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Messaging Beyond Texts with Real-time image Suggestions 20

Messaging Beyond Texts with Real-time Image Suggestions

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22nd International conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI)

作者： Kim, Joongyum Gong, Taesik Han, Kyungsik Kim, Juho Ko, JeongGil Lee, Sung-Ju Korea Adv Inst Sci & Technol Sch Comp Daejeon South Korea Ajou Univ Dept Comp Sci Suwon South Korea Yonsei Univ Sch Integrated Technol Seoul South Korea Korea Adv Inst Sci & Technol Sch Elect Engn Daejeon South Korea

ISBN: (纸本)9781450375160

While people primarily communicate with text in mobile chat applications, they are increasingly using visual elements such as images, emojis, and memes. Using such visual elements could help users communicate clearly and make chatting experience enjoyable. However, finding and inserting contextually appropriate images during the chat can be both tedious and distracting. We introduce MilliCat, a real-time image suggestion system that recommends images that match the chat content within a mobile chat application (i.e., autocomplete with images). MilliCat combines natural language processing (e.g., keyword extraction, dependency parsing) and mobile computing (e.g., resource and energy-efficiency) techniques to autonomously make image suggestions when users might want to use images. Through multiple user studies, we investigated the effectiveness of our design choices, the frequency and motivation of image usage by the participants, and the impact of MilliCat on mobile chat experiences. Our results indicate that MilliCat's realtime image suggestion enables users to quickly and conveniently select and display images on mobile chat by significantly reducing the latency in the image selection process (3.19x improvement) and consequently more frequent image usage (1.8x) than existing solutions. Our study participants reported that they used images more often with MilliCat as the images helped them convey information more effectively, emphasize their opinion, express emotions, and have fun chatting experience.

关键词： Mobile Chat image Recommendations visual communications

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The principles of organizing the search for an object in an image, tracking an object and the selection of informative features based on the visual perception of a person 3rd

The principles of organizing the search for an object in an ...

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3rd International conference on Data Stream and Mining and processing, DSMP 2020

作者： Boyun, Vitaliy National Academy of Sciences of Ukraine Kyiv Ukraine

ISBN: (纸本)9783030616557

A significant expansion of the scope of computer vision, in particular in real-time systems, places very high demands on them in terms of productivity and efficiency of information processing, and in feedback systems, it also requires information lag in it. Such requirements are not ensured by traditional approaches. The way out of the situation may be to use as a prototype the principles of organization of the human visual system, which has a very high selectivity of perception of video information. The paper presents a generalized dynamic model of the organization of these principles. It is proposed to use them to organize the search for an object in a coarse image of a scene, to track an object and, if necessary, to carry out its classification or recognition at a more detailed level. © 2020, Springer Nature Switzerland AG.

关键词： Real time systems

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Reduced-Reference Stereoscopic image Quality Assessment Based on Entropy of Gradient Primitives 5

Reduced-Reference Stereoscopic Image Quality Assessment Base...

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5th IEEE International conference on Signal and image processing, ICSIP 2020

作者： Ma, Jian Zhao, Xinxin Xu, Youxin Anhui University School of Internet China Anhui Xinhua University School of Electronics and Communications Engineering China Marvell Technology Group Ltd. Bermuda

ISBN: (纸本)9781728168968

Stereoscopic image quality assessment (SIQA) has always been challenging due to the remarkable distinction between human monocular and binocular vision. This paper proposes a novel gradient-based dictionary learning method for SIQA, which effectively integrates the gradients are sparser than the image itself. Specifically, we first compute the gradient maps of each view image of stereopair by applying contrast sensitivity of human visual system (HVS) and neighborhood gradient information to weight the gradient magnitudes in a locally adaptive manner. Afterwards, the binocular perceptual information of gradient (GBPI) is represented by the distribution statistics of visual primitives in gradient maps of left and right views' images, which are extracted by sparse representation. Furthermore, the entropy of gradient maps of each views' images are utilized to represent monocular cue. Their mutual information is used to represent binocular cue. The difference of the reference and distorted images' GBPIs is taken as quality-ware features. Finally, the kernel ridge regressing (KRR) is utilized to simulate a nonlinear relationship between the quality-ware features and human opinions. The performance of the proposed metric is evaluated over the LIVE 3D phase II asymmetric datasets, and shown to be competitive with the state-of-the-art SIQA algorithms. © 2020 IEEE.

关键词： Entropy

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External Sparsity Combined with Internal Low-Rankness for image Denoising

External Sparsity Combined with Internal Low-Rankness for Im...

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International conference on Computer and communications (ICCC)

作者： Yang Ou Bailin Li Jianqiao Luo Jiacai Liao School of Mechanical Engineering Southwest Jiaotong University Chengdu China College of Mechanical and Vehicle Engineering Hunan University Changsha China

ISBN: (纸本)9781665409513

Nonlocal self-similarity (NSS) as a remarkable prior has been successfully applied to image processing including image denoising. For each local patch in an image, we can search for many nonlocally similar patches under NSS prior and stack them into a group, and then process the group instead of a patch to better capture the nonlocal structure. Most existing methods consider the NSS either of the internal degraded image or from an external clean corpus, which may limit the denoising performance. In this paper, we propose a hybrid model to catch both the external and internal NSS. Specifically, we develop a model with two regularizers, the internal NSS is exploited by a low-rankness regularizer, and the external NSS is exploited by a sparse regularizer. An alternating minimization method is developed to solve our model. Experimental results demonstrate that our algorithm achieves better results compared with several state-of-the-art denoising methods.

关键词： Minimization methods image coding Computational modeling Noise reduction visual effects Noise measurement image denoising

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Modeling a Low Vision Observer: Application in Comparison of image Enhancement Methods 22nd

Modeling a Low Vision Observer: Application in Comparison of...

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22nd International conference on Human-Computer Interaction, HCI International 2020

作者： Walbrecq, Cédric Lafon-Pham, Dominique Marc, Isabelle EuroMov Digital Health in Motion University of Montpellier IMT Mines Ales Ales France

ISBN: (纸本)9783030607029

Numerous image processing methods have been proposed to help low vision people, often relied on contrast enhancement algorithms. Their assessment is usually performed by tests on low vision subjects, which are expensive and time consuming. This paper presents a low vision observer model, fully customizable to fit various impaired visual performances, which may be used for early algorithm assessment, and avoiding unnecessary human tests. This model is fitted to visual performances of a subject with degenerative retinal disease, and applied to images processed by two edge enhancement algorithms, allowing to explain their performances in terms of blur reduction and color saturation improvement. © 2020, Springer Nature Switzerland AG.

关键词： image enhancement

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Malware Classification Based on GAF visualization of Dynamic API Call Sequences

Malware Classification Based on GAF Visualization of Dynamic...

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International conference on Communication Technology (ICCT)

作者： Hongmei Zhang Xiaoqian Yun Xiaofang Deng Xiaoxiong Zhong School of Information and Communication Guilin University of Electronic Technology Guilin China Peng Cheng Laboratory Shenzhen China

Due to the constant updates of malware and its variants and the continuous development of malware obfuscation techniques. Malware intrusions targeting Windows hosts are also on the rise. Traditional static analysis methods such as signature matching mechanisms have been difficult to adapt to the detection of new malware. Therefore, a novel visual detection method of malware is proposed for first-time to convert the Windows API call sequence with sequential nature into feature images based on the Gramian Angular Field (GAF) idea, and train a neural network to identify malware. The experimental results demonstrate the effectiveness of our proposed method. For the binary classification of malware, the GAF visualization image of the API call sequence is compared with its original sequence. After GAF visualization, the classification accuracy of the classic machine learning model MLP is improved by 9.64%, and the classification accuracy of the deep learning model CNN is improved by 4.82%. Furthermore, our experiments show that the proposed method is also feasible and effective for the multi-class classification of malware.

关键词： Deep learning visualization Neural networks Static analysis Feature extraction Malware communications technology

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Research on image Super-Resolution Reconstruction Based on Generative Countermeasure Network

Research on Image Super-Resolution Reconstruction Based on G...

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1st International conference on Robotics and Rehabilitation Intelligence, ICRRI 2020

作者： Jia, Rongzhao Wang, Xiaohong Liaoning Shihua University Fushun113001 China

ISBN: (纸本)9789813349315

image super-resolution reconstruction technology is an important image processing technology used to improve image quality and video resolution in the field of computer vision. Nowadays, the main methods of super-resolution reconstruction based on convolutional neural network (CNN) are mostly to get higher peak signal-to-noise ratio (PSNR), which will produce many other problems, such as, the visual sensory effect of the image is not ideal, the gradient back propagation is difficult, the training effect of long training time is not ideal, the image lacks some high-frequency information and texture details, etc. In this paper, an improved image super-resolution reconstruction method based on generative multi anti network (GAN) is proposed. For the traditional generative adversary network, a VGG19 network assistant generator and discriminator model training are added, and the loss function is improved. Combined with the GAN adversary loss, the feature loss of the auxiliary VGG19 network is added. Experimental results show that compared with the existing methods, this method improves the overall visual effect of the reconstructed image, restores more realistic texture effect and higher MOS score under the condition of ensuring PSNR. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Computer vision

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A Modified Algorithm of visual Quality Providing in Lossy Compression of Remote Sensing images

A Modified Algorithm of Visual Quality Providing in Lossy Co...

引用

International conference on Radio Electronics & Info communications (UkrMiCo)

作者： Fangfang Li Sergey Krivenko Vladimir Lukin National Aerospace University- KhAI Kharkiv Ukraine

The development of remote sensing technology leads to a huge number of acquired images needed to be stored and/or transferred. Lossy compression is an essential mean to reduce the image size and, thus, to improve the efficiency of storing and transferring. Meanwhile, a certain quality (including visual quality) must be provided in lossy compression since this quality determines the efficiency of further image processing and/or analysis. However, the task to provide a desired quality in lossy image compression quickly and accurately is not trivial. In this paper, we propose a modified lossy compression scheme able to guarantee a desired quality with high accuracy in two steps. The quality is evaluated in terms of both a conventional metric PSNR and a human visual system (HVS)-based metric PSNR-HVS-M. The experiments are conducted for discrete cosine transform (DCT)-based AGU coder for which we reach the max variance of errors equal to 0.124 dB 2 , and the biases less than 0.27 dB. This result proves that the average rate-distortion curve drawn from the remote sensing category better fits remote sensing data. The combination scheme of derivative and tangent gives better parameter predictions and helps reduce the final error.

关键词： Measurement visualization Technological innovation image coding Rate-distortion visual systems Prediction algorithms

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Deep learning-based Object Detection in Underwater communications System

Deep learning-based Object Detection in Underwater Communica...

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Electrical, Electronics, Information and Communication Technologies (ICEEICT), International conference on

作者： M. Siva Sangari K. Thangaraj U. Vanitha N. Srikanth J. Sathyamoorthy K. Renu Department of CSE KPR Institute of Engineering and Technology Coimbatore India Department of Information Technology Sona College of Technology Salem India Department of ECE Sri Krishna College of Engineering and Technology Coimbatore India Department of Electronics and Communication Technology SASI Institute of Technology and Engineering Tadepalligudem Andhra Pradesh India Department of CSE Bannari Amman Institute of Technology Erode India Department of EECE GST GITAM Deemed to be University Visakhapatnam -45 A.P India

Being at the nexus of robotics and ocean engineering, underwater robots have been a developing research area. They can be used for deep sea infrastructure inspections, oceanographic mapping, and environmental monitoring. Autonomous navigation skills are essential for doing these activities successfully, especially given the poor communication conditions in underwater locations. Autonomous navigation technologies, such as path planning and tracking, have been one of the fascinating but difficult issues in the field of study due to the extremely dynamic and three-dimensional settings. Due to their short detection ranges and poor visibility, cameras have not received much attention as an underwater sensor. However, using visual data from cameras is still a popular technique for underwater sensing, and it works particularly well for close-range detections. In this study, the enhancement of underwater vision is achieved by combining the max-RGB and shades of grey methods. Then, to solve the problem of poorly illuminated underwater images, a technique known as RCNN (Region-based Convolutional Neural Network) is proposed. This procedure tells the mapping relationship how to create the illumination map. Following image processing, an RCNN strategy for underwater detection and classification is recommended. Two improved strategies are then used to change the RCNN structure in accordance with the properties of underwater vision. In order to deal with the challenges of object tracking and detection in underwater communication, a correlation filter tracking algorithm (CFTA) method was created. The properties of the invariant moment and area were looked at after the object's region had been extracted using a threshold segment and morphological technique. The findings show that the suggested method is effective for underwater target tracking based on RCNN-CFTA in the aquatic environment. Simulated evaluation of these methods' performance demonstrates the potency of the suggested

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A Study on 4D Light Field Compression Using Multi-focus images and Reference Views

A Study on 4D Light Field Compression Using Multi-focus Imag...

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IEEE visual communications and image processing (VCIP)

作者： Shuho Umebayashi Kazuya Kodama Takayuki Hamamoto Graduate School of Engineering Tokyo University of Science Tokyo Japan National Institute of Informatics Research Organization of Information and Systems Tokyo Japan

ISBN: (纸本)9781728173221

We propose a novel method of light field compression using multi-focus images and reference views. Light fields enable us to observe scenes from various viewpoints. However, it generally consists of 4D enormous data, that are not suitable for storing or transmitting without effective compression at relatively low bit-rates. On the other hand, 4D light fields are essentially redundant because it includes just 3D scene information. While robust 3D scene estimation such as depth recovery from light fields is not so easy, a method of reconstructing light fields directly from 3D information composed of multi-focus images without any scene estimation is successfully derived. Based on the method, we previously proposed light field compression via multi-focus images as effective representation of 3D scenes. Actually, its high performance can be seen only at very low bit-rates, because there exists some degradation of low frequency components and occluded regions on light fields predicted from multi-focus images. In this paper, we study higher quality light field compression by using reference views to improve quality of the prediction from multi-focus images. Our contribution is twofold: first, our improved method can keep good performance of 4D light field compression at a wider range of low bit-rates than the previous one working effectively only for very low bit-rates; second, we clarify how the proposed method can improve its performance continuously by introducing recent video codec such as HEVC and VVC into our compression framework, that does not depend on 3D-SPIHT previously adopted for the corresponding component. We show experimental results by using synthetic and real images, where quality of reconstructed light fields is evaluated by PSNR and SSIM for analyzing characteristics of our novel method well. We notice that it is much superior to light field compression using HEVC directly at low bit-rates regardless of its light field scan order.

关键词： image coding Three-dimensional displays visual communication Time series analysis Estimation Video compression Light fields

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