Violent video detection based on MoSIFT feature and sparse coding
To detect violence in a video, a common video description method is to apply local spatio-
temporal description on the query video. Then, the low-level description is further …
temporal description on the query video. Then, the low-level description is further …
Learning dictionary on manifolds for image classification
At present, dictionary based models have been widely used in image classification. The
image features are approximated as a linear combination of bases selected from the …
image features are approximated as a linear combination of bases selected from the …
Face recognition using class specific dictionary learning for sparse representation and collaborative representation
Recently, sparse representation based classification (SRC) and collaborative representation
based classification (CRC) have been successfully used for visual recognition and have …
based classification (CRC) have been successfully used for visual recognition and have …
Self-explanatory sparse representation for image classification
Traditional sparse representation algorithms usually operate in a single Euclidean space.
This paper leverages a self-explanatory reformulation of sparse representation, ie, linking …
This paper leverages a self-explanatory reformulation of sparse representation, ie, linking …
Blockwise coordinate descent schemes for sparse representation
The current sparse representation framework is to decouple it as two subproblems, ie,
alternate sparse coding and dictionary learning using different optimizers, treating elements …
alternate sparse coding and dictionary learning using different optimizers, treating elements …
Elastic net regularized dictionary learning for image classification
Dictionary learning plays a key role in image representation for classification. A multi-modal
dictionary is usually learned from feature samples across different classes and shared in the …
dictionary is usually learned from feature samples across different classes and shared in the …
Document image quality assessment using discriminative sparse representation
X Peng, H Cao, P Natarajan - 2016 12th IAPR Workshop on …, 2016 - ieeexplore.ieee.org
The goal of document image quality assessment (DIQA) is to build a computational model
which can predict the degree of degradation for document images. Based on the estimated …
which can predict the degree of degradation for document images. Based on the estimated …
Class specific centralized dictionary learning for face recognition
Sparse representation based classification (SRC) and collaborative representation based
classification (CRC) have demonstrated impressive performance for visual recognition. SRC …
classification (CRC) have demonstrated impressive performance for visual recognition. SRC …
Low-rank image tag completion with dual reconstruction structure preserved
User provided tags, albeit play an essential role in image annotation, may inhibit accurate
annotation as well since they are potentially incomplete. To address this problem, a novel …
annotation as well since they are potentially incomplete. To address this problem, a novel …
Image tag completion by low-rank factorization with dual reconstruction structure preserved
A novel tag completion algorithm is proposed in this paper, which is designed with the
following features: 1) Low-rank and error s-parsity: the incomplete initial tagging matrix D is …
following features: 1) Low-rank and error s-parsity: the incomplete initial tagging matrix D is …