Jixin Liu

Nanjing University of Posts and Telecommunications · Engineering Research Center of Wideband Wireless Communication Technology, Ministry of Education

Video summary technology based on keyframe extraction is an effective means to rapidly access video content. Traditional video summary generation technology requires high video resolution, which poses a problem as most existing studies have no targeted solutions for videos that are subject to privacy protection. We propose a novel keyframe extracti...

In recent years, fall detection, especially for the elderly living alone at home, is a challenge in the field of computer vision and pattern recognition. However, there is a concern of loss of privacy in intelligent visual surveillance. In order to solve the contradiction between security surveillance and privacy protection in vision-based fall det...

Face recognition under natural scenes is a significant challenge in pattern recognition research. With the success of sparse representation-based classification in related fields, face recognition based on compressed sensing (CS) theory has received increasing attention. These CS-based approaches produce excellent results when dealing with face dat...

Rare bird has long been considered an important in the field of airport security, biological conservation, environmental monitoring, and so on. With the development and popularization of IOT-based video surveillance, all day and weather unattended bird monitoring becomes possible. However, the current mainstream bird recognition methods are mostly...

Exact compressed sensing (CS) recovery theoretically depends on a large number of random measurements. In this study, the authors present a novel CS measurement technique based on the cellular automata chaos (CAC) model. The proposed method selects original signal thresholding (OST) as its initial seed to realise CS signal coding. The benefits of C...

In recent years, sparse recognition (SR) has increasingly become an emerging pattern recognition method. Because of its excellent recognition performance for some traditionally difficult problems (such as occluded or corrupted face recognition), several classical SR ideas (such as sparse representation-based classification (SRC) or dictionary-based...

Mutation and natural selection is the core of Darwin's idea about evolution. Many algorithms and models are based on this idea. However, in the evolution of prokaryotes, more and more researches have indicated that horizontal gene transfer (HGT) would be much more important and universal than the authors had imagined. Owing to this mechanism, the p...

High resolution and large field of view are two major development trends in optical remote sensing imaging. But these trends will cause the difficult problem of mass data processing and remote sensor design under the limitation of conventional sampling method. Therefore, we will propose a novel optical remote sensing imaging method based on compres...

In colour compressed sensing (CS) imaging, the current two bottlenecks for application are (1) high computation cost of sparse representation (SR) with over-complete dictionary and (2) unsatisfactory imaging quality of CS recovery with l1-norm minimisation. Thus, this study proposes a novel colour CS imaging framework. In the framework, two improve...

Compressed sensing (CS) is a topic of great interest in many research fields, especially image processing. However, in the traditional CS framework, one disadvantage is that the computational cost of sparse representation (SR) is too high to meet basic application requirements. Another is that l1-norm minimisation, as the object function of CS reco...

There are two major development trends in digital imaging, which are high resolution and large field of view. Because of these trends, mass data processing and sensor design will be caused by the limitation of conventional sampling method. Therefore, we propose a novel multi-scale subfield imaging method based on compressed sensing and fractal clas...

Although a bacterium looks like a simple structure microbe, their family is one of the oldest organisms and ubiquitous in every habitat on Earth. The main reason is the bacterial (or prokaryotes') global gene information sharing mechanism termed as bacterial gene sharing (BGS). Based on the research of BGS and Schrodinger's life entropy theory, we...

This study presents a novel compressive sensing (CS) framework to solve the high dimensional mass spectrometry (MS) signal processing in Bioinformatics. As a hot research topic, CS has attracted a great deal of attention in many fields. In theory, high sparsity is one precondition for any CS framework. However, in Bioinformatics, one application bo...

Basis pursuit (BP) and matching pursuit (MP) are two important basic recovery methods in compressive sensing (CS) research. BP can compute the global optimal solution in CS recovery problem, but its computational complexity is high and dimensional universality (regardless of 1D or 2D or higher dimensions) is not good. On the other side, the computa...

A new compressed sensing (CS) framework is presented for intelligent mass spectrum data processing in this paper. MS sensing data is used to realize the prior MS analysis through compressed sensing recognition (CSR) method. Then, based on the CSR prior knowledge, we propose the concept of sparse difference (SD) to accomplish high quality CS recover...