Feature extraction is vital for face recognition. In this paper, we focus on the general feature
extraction framework for robust face recognition. We collect about 300 papers regarding face …

This paper presents a compact and efficient yet powerful binary framework based on image
gradients for robust facial representation. It is termed as Binary Gradient Patterns (BGP). To …

A new line of research uses compression methods to measure the similarity between
signals. Two signals are considered similar if one can be compressed significantly when the …

Single-sample face recognition has been investigated by a few researches over the past few
decades. However, due to the demand of identity of interest searching from video …

Huge video archives consisting of news programs, dramas, movies, and Web videos (eg,
YouTube) are available in our daily life. In all these videos, human is usually one of the most …

During the last decade, sparse representations have been successfully applied to design
high-performing classification algorithms such as the classical sparse representation based …

Face recognition has received a substantial attention by the vision community over the past
few decades. Most of the proposed frameworks have adopted the closed-set form of face …

Recently, the regularized coding-based classification methods (eg SRC and CRC) show a
great potential for pattern classification. However, most existing coding methods assume that …

The main finding of this work is that the standard image classification pipeline, which
consists of dictionary learning, feature encoding, spatial pyramid pooling and linear …

Visual processing in social media platforms is a key step in gathering and understanding
information in the era of Internet and big data. Online data is rich in content, but its …