Visual Speech Recognition with Lightweight Psychologically Motivated Gabor Features

Extraction of relevant lip features is of continuing interest in the visual speech domain. Using end-to-end feature extraction can produce good results, but at the cost of the results being difficult for humans to comprehend and relate to. We present a new, lightweight feature extraction approach, motivated by human-centric glimpse-based psychological research into facial barcodes, and demonstrate that these simple, easy to extract 3D geometric features (produced using Gabor-based image patches), can successfully be used for speech recognition with LSTM-based machine learning. This approach can successfully extract low dimensionality lip parameters with a minimum of processing. One key difference between using these Gabor-based features and using other features such as traditional DCT, or the current fashion for CNN features is that these are human-centric features that can be visualised and analysed by humans. This means that it is easier to explain and visualise the results. They can also be used for reliable speech recognition, as demonstrated using the Grid corpus. Results for overlapping speakers using our lightweight system gave a recognition rate of over 82%, which compares well to less explainable features in the literature.     

一种新的磁共振图像处理流水线的设计与实现

磁共振图像的重建、后处理及可视化是磁共振成像（MRI）系统的重要组成部分.本文开发了一个新的用于磁共振图像重建、后处理及可视化的开源框架YAP（Yet Another Pipeline），利用此框架可以方便地构建图像处理流水线.与现有的一些其他开源框架相比，本文开发的框架具有如下特点：（1）采用基于接口的设计，可使用基于接口的插件对流水线的功能进行扩展；（2）允许用户使用编写脚本的方式构建图像处理流水线，编辑与修改流水线都很方便；（3）支持带有分支结构的流水线，便于流水线的构建与调试.目前，该框架已经在商用系统中获得了应用.     

Two-scale image fusion of visible and infrared images using saliency detection

Military, navigation and concealed weapon detection need different imaging modalities such as visible and infrared to monitor a targeted scene. These modalities provide complementary information. For better situation awareness, complementary information of these images has to be integrated into a single image. Image fusion is the process of integrating complementary source information into a composite image. In this paper, we propose a new image fusion method based on saliency detection and two-scale image decomposition. This method is beneficial because the visual saliency extraction process introduced in this paper can highlight the saliency information of source images very well. A new weight map construction process based on visual saliency is proposed. This process is able to integrate the visually significant information of source images into the fused image. In contrast to most of the multi-scale image fusion techniques, proposed technique uses only two-scale image decomposition. So it is fast and efficient. Our method is tested on several image pairs and is evaluated qualitatively by visual inspection and quantitatively using objective fusion metrics. Outcomes of the proposed method are compared with the state-of-art multi-scale fusion techniques. Results reveal that the proposed method performance is comparable or superior to the existing methods.     

刀锋伪影校正技术在精神疾病患者海马MRI检查中的应用

为探讨磁共振刀锋伪影校正（BLADE）技术提升精神疾病患者海马磁共振图像质量的效果，本文分别使用结合了BLADE技术的BLADE T₂WI TSE、BLADE T₂WI FLAIR及传统T₂WI TSE、T₂WI FLAIR四种序列，对47例精神疾病患者和美国放射学院（ACR）标准模体在3.0 T磁共振成像（MRI）设备上分别进行常规海马斜冠状位扫描和ACR标准检测.患者的磁共振图像由2名放射科医师采用5分法对运动伪影、搏动伪影、颗粒度、海马磁共振图像质量进行评价，并应用Wilcoxon符号秩检验进行数据分析.模体图像通过识别图像的钻孔阵列和轮辐的数目，半定量评价各序列的高对比空间分辨力（HCSR）和低对比物体探测能力（LCD）.结果表明相比传统序列，结合BLADE技术的序列能够明显改善海马磁共振图像的运动伪影、搏动伪影（p<0.001），提高图像质量（p<0.05）；但在图像颗粒度方面，传统序列表现更优（p<0.001）.ACR模体半定量分析显示，结合BLADE技术序列与传统序列相比，在LCD检测方面结果更优、在HCSR检测方面结果相同或略逊.本文推荐将BLADE技术应用于不合作的精神疾病患者海马的MRI检查.     

A new class of conformable spectral observers for signal reconstruction

In this work, the design of spectral observers for signal reconstruction based on Kalman filters is performed and evaluated. The conformable derivative and the beta‐derivative were used to design the Kalman filters. Both derivatives satisfy the same formulas of the classical derivation, eg, the chain rule. The derivative order, the Ricatti equation parameters, and the observers tuning parameters were optimized using an optimization algorithm based on the bat's echolocation behavior (Bat algorithm). The simulation results showed the advantages of using the proposed observers for the signal reconstruction.     

A high accuracy flow segmentation method in crowded scenes based on streakline

Flow segmentation based on similar motion patterns in crowded scenes remains an open problem in computer vision due to inherent complexity and vast diversity found in such scenes. To solve this problem, the streakline framework based on Lagrangian fluid dynamics had been proposed recently. However, this framework computed optical flow field using conventional optical flow method (Lucas Kanade method) which has poor anti-interference performance, and serious deviation would be brought to the computation of optical flow field. Moreover, our experimental results show that using the formulation of streak flow similarity in this framework can result in incorrect flow segmentation. Therefore, we combine this framework with a high accurate variational model, and modify the corresponding formulation of streak flow similarity after analyzing the streakline framework in detail. Finally, an improved method is proposed to solve flow segmentation in crowded scenes. Experiments are done to compare these two methods and results verify the validity and accuracy of our method.     

Fingerprint image enhancement using data driven Directional Filter Bank

A new method based upon data driven tool, principal component analysis (PCA), for fingerprint enhancement is proposed in this paper. PCA is a very useful statistical technique that has found application in many different fields like image compression, face recognition and is commonly used for finding patterns in data of high dimension. In the proposed method, the input image is first decomposed into directional images using decimation free Directional Filter Bank (DDFB). Then these directional images are normalized. A data driven technique PCA is applied to these normalized directional fingerprint images, which gives the PCA filtered images. These are basically directional images. Then these directional images are reconstructed into one image which is the enhanced one. Simulation results are included illustrating the capability of the proposed method.     

Experimental investigation of the effect of temperature on the strength of polyimide contact structures

A new photogrammetry based measurement technique for contact areas in line contact structures is developed. From the data collected by this technique, a method for measuring the contact strength of contact structures in high temperature applications is proposed. The contact strength of a line contact structure of polyimide at different temperatures is measured; the results show that the increase in temperature decreases the contact strength of the structure. The effect of temperature on the contact strength is studied by investigating the occurrence and evolution of yielding core within the structure at different temperatures. The decrease in the yield strength and elastic modulus of the polyimide material at high temperature induces core yielding at lower loads and eases the propagation of core yielding to the surface.