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A Novel Binary Feature from Intensity Difference Quantization between Random Sample of Points
[chapter]
2013
Lecture Notes in Computer Science
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It consists of a string of binary bits which are derived from the intensity difference quantization (IDQ) between pixel pairs which are chosen according to a fixed random sample pattern, so we called it ...
This pressing need brings a huge challenge to the conventional feature. ...
string, in which the binary bits derived from quantization of the difference of intensity of pixel pairs. ...
doi:10.1007/978-3-642-35728-2_22
fatcat:24debktnsnhivkwxaomzjnmh6e
Random Binary Local Patch Clustering Transforms Based Image Matching for Nonlinear Intensity Changes
2018
Mathematical Problems in Engineering
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Then, a random binary pattern coding method extracts raw feature histograms from the new space. ...
First, a binary local patch clustering transform response is employed as the transform space. The value of the new space exhibits a high similarity after changes in intensity. ...
Acknowledgments This work was supported in part by the Natural Science Foundation of China under Grant 61872425, 61771265, ...
doi:10.1155/2018/6360741
fatcat:s5qtfpn7prgihktjayrwejxzkm
Reflectance hashing for material recognition
2015
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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We introduce a novel method for using reflectance to identify materials. ...
We introduce a framework called reflectance hashing that models the reflectance disks with dictionary learning and binary hashing. ...
Acknowledgement The authors would like to thank Felix Yu from lab of Shih-Fu Chang, Columbia University and Sanjiv Kumar from Google Research for supplying binary embedding codes. ...
doi:10.1109/cvpr.2015.7298926
dblp:conf/cvpr/ZhangDN15
fatcat:vxtotslyqzblvo6njlga4zafea
Texture Description with Completed Local Quantized Patterns
[chapter]
2013
Lecture Notes in Computer Science
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Local binary patterns (LBP) has been very successful in a number of areas, including texture analysis and face analysis. ...
Recently, local quantized patterns (LQP) was proposed to use vector quantization to code complicated patterns with a large number of neighbors and several quantization levels. ...
This work was supported by the Academy of Finland, Infotech Oulu and Nokia Foundation. This work was supported in part by grant 40297/11 from Tekes and NSFC (61231002, 61073137). ...
doi:10.1007/978-3-642-38886-6_1
fatcat:dx7gfkpg75gehpptqb7yo5wmqe
Reflectance Hashing for Material Recognition
[article]
2015
arXiv
pre-print
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We introduce a novel method for using reflectance to identify materials. ...
We demonstrate the effectiveness of reflectance hashing for material recognition with a number of real-world materials. ...
Therefore, the recorded image is an observation of a single point on the surface but from a dense sampling of viewing directions. ...
arXiv:1502.02092v1
fatcat:mhdojjw5ujd7rmwsgv446ibc4i
Budget restricted incremental learning with pre-trained convolutional neural networks and binary associative memories
2017
2017 IEEE International Workshop on Signal Processing Systems (SiPS)
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NUMBERS BETWEEN BRACKETS ACCOUNTS FOR PRODUCT RANDOM SAMPLING INSTEAD OF PQ. ...
Basically, we split each x m into P subvectors of equal sizes denoted x m p 1≤p≤P , which are quantized independently from each other using random selection of K anchor points Y p = y p1 , ..., y pK , ...
doi:10.1109/sips.2017.8109978
dblp:conf/sips/HaceneGFAJ17
fatcat:2lhfhwdrfrbrtl6zkpjjobelc4
Budget Restricted Incremental Learning with Pre-Trained Convolutional Neural Networks and Binary Associative Memories
2019
Journal of Signal Processing Systems
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NUMBERS BETWEEN BRACKETS ACCOUNTS FOR PRODUCT RANDOM SAMPLING INSTEAD OF PQ. ...
Basically, we split each x m into P subvectors of equal sizes denoted x m p 1≤p≤P , which are quantized independently from each other using random selection of K anchor points Y p = y p1 , ..., y pK , ...
doi:10.1007/s11265-019-01450-z
fatcat:uyx2jv3u4fe3njgfu753qyz5u4
Adaptive Training of Random Mapping for Data Quantization
[article]
2017
arXiv
pre-print
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In this work, a novel binary embedding method, termed adaptive training quantization (ATQ), is proposed to learn the ideal transform of random encoder, where the limitation of cosine random mapping is ...
Data quantization learns encoding results of data with certain requirements, and provides a broad perspective of many real-world applications to data handling. ...
Acknowledgment This work was supported by Natural Science Foundation Project of Macau S.A.R., research committee of Macau University of Science and Technology, and Qingdao University. ...
arXiv:1606.08808v2
fatcat:on7ewxoqsfbjje2bmk5cdo5qpe
High-contrast pattern reconstructions using a phase-seeded point CGH method
2016
Applied Optics
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A seeded-phase point method is proposed to address this challenge, whereby patterns composed of fine lines that intersect and form closed shapes are reconstructed with high contrast while maintaining a ...
It is also shown that binary phase modulation achieves similar contrast performance with benefits for the fabrication of simpler diffractive optical elements. ...
random phase distribution created by inserting p interpolated values between an initial random sequence. ...
doi:10.1364/ao.55.001703
pmid:26974633
fatcat:52qjs7trzbdxjkcqqqrzaodgsm
Recent Advance in Content-based Image Retrieval: A Literature Survey
[article]
2017
arXiv
pre-print
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With the ignorance of visual content as a ranking clue, methods with text search techniques for visual retrieval may suffer inconsistency between the text words and visual content. ...
Such a problem is challenging due to the intention gap and the semantic gap problems. Numerous techniques have been developed for content-based image retrieval in the last decade. ...
Apart from floating point feature like SIFT, binary features are popularly explored and directly extracted from the local region of interest. ...
arXiv:1706.06064v2
fatcat:m52xwsw5pzfzdbxo5o6dye2gde
HISTOGRAM OF EDGE SEGMENT CURVATURES FOR TEXTURE RECOGNITION
2018
Anadolu University Journal of Science and Technology. A : Applied Sciences and Engineering
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In this paper, we propose novel feature descriptor, namely histogram of edge segment curvatures (HESC) which extracts edge segments of an input image and construct a histogram from quantized curvature ...
The majority of methods use appearance-based properties of texture images to generate a feature descriptor. ...
Then the histograms of the binary codes generated from differences are used as feature descriptor. ...
doi:10.18038/aubtda.441568
fatcat:wrb3j6kq4rbptfpdfxhnanet6i
CQ-VAE: Coordinate Quantized VAE for Uncertainty Estimation with Application to Disk Shape Analysis from Lumbar Spine MRI Images
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:2010.08713v1 fatcat:t3f6qufikndvbjmfybzwx3m4ua
A matching algorithm is used to establish the correspondence between model-generated samples and "ground-truth" samples, which makes a trade-off between the ability to generate new samples and the ability ...
Our model, named Coordinate Quantization Variational Autoencoder (CQ-VAE) employs a discrete latent space with an internal discrete probability distribution by quantizing the coordinates of a continuous ...
This VAE-based U-Net samples a random feature map from a generative model and concatenates this map to the last activation map of U-Net to generate a possible segmentation mask. ...
arXiv:2010.08713v2
fatcat:mlthrwmdcfa5jcqfddx4jv4dce
Perceptual Image Hashing Via Feature Points: Performance Evaluation and Tradeoffs
2006
IEEE Transactions on Image Processing
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We apply probabilistic quantization on the derived features to introduce randomness, which in turn reduces vulnerability to adversarial attacks. ...
We propose an image hashing paradigm using visually significant feature points. The feature points should be largely invariant under perceptually insignificant distortions. ...
The binary string obtained from the quantized feature vector f q is hence of length P log 2 (L) bits. ...
doi:10.1109/tip.2006.881948
pmid:17076404
fatcat:zsavnvskfjb3pnblamibcwd47m
Local circular patterns for multi-modal facial gender and ethnicity classification
2014
Image and Vision Computing
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In order to comprehensively represent the difference between different genders or ethnicities, we propose a novel local descriptor, namely local circular patterns (LCP). ...
LCP improves the widely utilized local binary patterns (LBP) and its variants by replacing the binary quantization with a clustering based one, resulting in higher discriminative power as well as better ...
To comprehensively represent the difference between different genders or ethnicities, a novel local descriptor, namely local circular patterns (LCP) is introduced. ...
doi:10.1016/j.imavis.2014.06.009
fatcat:xcac5emejje7doamlq4p4hdpjm
Learning Image Descriptors with Boosting
2015
IEEE Transactions on Pattern Analysis and Machine Intelligence
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We propose a novel and general framework to learn compact but highly discriminative floating-point and binary local feature descriptors. ...
We then present the main contribution of this paper -a binary extension of the framework that demonstrates the real advantage of our approach and allows us to compress the descriptor even further. ...
These patches are sampled around interest points detected using Difference of Gaussians and the correspondences between patches are found using a multi-view stereo algorithm. ...
doi:10.1109/tpami.2014.2343961
pmid:26353264
fatcat:az4aswmbjbhgnghpp5zabrgf4u
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