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Scale Adaptive Block Target Tracking Based on Multi-layer Convolution Features and Kernel Correlation Filter

Journal of Physics: Conference Series 2021年第1期1828卷

作者： Ting Zhang Dong Hu Jing Zhang Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing 210003 China Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing 210003 China Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing 210003 China

Target tracking is currently a hot research topic in Computer Vision and has a wide range of use in many research fields. However, due to factors such as occlusion, fast motion, blur and scale variation, tracking method still needs to be deeply studied. In this paper, we propose a block target tracking method based on multi-convolutional layer features and Kernel correlation filter. Our method divides the tracking process into two parts: target position estimation and target scale estimation. First, we block the target frame based on the condition number. Second, we extract the features by the convolutional layer and apply it to the kernel correlation filter to get the center position of different block targets. With the reliability of different blocks measured by the Barker coefficient, the overall target position center is obtained. Then, the affine transformation is adopted to achieve the scale adaptation. The algorithm in this paper is evaluated by the public video sequences in OTB-2013. Numerous experimental results demonstrate that the proposed tracking method can achieve target scale adaptation and effectively improve the tracking accuracy.

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Anchored Neighborhoods Search Based on Global Dictionary Atoms for Face Photo-Sketch Synthesis

Anchored Neighborhoods Search Based on Global Dictionary Ato...

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2019第十一届数字图像处理国际会议

作者： Feng Liu Ran Xu Jieying Zheng Qiuli Lin Zongliang Gan College of Educational Science and Technology Nanjing University of Posts and Telecommunications Jiangsu Province Key Lab on Image Processing & Image Communications Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications

Example-based face sketch synthesis technology generally requires face photo-sketch images with face alignment and size *** break through the limitation,we propose a global face sketch synthesis method:In training,all training photo-sketch patch pairs are collected together and a photo feature dictionary is learned from the photo *** each atom of the dictionary,its K closest photo-sketch patch pairs are clustered,namely "Anchored Neighborhood".In testing,for each test photo patch,we search its nearest photo patch in the Anchored Neighborhood determined by its closest atom,then the corresponding sketch patch is the *** the same way,we train and test in the high-frequency domain and synthesis the high-frequency ***,the fusion of the initial and the high-frequency results is the final *** experiments on three public face sketch datasets and various real-world photos demonstrate the effectiveness and robustness of the proposed method.

关键词： Face sketch synthesis Dictionary learning Dictionary atom Anchored neighborhood image patch

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Vehicle Color Recognition Based on Superpixel Features

Vehicle Color Recognition Based on Superpixel Features

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2019第十一届数字图像处理国际会议

作者： Qiuli Lin Feng Liu Qiang Zhao Ran Xu Jiangsu Province Key Lab on Image Processing & Image Communications Nanjing University of Posts and Telecommunications College of Educational Science and Technology Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications

In this paper,a novel methodology is presented to settle the region of interest(ROI) detection problem in vehicle color recognition so as to remove the redundant components of vehicles that interfere greatly with color *** order to make full use of the local color and spatial information,vehicle images are divided into different superpixels at *** spatial relationship between superpixels and the outermost pixels is then used for the background removal of vehicle *** comparing with the vehicle window clustering centroids obtained by k-means,the superpixels close to the universal color characteristics of windows are removed so that the dominant color superpixels are ***,a linear Support Vector Machine classifier is trained for color *** experiments demonstrate that the proposed methodology is effective for color region of interest detection and thus contribute to vehicle color recognition.

关键词： vehicle color recognition region of interest superpixel universal color characteristics Support Vector Machine

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Angle Independent Fano Resonances in Bioinspired Nanostructured Fabry-Pérot sensors

Angle Independent Fano Resonances in Bioinspired Nanostructu...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Daniel Assumpcao Radwanul Siddique Vinayak Narasimhan Hyuck Choo 1200 E. California Blvd. MC 136-93 California Institute of Technology Pasadena California USA Image Sensor Lab Samsung Advanced Institute of Technology (SAIT) Samsung Semiconductor Inc. 2 N Lake Ave #240Pasadena CA USA Device Lab Device & System Research Center Samsung Advanced Institute of Technology (SAIT) Suwon Republic of Korea

The utility of Fabry-Pérot based optical sensors is limited by their poor readout angle. We numerically demonstrate that adding bioinspired short-range-order nanostructuring to these devices leads to angle-indepe... 详细信息

ISBN: (数字)9781728143330

ISBN: (纸本)9781728152394

关键词： Nanopatterning Interference Lasers and electrooptics Biomembranes Nanoscale devices Fabry-Perot Optical sensors

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A Siamese Network Tracking Algorithm Based on Hierarchical Attention Mechanism

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Journal of Physics: Conference Series 2021年第1期1828卷

作者： Hu Zhang Dong Hu Yingcan Qiu Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing 210003 China Nanjing University of Posts and Telecommunications Nanjing 210003 China Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing 210003 China Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Nanjing 210003 China

A siamese network tracking algorithm based on hierarchical attention mechanism is proposed in this paper. In order to obtain more robust target tracking results, different layer features are fused effectively. In the process of extracting features, attention mechanism is used to recalibrate the feature map, and AdaBoost algorithm is used to weight the target feature map, which improves the reliability of the response map. Besides, the Inception module is also introduced which not only increases the width of the network and the adaptability of the siamese network to the scale, but also reduces the parameters and improves the speed of network training. Experimental results show that this method can effectively solve the impact of background clutter and improve the accuracy of tracking.

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Vehicle Precise Retrieval via Color image Retrieval Method Based on Improved Fast-Match 10

Vehicle Precise Retrieval via Color Image Retrieval Method B...

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10th International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Liu, Feng Wang, Yue Wei, Jian Gan, Zongliang Cui, Ziguan Nanjing Univ Posts & Telecommun Coll Educ Sci & Technol Nanjing Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Jiangsu Prov Key Lab Image Proc & Image Commun Nanjing Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Minist Educ Key Lab Broadband Wireless Commun & Sensor Networ Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538661192

Precise vehicle retrieval, which means ascertaining all instances for a given query vehicle image, is a challenging task as different vehicles will share the same visual attributes. To solve this problem, a novel color image retrieval method based on improved fast affine matching is proposed, which combines color constants and hue and saturation (H-S) color features of special marks to perform the fine-grained retrieval of images. The proposed method overcomes the influence of illumination variation and deformation on vehicle images. Furthermore, with full use of vehicle annual inspection labels, vehicle retrieval can be separated from excessive reliance on vehicle license plates. We evaluate our proposed method on the ReIDcar dataset, which includes many low-quality vehicle images in a series of experiments, and the large-scale image dataset VehicleID. Experimental results demonstrate that the retrieval rate outperforms other traditional methods, verifying the feasibility and effectiveness of the proposed method. Experimental results demonstrate that the proposed method is superior to other synopsis methods in the processing speed and retrieval accuracy.

关键词： vehicle retrieval color fast-match color constant vehicle annual inspection label multi feature matching

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Study on the Segmentation Method of Multi-Phase CT Liver Tumor Based on Dual Channel U-Nets

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Journal of Physics: Conference Series 2021年第1期1828卷

作者： Changchang Xu Dong Hu YaoDong Zhang Yuwei Pang Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications Nanjing 210003 China Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing 210003 China Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing 210003 China The first clinical medical college of Nanjing Medical University Nanjing University of Posts and Telecommunications Nanjing 210003 China

As a common malignant tumor disease, hepatocellular carcinoma is the most common cancers in the world. The incidence of hepatocellular carcinoma in China is higher than that in the world. Therefore, it is very important for doctors to separate liver and tumor from CT images by means of computer-aided diagnosis and treatment. In this paper, a multiscale DC-CUNets network liver tumor segmentation method is proposed to enhance the fusion of multi-phase image features in CT, the scale of liver tumors, and the optimization of network training process. (1) A multistage CT liver tumor segmentation method based on two-channel cascaded U-Nets (DC-CUNets) is proposed. The liver was segmented using the first-order U-Net, and then the segmented area of interest of the liver was input into the second-order U-Net network to segment liver tumors. We designed two-channel U-Nets to learn the image characteristics of CT images in arterial and venous phases respectively, and to achieve two-channel feature fusion through feature cascade to improve the overall accuracy of liver tumor segmentation.(2) A multistage CT liver tumor segmentation method based on multiscale DC-CUNets was proposed. For the scale problem of liver tumors, we designed a two-layer multiscale void convolution module to obtain image features at different scales for large, medium and small tumors, and fuse the multiscale features at the output of the module. We have replaced the convolution layer of the fourth module in the second-order two-channel liver tumor segmentation U-Nets by the two-layer multiscale cavity convolution module to implement multiscale DC-CUNets.

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Total Ionizing Dose Effects on a Radiation-Hardened CMOS image sensor Demonstrator for ITER Remote Handling

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2018年第1期65卷 101-110页

作者： Goiffon, Vincent Rizzolo, Serena Corbiere, Franck Rolando, Sebastien Bounasser, Said Sergent, Marius Chabane, Aziouz Marcelot, Olivier Estribeau, Magali Magnan, Pierre Paillet, Philippe Girard, Sylvain Gaillardin, Marc Marcandella, Claude Allanche, Timothe Van Uffelen, Marco Mont Casellas, Laura Scott, Robin De Cock, Wouter Univ Toulouse ISAE SUPAERO Image Sensor Res Team F-31055 Toulouse France CEA DAM DIF F-91297 Arpajon France Univ St Etienne UMR CNRS 5516 Lab Hubert Curien F-42100 St Etienne France Fus Energy Barcelona 08019 Spain Oxford Technol Ltd Abingdon OX14 1RL Oxon England SCK CEN B-2400 Mol Belgium

Total ionizing dose effects are studied on a radiation hardened by design (RHBD) 256 x 256-pixel CMOS image sensor (CIS) demonstrator developed for ITER remote handling by using X- and gamma-ray irradiations. The (color) imaging capabilities of the RHBD CIS are demonstrated up to 10 NICy (SiO2), 1 Grad (SiO2), validating the radiation hardness of most of the designed integrated circuit. No significant sensitivity (i.e., responsivity and color filter transmittance) or readout noise degradation is observed. The proposed readout chain architecture allows achieving a maximum output voltage swing larger than 1 V at 10 MGy (SiO2). The influence of several pixel layout (the gate oxide thickness, the gate overlap distance, and the use of an in-pixel P+ ring) and manufacturing process parameters (photodiode doping profile and process variation) on the radiation-induced dark current increase is studied. The nature of the dark current draining mechanism used to cancel most of the radiation-induced degradation is also discussed and clarified.

关键词： Active pixel sensors (APS) CMOS CMOS image sensors (CISs) Co60 dark current deep submicrometer (DSM) process enclosed layout transistors (ELTs) gamma-rays Gigarad (Grad) image sensors integrated circuit interface states ionizing radiation ITER MAPS Megagray (MGy) monolithic active pixel sensor quantum efficiency rad hard radiation damage radiation effects radiation hard radiation hardening radiation tolerant radiation hardened by design (RHBD) shallow trench isolation (STI) total ionizing dose (TID) trapped charge X-rays

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Joint occlusion boundary detection and figure/ground assignment by extracting common-fate fragments in a back-projection scheme

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PATTERN RECOGNITION 2017年 64卷 15-28页

作者： Chen, Cheng Corso, Jason J. Oklahoma State Univ Image & Sensor Lab Pavement Stillwater OK 74078 USA Univ Michigan Elect Engn & Comp Sci 1301 Beal Ave Ann Arbor MI 48109 USA

Occlusion boundary detection and figure/ground assignment are among the fundamental challenges for the real world visual pattern recognition applications, such as 3D spatial understanding, robotic navigation and object search. We attack these challenges by extracting an intermediate-level image/video representation, namely, Common-Fate Fragments. A Common-Fate Fragment is composed of both over-segmented region and edge fragments. Physically, it exists as a coupled edge-region fragment bound with dynamic information. Common Fate Fragment candidates are generated by an integrated line-region growing process, which does not require complete object segmentation or closed object boundary extraction. To identify Common-Fate Fragments from these extracted candidates, we introduce a back-projection verification scheme that can circumvent the notoriously difficult task of direct motion estimation on boundaries. This allows occlusion detection and figure/ground labeling to be jointly conducted within a simple but effective hypothesize-and-test framework. We test the proposed method on YouTube Motion Boundaries (YMB) data set and two benchmark data sets: the CMU and Berkeley motion data sets. Even though the idea of the proposed method is simple and transparent, promising experimental results are observed.

关键词： REAR-screen projection PATTERN perception PATTERN recognition systems SEGMENTATION (image processing) NAVIGATION

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Intra/Inter-frame Joint WPP Coding Algorithm on Multicore Platform

Intra/Inter-frame Joint WPP Coding Algorithm on Multicore Pl...

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2018 3rd International Conference on Electrical, Automation and Mechanical Engineering(EAME 2018)

作者： Chuanwei Yin Dong Hu Tao Gu Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications

Although wavefront parallel processing(WPP) proposed in the HEVC standard and various inter frame WPP algorithms can achieved comparatively high parallelism, their scalability for its parallelism is still very limited due to various dependencies introduced in spatial and temporal prediction in HEVC. In this paper, through pixel correlation analysis, establishment of CTU node model, multi-core resource allocation strategy, we proposed an intra/inter-frame joint WPP coding algorithm for multi-core platform which can significantly improve the parallelism, while achieved good results in bit rate, PSNR, and acceleration ratio. Experiments on standard HD test sequence show that the proposed algorithm can lead to up to 2x, 1.3x speed up compared with the original WPP and IWF parallelism.

关键词： video coding HEVC multicore platform high parallelism WPP

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