检索结果-内蒙古大学图书馆

Millimeter-wave radar image analysis for the traffic sensing

Journal of Physics: Conference Series 2020年第5期1507卷

作者： H M Wu F Qi J K Wang Y Wang School of communication science and engineering Northeastern University Liaoning Province Shenyang 110819 China Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences China Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang 110016 China

Millimeter-wave(MMW) radar sensing is one of the most promising technologies to provide safe navigation for autonomous vehicles due to its expected high-resolution imaging capability However, driverless cars have higher request for different environment and light conditions. Therefore, millimetre-wave imaging is of paramount importance for complex load scenario. In this paper, we have built models of pavement pits and bulges and analysed their with differences ways of antennas. A comparison of the imaging performance of experimental systems operating at a MMW radar and a Lidar is presented with the analysis of features for initial image interpretation Experimental images of the complex road surface are made by a 94GHz frequency-modulated continuous-wave (FMCW) radar technique with 3mm wavelength.

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A Novel LOS Rate Estimation Method Based on images for Strap-down Inertial Guidance

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Journal of Physics: Conference Series 2020年第1期1570卷

作者： Zheng Xu Haibo Luo Bin Hui Zheng Chang Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Tel.: +86-024-2397-0757 Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang 110016 China University of Chinese Academy of Sciences Beijing 100049 China Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Science Shenyang 110016 China The Key Lab of Image Understanding and Computer Vision Shenyang 110016 China

With the development of technology, precision guided weapon is becoming more and more important in modern war. In order to launch our recent guidance system on medium and small guided weapons, we propose a method to obtain the LOS rate by combining information from both camera and gyroscope. To be specific, we firstly calculate the body LOS angle through transforming the image pixel coordinate system into the image physical coordinate system according to camera internal parameters; then subtract the missile motion information contained in the measurement signal of the seeker and finally the LOS rate is deduced. Comparing with traditional gimballed seekers, our strap-down seekers with camera have significantly reduced costs and influences caused by external environments on platform.

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Stereo matching algorithm based on the combination of matching costs 7

Stereo matching algorithm based on the combination of matchi...

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7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017

作者： Ende, Wang Yalong, Zhu Liangyu, Peng Yijun, Li Tianyao, Wu Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Opto-Electronic Information Processing CAS Shenyang110016 China Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang110016 China College of Electrical Engineering Yanshan University Qinhuangdao066004 China School of Metallurgy Northeastern University Shenyang110819 China

ISBN: (纸本)9781538604892

Aiming at solving the problem of low accuracy of weak texture region and disparity discontinuous region and sensitivity to illumination caused by existing local stereo matching algorithm, a new stereo matching algorithm based on the combination of Sum of Absolute Difference algorithm and Absolute Difference of Gradient algorithm is presented here. Using the average of the pixels in the disparity range to apply adaptive weight to the SAD part. The new algorithm can adaptively adjust each part of the cost function in the proportion of the total cost function according to the different texture, illumination characteristics of image. Moreover, we use the semiglobal matching algorithm to calculate the cost of 8 directions, to carry out optimized processing on disparity image, finally a dense disparity map is obtained. The experimental results shows that the proposed method not only improve accuracy of stereo matching, but also has well results in weak texture region and disparity discontinuous region. © 2017 IEEE.

关键词： Textures

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Adversarial learning of structure-aware fully convolutional networks for landmark localization

arXiv

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arXiv 2017年

作者： Chen, Yu Shen, Chunhua Chen, Hao Wei, Xiu-Shen Liu, Lingqiao Yang, Jian Key Lab of Intelligent Perception and Systems High-Dimensional Information of Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security Nanjing University of Science and Technology School of Computer Science University of Adelaide Australian Centre for Robotic Vision Department of Computer Science and Technology Nanjing University

Landmark/pose estimation in single monocular images has received much effort in computer vision due to its important applications. It remains a challenging task when input images come with severe occlusions caused by, e.g., adverse camera views. Under such circumstances, biologically implausible pose predictions may be produced. In contrast, human vision is able to predict poses by exploiting geometric constraints of landmark point inter-connectivity. To address the problem, by incorporating priors about the structure of pose components, we propose a novel structure-aware fully convolutional network to implicitly take such priors into account during training of the deep network. Explicit learning of such constraints is typically challenging. Instead, inspired by how human identifies implausible poses, we design discriminators to distinguish the real poses from the fake ones (such as biologically implausible ones). If the pose generator G generates results that the discriminator fails to distinguish from real ones, the network successfully learns the priors. Training of the network follows the strategy of conditional Generative Adversarial Networks (GANs). The effectiveness of the proposed network is evaluated on three pose-related tasks: 2D human pose estimation, 2D facial landmark estimation and 3D human pose estimation. The proposed approach significantly outperforms several state-of-the-art methods and almost always generates plausible pose predictions, demonstrating the usefulness of implicit learning of structures using GANs. Copyright © 2017, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Improved Kernel Correlation Filter Tracking with Gaussian scale space

Improved Kernel Correlation Filter Tracking with Gaussian sc...

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International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.12 Infrared Technology and Application

作者： Shukun Tan Yunpeng Liu Yicui Li Shenyang Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Science The Key Lab of Image Understanding and Computer Vision

Visual tracking is one of the most challenging tasks in the field of computer vision and is related to a wide range of applications like surveillance and robotics. Tracking-by-detection methods are wi

ISBN: (纸本)9781510607729

关键词： visual tracking kernel correlation filter Gaussian scale space bilinear interpolation Mean Absolute Difference visual tracking bilinear interpolation images absolute difference imagery (Psychotherapy) Gauss Scale formation scale parameter Targets image Seeds jigs(templates) scales Scale

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Dehazed image Quality Assessment by Haze-Line Theory

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Journal of Physics: Conference Series 2017年第1期844卷

作者： Yingchao Song Haibo Luo Rongrong Lu Junkai Ma Shenyang Institute of Automation CAS Shenyang 110016 China University of Chinese Academy of Sciences Beijing 100049 China Key Laboratory of Opto-Electronic Information Processing CAS Shenyang 110016 China The Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang 110016 China

images captured in bad weather suffer from low contrast and faint color. Recently, plenty of dehazing algorithms have been proposed to enhance visibility and restore color. However, there is a lack of evaluation metrics to assess the performance of these algorithms or rate them. In this paper, an indicator of contrast enhancement is proposed basing on the newly proposed haze-line theory. The theory assumes that colors of a haze-free image are well approximated by a few hundred distinct colors, which form tight clusters in RGB space. The presence of haze makes each color cluster forms a line, which is named haze-line. By using these haze-lines, we assess performance of dehazing algorithms designed to enhance the contrast by measuring the inter-cluster deviations between different colors of dehazed image. Experimental results demonstrated that the proposed Color Contrast (CC) index correlates well with human judgments of image contrast taken in a subjective test on various scene of dehazed images and performs better than state-of-the-art metrics.

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Violent Interaction Detection in Video Based on Deep Learning

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Journal of Physics: Conference Series 2017年第1期844卷

作者： Peipei Zhou Qinghai Ding Haibo Luo Xinglin Hou Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 University of Chinese Academy of Sciences Beijing 100049 Key Laboratory of Opto-Electronic Information Processing CAS Shenyang 110016 The Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang 110016 Space star technology co. LTD Beijing 100086

Violent interaction detection is of vital importance in some video surveillance scenarios like railway stations, prisons or psychiatric centres. Existing vision-based methods are mainly based on hand-crafted features such as statistic features between motion regions, leading to a poor adaptability to another dataset. En lightened by the development of convolutional networks on common activity recognition, we construct a FightNet to represent the complicated visual violence interaction. In this paper, a new input modality, image acceleration field is proposed to better extract the motion attributes. Firstly, each video is framed as RGB images. Secondly, optical flow field is computed using the consecutive frames and acceleration field is obtained according to the optical flow field. Thirdly, the FightNet is trained with three kinds of input modalities, i.e., RGB images for spatial networks, optical flow images and acceleration images for temporal networks. By fusing results from different inputs, we conclude whether a video tells a violent event or not. To provide researchers a common ground for comparison, we have collected a violent interaction dataset (VID), containing 2314 videos with 1077 fight ones and 1237 no-fight ones. By comparison with other algorithms, experimental results demonstrate that the proposed model for violent interaction detection shows higher accuracy and better robustness.

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High Dynamic Range Imaging Using Multiple Exposures

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Journal of Physics: Conference Series 2017年第1期844卷

作者： Xinglin Hou Haibo Luo Peipei Zhou Wei Zhou Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 University of Chinese Academy of Sciences Beijing 100049 Key Laboratory of Opto-Electronic Information Processing CAS Shenyang 110016 The Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang 110016 AVIC Jiangxi HONGDU Aviation Industry Group LTD Nanchang China

It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range (LDR) camera. This paper presents an approach for improving the dynamic range of cameras by using multiple exposure images of same scene taken under different exposure times. First, the camera response function (CRF) is recovered by solving a high-order polynomial in which only the ratios of the exposures are used. Then, the HDR radiance image is reconstructed by weighted summation of the each radiance maps. After that, a novel local tone mapping (TM) operator is proposed for the display of the HDR radiance image. By solving the high-order polynomial, the CRF can be recovered quickly and easily. Taken the local image feature and characteristic of histogram statics into consideration, the proposed TM operator could preserve the local details efficiently. Experimental result demonstrates the effectiveness of our method. By comparison, the method outperforms other methods in terms of imaging quality.

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An anti-interference reconstruction algorithm of image compression based on compressed sensing

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Guangdianzi Jiguang/Journal of Optoelectronics Laser 2014年第5期25卷 1003-1009页

作者： Du, Mei Zhao, Huai-Ci Zhao, Chun-Yang Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Key Lab. of Image Understanding and Comput. Vision of Liaoning Province Shenyang Inst. of Automation Shenyang 110016 China Graduate School of Chinese Academy of Sciences Beijing 100049 China

When the images compressed by traditional transformation compression algorithms are transmitted over wireless channels, if Gaussian random interference causes the loss of the crucial transformation coefficients, the contents of the reconstructed images will be lost obviously and this will reduce the accuracy of the subsequent detection and recognition results greatly. In order to solve this problem, based on the characteristics of equal importance about each compressed sensing component, this paper first analyzes the feasibility of resisting the interference by removing the distorted compressed sensing signal components, then proposes an anti-interference image reconstruction algorithm. This algorithm first confirms the new compressed sensing signals and the new reconstruction matrix based on the locations of the corresponding compressed sensing signal components of the Gaussian-interfered bits, and then reconstructs the original images employing the iterative threshold algorithm. The simulation results demonstrate that our algorithm can reconstruct exact images at low bit error rates, and inexact images whose qualities are slightly lowered without loss of local contents at high bit error rates. As a result, our algorithm can overcome the deficiency in anti-interference ability of transformation compression algorithms and the iterative threshold algorithm, thus proposes a feasible scheme for the anti-interference problem that arises in wireless image transmission.

关键词： image reconstruction

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A legible method for fluid cavity detection in ultrasound image

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2013 International Conference on Energy Research and Power Engineering, ERPE 2013

作者： Guo, De Quan Yang, Hong Yu Zhang, Zhi Jie Liu, Dong C. Key Lab. of Fundamental Synthetic Vision Graphics and Image Sci. for National Defense Sichuan University Chengdu 610065 China Neijiang Vocational and Technical College Neijiang Sichuan 641100 China College of Computer science Sichuan University Chengdu 610065 China

ISBN: (纸本)9783037857588

We present a novel method to modulate influence of diffuse scattering in fluid cavity and reflection at boundary of pulse-echo ultrasound image. A simplified formation of ultrasound model is used to delineate it, and which is merged with modified dehaze model from principle of ultrasonic imaging, a legible fluid cavity in vascular or amniotic fluid of ultrasound image is obtained. Local and global characteristics of the image are utilized to adjust diffuse in different levels. Experimental results indicate that the proposed method is capable of producing ultrasound images that have better image quality and greater fidelity to the true tissue reflectivity. © (2013) Trans Tech Publications, Switzerland.

关键词： Ultrasonic imaging

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