Robust visual tracking via CAMShift and structural local sparse appearance model

This paper addresses issues in visual tracking where videos contain object intersections, pose changes, occlusions, illumination changes, motion blur, and similar color distributed background. We apply the structural local sparse representation method to analyze the background region around the target. After that, we reduce the probability of prominent features in the background and add new information to the target model. In addition, a weighted search method is proposed to search the best candidate target region. To a certain extent, the weighted search method solves the local optimization problem. The proposed scheme, designed to track single human through complex scenarios from videos, has been tested on some video sequences. Several existing tracking methods are applied to the same videos and the corresponding results are compared. Experimental results show that the proposed tracking scheme demonstrates a very promising performance in terms of robustness to occlusions, appearance changes, and similar color distributed background.     

Distinguishing and quantification of the human visual pathways using high-spatial-resolution diffusion tensor tractography

Quantification of the living human visual system using MRI methods has been challenging, but several applications demand a reliable and time-efficient data acquisition protocol. In this study, we demonstrate the utility of high-spatial-resolution diffusion tensor fiber tractography (DTT) in reconstructing and quantifying the human visual pathways. Five healthy males, age range 24–37 years, were studied after approval of the institutional review board (IRB) at The University of Texas Health Science Center at Houston. We acquired diffusion tensor imaging (DTI) data with 1-mm slice thickness on a 3.0-Tesla clinical MRI scanner and analyzed the data using DTT with the fiber assignment by continuous tractography (FACT) algorithm. By utilizing the high-spatial-resolution DTI protocol with FACT algorithm, we were able to reconstruct and quantify bilateral optic pathways including the optic chiasm, optic tract, optic radiations free of contamination from neighboring white matter tracts.     

不断向自然与金属冶金学习的高分子加工

总结了高分子材料加工的发展趋势及发展历程,并指出过去很多加工新技术的出现都得益于从自然现象及其他材料行业中获得很好的借鉴,如从蜘蛛吐丝发展出溶液纺丝成型、从玻璃吹制发展出吹塑成型、从金属锻造发展出压延成型及固相拉拔成型等;随后针对生物基可生物降解的立构复合型聚乳酸难以采用传统熔融加工方法成型的问题,借鉴金属粉末冶金加工的思路,提出了一种通过低温烧结制备高性能立构复合型聚乳酸制品的新方法.通过这种加工方法不仅可以有效解决立构复合型聚乳酸在熔融加工过程中熔体稳定性差、易降解的问题,而且可以制得耐热性好、光学透明度高、耐水解降解性佳、综合力学性能优异的高性能聚乳酸制品.     

Saliency4ASD: Challenge,dataset and tools for visual attention modeling for autism spectrum disorder

The recent studies showing that gaze features can be useful in the identification of Autism Spectrum Disorder (ASD), have opened a new domain where Visual Attention (VA) modeling could be of great help. In this sense, this paper presents a report of the Grand Challenge “Saliency4ASD: Visual attention modeling for Autism Spectrum Disorder”, organized at IEEE ICME’19, aiming at supporting the research on VA modeling towards this healthcare societal challenge. In particular, this paper describes the workflow, obtained results, and datasets and tools that were used within this activity, in order to help on the development and evaluation of two types of VA models: (1) to predict saliency maps that fit gaze behavior of people with ASD, and (2) to identify individuals with ASD from typical development.     

Comprehensive performance analysis of objective quality metrics for digital holography

Objective quality assessment of digital holograms has proven to be a challenging task. While prediction of perceptual quality of the recorded 3D content from the holographic wavefield is an open problem; perceptual quality assessment from content after rendering, requires a time-consuming rendering step and a multitude of possible viewports. In this research, we use 96 Fourier holograms of the recently released HoloDB database to evaluate the performance of well-known and state-of-the-art image quality metrics on digital holograms. We compare the reference holograms with their distorted versions: (i) before rendering on the real and imaginary parts of the quantized complex-wavefield, (ii) after converting Fourier to Fresnel holograms, (iii) after rendering, on the quantized amplitude of the reconstructed data, and (iv) after subsequently removing speckle noise using a Wiener filter. For every experimental track, the quality metric predictions are compared to the Mean Opinion Scores (MOS) gathered on a 2D screen, light field display and a holographic display. Additionally, a statistical analysis of the results and a discussion on the performance of the metrics are presented. The tests demonstrate that while for each test track a few quality metrics present a highly correlated performance compared to the multiple sets of available MOS, none of them demonstrates a consistently high-performance across all four test-tracks.     

离散傅里叶变换误差分析与参数设置

离散傅里叶变换( Discrete Fourier Transform,DFT) 是数字信号处理教学的重点和难点,其参数设置的正确与否直接影响信号频谱分析的准确性。本文对连续与离散周期信号、非周期信号分别进行DFT运算,从時域和频域角度分析实际频谱与理想频谱之间的误差。通过MATLAB仿真,加深学生对DFT的理解,引导学生正确设置DFT参数。     

IR saliency detection via a GCF-SB visual attention framework

Infrared (IR) saliency detection with high detection accuracy is a challenging task due to the complex background and low contrast of IR images. In this paper, an IR saliency detection method via a new visual attention framework is proposed, which comprises two phases. In the first phase, a Gray & Contrast Features (GCF) model is established, in which the IR image is processed in two feature channels, a gray feature channel and a contrast feature channel. And then a primary feature map can be obtained by fusing the gray and contrast features from these two channels, which is the basis of the second phase. In the second phase, a Similarity-based Bayes (SB) model is established, in which two prior probabilities and two likelihood functions are calculated according to the previously obtained primary feature map. Finally, the saliency map is calculated with the obtained prior probabilities and likelihood functions by Bayes formula. Experimental results indicate that the proposed method can effectively reduce noise and enhance contrast of IR images with complex background and low contrast, and obtain a higher detection accuracy and robustness than seven state-of-the-art methods.     

“Photoshop图形图像处理技术”教学中应用项目教学法的实践

随着我国社会经济的发展,教育事业不断完善。为了不断提高我国的教育水平,高校正在逐步改善教育内容、教育理念、教育方法等,项目教学法是主要的教学方法之一。与以往的教学方法不同,项目教学法提倡以学生为主体,注重学生自身的综合能力,促进教育水平的提高。文章主要分析了"Photoshop图形图像处理技术"的教学,简述了PBL在教学应用中的特点,希望能为PBL未来的应用提供一定的帮助。     

An efficient inexact Full Adder cell design in CNFET technology with high-PSNR for image processing

The design of inexact circuits at the transistor level remarkably improves figures of merits such as power consumption, delay, energy, and area. Therefore, inexact technique for designing circuits has attracted the attention of researchers worldwide. Designing inexact Full Adder cell as a building block of a variety of arithmetic circuits can affect the entire electronic system’s performance. In this paper, two novel inexact 1-bit Full Adder cells are presented using carbon nanotube field effect transistors (CNFETs). The capacitive threshold logic (CTL) is used to realize the proposed cells. Comprehensive simulations at two levels of abstraction, i.e., application and hardware are carried out to evaluate the efficacy of these circuits. First, the motion detector which is one of the image processing applications is deployed in MATLAB software to measure peak signal-to-noise ratio (PSNR) figure of merit. At hardware level, the HSPICE tool is used to carry out simulations and measure power, delay, power-delay product (PDP), energy-delay product (EDP), power-delay-area product (PDAP) and power-delay-area-PSNR product (PDAPP). Simulation results confirmed the superiority of the proposed Full Adder cells compared to others. For instance, the proposed 6TIFA improves PDAPP metric at least 21% and at most 76% compared to its counterparts at 0.9V power supply.