journal Article

Em: IEEE Transactions on Circuits and Systems for Video Technology, 27 (3), pp. 673-682, 2017.

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Carlos Antonio Caetano Junior; Jefersson A dos Santos; William Robson Schwartz

Optical Flow Co-occurrence Matrices: A Novel Spatiotemporal Feature Descriptor Inproceedings

Em: IAPR International Conference on Pattern Recognition (ICPR), pp. 1-6, 2016.

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Ramon F Pessoa; William Robson Schwartz; Jefersson A dos Santos

A Study on Low-Cost Representations for Image Feature Extraction on Mobile Devices Inproceedings

Em: 14th Iberoamerican Congress on Pattern Recognition (CIARP), pp. 1-8, 2015.

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Antonio Carlos Nazare Junior; Renato Ferreira; William Robson Schwartz

Scalable Feature Extraction for Visual Surveillance Inproceedings

Em: Iberoamerican Congress on Pattern Recognition (CIARP), pp. 375-382, Springer International Publishing, 2014.

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F R de Siqueira; William Robson Schwartz; H Pedrini

Multi-Scale Gray Level Co-Occurrence Matrices for Texture Description Journal Article

Em: Neurocomputing, pp. 1-10, 2013.

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E R Nascimento; G L Oliveira; M F M Campos; William Robson Schwartz

BRAND: A Robust Appearance and Depth Descriptor for RGB-D Images Inproceedings

Em: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012.

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E R Nascimento; William Robson Schwartz; M F M Campos

EDVD - Enhanced Descriptor for Visual and Depth Data Inproceedings

Em: IAPR International Conference on Pattern Recognition, 2012.

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E R Nascimento; William Robson Schwartz; G L Oliveira; A W Vieira; M F M Campos; D B Mesquita

Appearance and Geometry Fusion for Enhanced Dense 3D Alignment Inproceedings

Em: Conference on Graphics, Patterns and Images, 2012.

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William Robson Schwartz; H Pedrini

Evaluation of Feature Descriptors for Texture Classification Journal Article

Em: Journal of Electronic Imaging, 21 (2), pp. 1-17, 2012.

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R D da Silva; William Robson Schwartz; H Pedrini

Scalar Image Interest Point Detection and Description Based on Discrete Morse Theory and Geometric Descriptors Inproceedings

Em: IEEE International Conference on Image Processing, 2012.

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J Choi; H Guo; William Robson Schwartz; L S Davis

A Complementary Local Feature Descriptor for Face Identification Inproceedings

Em: IEEE Workshop on Applications of Computer Vision, pp. 121-128, 2012.

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William Robson Schwartz; R D da Silva; L S Davis; H Pedrini

A Novel Feature Descriptor Based on the Shearlet Transform Inproceedings

Em: IEEE International Conference on Image Processing, pp. 1033-1036, 2011.

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