Scalable Block-Diagonal Locality-Constrained Projective Dictionary Learning

05/25/2019
by   Zhao Zhang, et al.
0

We propose a novel structured discriminative block-diagonal dictionary learning method, referred to as scalable Locality-Constrained Projective Dictionary Learning (LC-PDL), for efficient representation and classification. To improve the scalability by saving both training and testing time, our LC-PDL aims at learning a structured discriminative dictionary and a block-diagonal representation without using costly l0/l1-norm. Besides, it avoids extra time-consuming sparse reconstruction process with the well-trained dictionary for new sample as many existing models. More importantly, LC-PDL avoids using the complementary data matrix to learn the sub-dictionary over each class. To enhance the performance, we incorporate a locality constraint of atoms into the DL procedures to keep local information and obtain the codes of samples over each class separately. A block-diagonal discriminative approximation term is also derived to learn a discriminative projection to bridge data with their codes by extracting the special block-diagonal features from data, which can ensure the approximate coefficients to associate with its label information clearly. Then, a robust multiclass classifier is trained over extracted block-diagonal codes for accurate label predictions. Experimental results verify the effectiveness of our algorithm.

READ FULL TEXT

page 3

page 6

research
05/27/2019

Jointly Learning Structured Analysis Discriminative Dictionary and Analysis Multiclass Classifier

In this paper, we propose an analysis mechanism based structured Analysi...
research
06/11/2019

Joint Subspace Recovery and Enhanced Locality Driven Robust Flexible Discriminative Dictionary Learning

We propose a joint subspace recovery and enhanced locality based robust ...
research
08/04/2017

Correlation and Class Based Block Formation for Improved Structured Dictionary Learning

In recent years, the creation of block-structured dictionary has attract...
research
01/07/2016

Block-Diagonal Sparse Representation by Learning a Linear Combination Dictionary for Recognition

In a sparse representation based recognition scheme, it is critical to l...
research
08/04/2019

Robust Subspace Discovery by Block-diagonal Adaptive Locality-constrained Representation

We propose a novel and unsupervised representation learning model, i.e.,...
research
10/17/2014

KCRC-LCD: Discriminative Kernel Collaborative Representation with Locality Constrained Dictionary for Visual Categorization

We consider the image classification problem via kernel collaborative re...
research
11/22/2019

Locality Constraint Dictionary Learning with Support Vector for Pattern Classification

Discriminative dictionary learning (DDL) has recently gained significant...

Please sign up or login with your details

Forgot password? Click here to reset