2021

• Record 109 of
  
  Title:Hardware design of an image acquisition device for target observation and tracking
  
  Author(s):Bian, He(1); Zhang, Haifeng(1); Wang, Hua(1); Huang, Jijiang(1)
  Source: IOP Conference Series: Earth and Environmental Science  Volume: 632  Issue: 4  DOI: 10.1088/1755-1315/632/4/042043  Published: January 13, 2021  
  Abstract:In order to observe and track the separated targets in the air, This paper presents a hardware image acquisition platform based on three-way camera + FPGA + two-way DSP, Xilinx artix-7 series xc7a200t-2fbg676i FPGA is used as the main processor. It is mainly responsible for high-speed image acquisition, preprocessing, transmission and display, TMS320DM368 DSP of Texas Instruments is used as image compression processor. After receiving the image transmitted by artix-7 FPGA, the image H.264 is compressed. This architecture solves the delay problem of traditional image acquisition system in hardware architecture level, and realizes the real-time and high-speed image acquisition and processing. At the same time, the hardware has the basis of multi-channel image acquisition, multi-channel image compression, visible light and infrared camera acquisition data fusion. © 2021 IOP Conference Series: Earth and Environmental Science.
  Accession Number: 20210809938434
• Record 110 of
  
  Title:One-dimensional purely Lee-Huang-Yang fluids dominated by quantum fluctuations in two-component Bose-Einstein condensates
  
  Author(s):Liu, Xiuye(1,2); Zeng, Jianhua(1,2)
  Source: arXiv  Volume:   Issue:   DOI: 10.48550/arXiv.2109.05515  Published: September 12, 2021  
  Abstract:Lee-Huang-Yang (LHY) fluids are an exotic quantum matter dominated purely by quantum fluctuations. Recently, the three-dimensional LHY fluids were observed in ultracold atoms experiments, while their low-dimensional counterparts have not been well known. Herein, based on the Gross-Pitaevskii equation of one-dimensional LHY quantum fluids in two-component Bose-Einstein condensates, we reveal analytically and numerically the formation, properties, and dynamics of matter-wave structures therein. Considering a harmonic trap, approximate analytical results are obtained based on variational approximation, and higher-order nonlinear localized modes with nonzero nodes are constructed numerically. Stability regions of all the LHY nonlinear localized modes are identified by linear-stability analysis and direct perturbed numerical simulations. Movements and oscillations of single localized mode, and collisions between two modes, under the influence of different initial kicks are also studied in dynamical evolutions. The predicted results are available to quantum-gas experiments, providing a new insight into LHY physics in low-dimensional settings. Copyright © 2021, The Authors. All rights reserved.
  Accession Number: 20210318988
• Record 111 of
  
  Title:Research on multi-sensor high dynamic range imaging technology and application
  
  Author(s):Guo, Lulu(1); Yi, Hongwei(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 11850  Issue:   DOI: 10.1117/12.2599254  Published: 2021  
  Abstract:In dynamic scene imaging, multi-sensor high dynamic range (HDR) fusion technology used to solve the ghosting problem of multi-exposure fusion based on camera aperture, and achieve high-quality HDR video imaging. Therefore, it has made significant progress in image capture and synthesis of HDR optical imaging. First, we introduce the development status of multi-sensor based on time bracketing and space bracketing. Then introduce the different method of multi-exposure image fusion, including aligning different exposures, rejecting misalignment information and patch-based optimization. Finally, discuss the key technical issues and development trends of this technology in HDR imaging technology. © 2021 SPIE.
  Accession Number: 20212810623856
• Record 112 of
  
  Title:Expanded Edge Penalty Loss for Salient Object Detection
  
  Author(s):Wang, Nan(1); Shi, Yuetian(1); Fang, Jie(2); Yang, Fanchao(1); Zhang, Geng(1); Li, Siyuan(1); Liu, Xuebin(1)
  Source: 2021 4th International Conference on Information Communication and Signal Processing, ICICSP 2021  Volume:   Issue:   DOI: 10.1109/ICICSP54369.2021.9611977  Published: 2021  
  Abstract:As an indispensable preprocessing technique for image understanding, salient object detection aims to extract interesting regions from an image for subsequent processing, which has attracted much attention since its wide range of applications. Recently, with the rapid development of artificial intelligence and machine learning, deep neural network especially deep convolutional neural network based methods have achieved competitive performances because of their strong feature representation capability. However, most of these methods often suffer from coarse boundaries. The main reason is that equal penalty factor is applied to each pixel in the image to optimize the network, but there are huge distinctions in prediction complexity among different ones actually. Specifically, pixels closer to the boundaries are increasingly difficult because of their huge gaps between structural information and semantic label. In these cases, we present an Expanded Edge Penalty Loss (EPL) for salient object detection. EPL gives bigger penalty factors to pixels distributed in boundary and near-boundary regions, and further dynamically adjusts their contributions to the model optimization. In addition, the experimental results on five public and challenging datasets have validated the superiority and effectiveness of the proposed method. © 2021 IEEE.
  Accession Number: 20220411511204
• Record 113 of
  
  Title:SiamPBN: Point-based Siamese Network for Rotating Objects Tracking
  
  Author(s):Yang, Chen(1); Zhang, Ximing(2); Li, Baopeng(1); Lei, Hao(2); Song, Zongxi(2)
  Source: 2021 7th International Conference on Computer and Communications, ICCC 2021  Volume:   Issue:   DOI: 10.1109/ICCC54389.2021.9674679  Published: 2021  
  Abstract:In recent years, the Siamese network based trackers have achieved outperforming results in the metrics of speed and accuracy in terms of visual tracking. However, it is difficult for the Siamese networks to achieve the accurate location of rotating objects. This paper proposes an efficient network architecture named SiamPBN to resolve rotation problem in tracking. We find that the predicted center of the object deviates from the center of the predicted box while the object rotates continuously. Therefore, we add a centerness head to the network to improve the performance of handling rotating objects. In addition, SiamPBN obtains the predicted outputs by point-based instead of anchor-based method, thus avoiding the complex computation associated with anchors. Our proposed method has gained the excellent performance on the datasets, including GOT-10k, LaSOT and VOT2019. © 2021 IEEE.
  Accession Number: 20220911723600
• Record 114 of
  
  Title:Learning Oculomotor behaviors from scanpath
  
  Author(s):Li, Beibin(1); Nuechterlein, Nicholas(1); Barney, Erin(2); Foster, Claire(3); Kim, Minah(4); Mahony, Monique(2); Atyabi, Adham(5); Feng, Li(6); Wang, Quan(7); Ventola, Pamela(8); Shapiro, Linda(1); Shic, Frederick(9)
  Source: arXiv  Volume:   Issue:   DOI: null  Published: August 11, 2021  
  Abstract:Identifying oculomotor behaviors relevant for eye-tracking applications is a critical but often challenging task. Aiming to automatically learn and extract knowledge from existing eye-tracking data, we develop a novel method that creates rich representations of oculomotor scanpaths to facilitate the learning of downstream tasks. The proposed stimulus-agnostic Oculomotor Behavior Framework (OBF) model learns human oculomotor behaviors from unsupervised and semi-supervised tasks, including reconstruction, predictive coding, fixation identification, and contrastive learning tasks. The resultant pre-trained OBF model can be used in a variety of applications. Our pre-trained model outperforms baseline approaches and traditional scanpath methods in autism spectrum disorder and viewed-stimulus classification tasks. Ablation experiments further show our proposed method could achieve even better results with larger model sizes and more diverse eye-tracking training datasets, supporting the model's potential for future eye-tracking applications. Open source code: http://github.com/BeibinLi/OBF. Copyright © 2021, The Authors. All rights reserved.
  Accession Number: 20210253797
• Record 115 of
  
  Title:Highly Versatile Broadband RF Photonic Fractional Hilbert Transformer Based on a Kerr Soliton Crystal Microcomb
  
  Author(s):Tan, Mengxi(1); Xu, Xingyuan(2); Boes, Andreas(3); Corcoran, Bill(4); Wu, Jiayang(1); Nguyen, Thach G.(3); Chu, Sai T.(5); Little, Brent E.(6); Lowery, Arthur J.(2); Morandotti, Roberto(7,8); Mitchell, Arnan(3); Moss, David J.(1)
  Source: Journal of Lightwave Technology  Volume: 39  Issue: 24  DOI: 10.1109/JLT.2021.3101816  Published: December 15, 2021  
  Abstract:We demonstrate an RF photonic fractional Hilbert transformer based on an integrated Kerr micro-comb source featuring a record low free spectral range of 48.9 GHz, yielding 75 microcomb lines across the C-band. By programming and shaping the comb lines according to calculated tap weights, we demonstrate that theHilbert transformer can achieve tunable bandwidths ranging from 1.2 to 15.3 GHz, switchable centre frequencies from baseband to 9.5 GHz, and arbitrary fractional orders. We experimentally characterize the RF amplitude and phase response of the tunable bandpass and lowpass Hilbert transformers with 90 and 45-degree phase shift. The experimental results show good agreement with theory, confirming the effectiveness of our approach as a powerful way to implement the standard as well as fractional Hilbert transformers with broad and switchable processing bandwidths and centre frequencies, together with high reconfigurability and greatly reduced size and complexity. © 2021 IEEE.
  Accession Number: 20213210745070
• Record 116 of
  
  Title:Atomistic Evidence of Nucleation Mechanism for the Direct Graphite-to-Diamond Transformation
  
  Author(s):Luo, Duan(1); Yang, Liuxiang(2); Xie, Hongxian(3); Srinivasan, Srilok(1); Tian, Jinshou(4); Sankaranarayanan, Subramanian(1); Arslan, Ilke(5); Yang, Wenge(2); Mao, Ho-Kwang(2); Wen, Jianguo(5)
  Source: Research Square  Volume:   Issue:   DOI: 10.21203/rs.3.rs-1091313/v1  Published: December 2, 2021  
  Abstract:The direct graphite-to-diamond transformation mechanism has been a subject of intense study and remains debated concerning the initial stages of the conversion, the intermediate phases, and their transformation pathways. Here, we successfully recover samples at early conversion stage by tuning high-pressure/high-temperature conditions and reveal direct evidence supporting the nucleation-growth mechanism. Atomistic observations show that intermediate orthorhombic graphite phase mediates the growth of diamond nuclei. Furthermore, we observe that quenchable orthorhombic and rhombohedra graphite are stabilized in buckled graphite at lower temperatures. These intermediate phases are further converted into hexagonal and cubic diamond at higher temperatures following energetically favorable pathways in the order: graphite -> orthorhombic graphite -> hexagonal diamond, graphite -> orthorhombic graphite -> cubic diamond, graphite -> rhombohedra graphite -> cubic diamond. These results significantly improve our understanding of the transformation mechanism, enabling the synthesis of different high-quality forms of diamond from graphite. © 2021, CC BY.
  Accession Number: 20220148402
• Record 117 of
  
  Title:Serial-parallel multi-scale feature fusion for anatomy-oriented hand joint detection
  
  Author(s):Li, Bin(1); Fu, Hong(2); Li, Ruimin(3); Wang, Wendi(4)
  Source: arXiv  Volume:   Issue:   DOI: null  Published: February 19, 2021  
  Abstract:Accurate hand joints detection from images is a fundamental topic which is essential for many applications in computer vision and human computer interaction. This paper presents a two-stage network for hand joints detection from single unmarked image by using serial-parallel multi-scale feature fusion. In stage I, the hand regions are located by a pre-trained network, and the features of each detected hand region are extracted by a shallow spatial hand features representation module. The extracted hand features are then fed into stage II, which consists of serially connected feature extraction modules with similar structures, called "multi-scale feature fusion" (MSFF). A MSFF contains parallel multi-scale feature extraction branches, which generate initial hand joint heatmaps. The initial heatmaps are then mutually reinforced by the anatomic relationship between hand joints. The experimental results on five hand joints datasets show that the proposed network overperforms the state-of-the-art methods. © 2021, CC BY-NC-SA.
  Accession Number: 20210062335
• Record 118 of
  
  Title:Multispectral Images Deblurring via Interchannel Correlation Relationship
  
  Author(s):Shi, Yuetian(1); Wang, Nan(1); Yang, Fanchao(1); Zhang, Geng(1); Li, Siyuan(1); Liu, Xuebin(1)
  Source: 2021 4th International Conference on Information Communication and Signal Processing, ICICSP 2021  Volume:   Issue:   DOI: 10.1109/ICICSP54369.2021.9611913  Published: 2021  
  Abstract:Image blur is very common in multispectral images, especially out-of-focus blur when the multispectral cameras are well focused on a specific channel. Therefore, it is important to recover the latent clear images from the blurred image. Many researchers have proposed a large number of methods for deblurring multispectral images. These algorithms assume that the relationship between channels is consistent. In fact, the relationship between different channels in multispectral images suffers from different blurring. Therefore it needs different processing for different channels. We propose a joint spatial and spectral filtering algorithm for multispectral images deblurring. We have introduced an adaptive Gaussian distribution as a constraint relationship between channels, which can effectively deblur the multispectral images. Extensive experiments show that our method achieves state-of-the-art results. © 2021 IEEE.
  Accession Number: 20220411511779
• Record 119 of
  
  Title:Research on dynamic range analysis and improvement of imaging equipment
  
  Author(s):Wang, Hao(1); Huo, Youhui(1); Zhang, Hongbo(2)
  Source: ACM International Conference Proceeding Series  Volume:   Issue:   DOI: 10.1145/3456389.3456392  Published: March 12, 2021  
  Abstract:This paper proposes a dynamic range model and algorithm that analyzes several key factors that affect the dynamic range of imaging equipment. Through this model and algorithm, we analyze several modules that affect the dynamic range of the system, including sensor noise, AD conversion noise, analog gain, digital gain and mapping, and give the quantitative relationships which are used to guide designers to design high performance dynamic range imaging equipment. According to the model and algorithm, a high performance dynamic range imaging equipment can be designed. A hardware extension method based on multi-slope integration is proposed, and the experimental results show that this method is an effective dynamic range expansion method. © 2021 ACM.
  Accession Number: 20212510538378
• Record 120 of
  
  Title:Design of solar observation electronics system for space application
  
  Author(s):Yao, Pei(1,2); Zhu, Bo(1); Li, Chuang(1); Wang, Hong(1); Dai, HaoBin(1,2); Yang, Yang(1)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 12069  Issue:   DOI: 10.1117/12.2606581  Published: 2021  
  Abstract:Space-based solar observation has severe requirements for resolution, dynamic range, and signal-To-noise ratio of the camera. In order to acquire high-quality solar image data, this paper proposes a high-resolution electronics system based on Gpixel GSENSE6060 image sensor for space-based solar observation. The system uses XILINX XQ5VFX130T as the timing control of the overall system, with DDR SDRAM to cache the image data, which can realize flexible working mode with the windowing mode of the sensor. Firstly, the principle of system parameter selection are given, and the work characteristics of GSENSE6060 are described, then the triggering and termination of event mode are realized by algorithm. The system has high flexibility and reliability, which is suitable for long-Time Full-Disk observation and solar eruptions monitoring. During the flare eruption, a high frame rate acquisition with a resolution of 1024 × 1024 can be realized every 4s for the eruption region, which can be used to acquisition the maximum effective data. Experiments show that the system readout noise is better than 6 e-, in Rolling HDR mode can synthesize 16-bit, resolution of 4608 × 4608 and dynamic range larger than 90dB images, to meet the system design index. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
  Accession Number: 20220211444596