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IEEE international conference on Industrial Technology (ICIT)

作者： L. O. Solis-Sanchez J. M. Ortiz-Rodriguez R. Castañeda-Miranda M. R. Martinez-Blanco G. Ornelas-Vargas J. I. Galvan-Tejada C. E. Galvan-Tejada J. M. Celaya-Padilla C. L. Castañeda-Miranda Facultad de Ingeniería Eléctrica Centro de Investigación e Innovación Tecnológica Industrial (CIITI) Zacatecas Zacatecas México

The diabetic foot is one of the most devastating complications related to diabetic. Its significant transcendence is related to a higher incidence and amputation percentage as well as deaths. Given the fact that laboratory diagnoses trials are both limited and expensive, the most typical alternative is still based on the disease's signs and symptoms. Therefore, the attending physician fills out a questionnaire based on its support instrumental measurements and its own observation (it could be method but not so sure). The aforementioned questionnaire will provide the foundation for the diagnose that also depends on the criteria and the consultant's experience. However, for some variables such as the laceration (injury or wound) and-or-location the previous dependency is not acceptable. This paper aims to become the first link to optimize the diabetic's foot evaluation through the introduction of digital image processing techniques. Because of the use of advanced object segmentation techniques and a parameter that adjusts the system's sensibility until obtaining the desired results it was possible to apply an algorithm to a series of trial images provided positive results for wound and location detection.

关键词： Diabetes Wounds Lesions Digital images image segmentation Foot Cameras

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Keynote Speaker: Hacking Human Visual Perception

Keynote Speaker: Hacking Human Visual Perception

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IEEE Annual international Symposium Virtual Reality

作者： Shinya Nishida NTT Communication Science Laboratories

Roughly speaking, there are two strategies to provide users with a virtual realistic perceptual experience. One is to make the physical input to the user's sensory systems close to that of the real experience (physics-based approach). The other one, which sensory scientists (like us) prefer, is to make the response pattern of the users' sensory system close to that of the real experience (perception-based approach). Using cognitive/neuro-scientific knowledge about human visual processing, we are able to control cortical perceptual representations in addition to sensor responses, and then achieve perceptual effects that would be hard to obtain with the straightforward physics-based approach. For instance, recent research on human material perception has suggested simple image-based methods to control glossiness, wetness, subthreshold fineness and liquid viscosity. Deformation Lamp/Hengento (Kawabe et al., 2016) is a projection mapping technique that can produce an illusory movement of a real static object. Although only a dynamic gray-scale pattern is projected, it effectively drives visual motion sensors in the human brain, and then induces a “motion capture” effect on the colors and textures of the original static object. In Hidden Stereo (Fukiage et al., 2017), multi-scale phase-based binocular disparity signals effectively drives human stereo mechanisms, while the disparity-inducing image components for the left and right images are cancelled out with each other when they are fused. As a result, viewers with stereo glasses perceive 3D images, while those without glasses can enjoy 2D images with no visible ghosts. I will discuss how vision science helps virtual reality technologies, and how vision science is helped by application to the cutting-edge technologies.

关键词： Laboratories Visual perception Visualization Glass Psychology computer crime Process control

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Automatic Multiview Face Detection and Pose Estimationfrom Videos Based on Mixture-of-Trees Model and Optical Flow

Automatic Multiview Face Detection and Pose Estimationfrom V...

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2016 IEEE international conference on Signal and image processing

作者： Huisi Wu Laiqun Li Jingjing Liu Youcai Zhu Ping Li Zhenkun Wen College of Computer Science and Software Engineering Shenzhen University Department of Mathematics and Information Technology The Education University of Hong Kong

Face detection is an important task in the field of computer vision, which is widely used in the field of security, human-machine interaction, identity recognition, and *** existing methods are developed for image based face pose estimation, but few of them can be directly extended to ***, video-based face pose estimation is much more important and frequently used in real *** paper describes a method of automatic face pose estimation from videos based on mixture-of-trees model and optical *** the traditional mixture-of-trees model, which may easily incur errors in losing faces or with wrong angles for a sequence of faces in video, our method is much more robust by considering the spatio-temporal consistency on the face pose estimation for *** preserve the spatio-temporal consistency from one frame to the next, this method employs an optical flow on the video to guide the face pose estimation based on *** method is extensively evaluated on videos including different faces and with different pose *** visual and statistics results demonstrated its effectiveness on automatic face pose estimation.

关键词： face detection pose estimation mixture-of-trees model optical flow

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Face Clustering based on Graph Embedded Semi-NMF with Kernels

Face Clustering based on Graph Embedded Semi-NMF with Kernel...

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2016 IEEE 13th international conference on Signal processing（ICSP2016）

作者： Jia Liu He Zhang Bao-Di Liu Yanjiang Wang College of Information and Control Engineering China University of Petroleum(East China)

Non-negative Matrix Factorization(NMF) has been widely studied and applied to variant computer vision tasks, such as image clustering and pattern ***, real world stimuli for human neural system(e.g.,face images) are usually represented as high-dimensional data vectors rely on graph embedding in original Euclidean ***, the traditional NMF and its variants exhibit weakness for such clustering tasks. In this paper, we propose a Graph Embedding based Semi-NMF on Reproducing Kernel Hillbert Space(RKHS-SNMF) for human face clustering. This algorithm jointly considers the efficient dimension reduction and effective locally geometric preservation based on the exceptional property of measurability and differentiability of Reproducing Kernel Hillbert Space(RKHS). Extensive experimental results show that our RKHS-SNMF clustering algorithm outperforms the traditional clustering methods and the state-of-the-art NMF based clustering approaches on four benchmark human face databases.

关键词： Non-negative Matrix Factorization image Clustering Graph Embedding Kernel Space

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Fast Ship Detection in Remote Sensing images Based on Multi-Attention Mechanism 21

Fast Ship Detection in Remote Sensing Images Based on Multi-...

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Proceedings of the 5th international conference on Algorithms, Computing and Systems

作者： Jian Huang Zhuo Chen Hao Xu Xiushan Zhang School of Electrical Engineering Naval University of Engineering China

ISBN: (纸本)9781450385084

With the continuous development of deep learning in computer vision, object detection technology is constantly employed for processing remote sensing images. Especially, ship detection has become a significant and challenging task due to complex environmental factors (strong waves, clouds interference, etc.) and object issues (orientation, scale variety, density, etc.). Current detection methods pay more attention to the detection accuracy while ignoring the detection speed. In contrast with accuracy, detection speed is more important in some cases such as marine rescue and vessel tracking. Aiming at addressing these problems, we propose an enhanced YOLOv4(C-YOLOv4) which contains the feature fusion attention module (FAM) with a channel correlation loss(C-loss). C-loss is proposed to constrain the relations between object classes and channels while maintaining the intra-class and the inter-class separability. To evaluate the effectiveness of the proposed approach, comprehensive experiments are conducted on a public dataset HRSC2016. According to the experimental results, our proposed approach outperforms the baselines.

关键词： Convolutional neural networks Object detection Remote sensing image Ship detection

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Foreword to the Special Section on Smart Tools and Applications in computer Graphics 2015

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computerS & GRAPHICS-UK 2016年第0期60卷 A3-A4页

作者： Biasotti, Silvia Giachetti, Andrea Tarini, Marco CNR IMATI Genoa Italy Univ Verona Dept Comp Sci I-37100 Verona Italy Univ Insubria Varese Italy CNR ISTI Pisa Italy

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A Weighted Skin Probability Map for Skin Color Segmentation

A Weighted Skin Probability Map for Skin Color Segmentation

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international conference on Wireless Communications, Signal processing and Networking

作者： Biplab Ketan Chakraborty M. K. Bhuyan Sunil Kumar Department of Electronics and Electrical Engineering Indian Institute of Technology Guwahati

ISBN: (纸本)9781467393393

Skin color segmentation is important for several image processing, and computer vision applications. But, the accuracy of a color-based skin detection method is affected by the presence of some skin-like colors in the background regions. So, probabilistic approaches are more suitable for the skin detection as compared to hard decision-based approaches. A Skin Probability Map (SPM) of an image provides the probability of a pixel belonging to skin region. It is observed that the accuracy of a SPM-based skin detection method also depend on the chosen colorspace for the SPM. In this paper, a novel Weighted Skin Probability Map (WSPM) is proposed for the skin color segmentation. The WSPM is represented as a weighted sum of the SPMs obtained from different color spaces. Experimental results based on standard databases show that replacing the single colorspace-based SPMs with the proposed WSPM can reduce the overall detection errors significantly.

关键词： Skin image color analysis Color Entropy image segmentation Computational modeling conferences image colour analysis skin skin color Computational modeling image segmentation epidermis (animal) entropy inspection methods Skin Pigmentation Error detection images Scanning Probe Microscopy regions of skin Color background partition

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Web-Based Physics Experiments in Dynamics Using image processing

Web-Based Physics Experiments in Dynamics Using Image Proces...

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international conference on Power Electronics, Intelligent Control and Energy Systems

作者： Kiran C. Pattanashetty Ranjeet Kumar S.R. Pandian Department of Electronics Engineering Indian Institute of Information Technology Design and Manufacturing Kancheepuram

ISBN: (纸本)9781467385886

Web-based laboratories are promising to save the cost required to setup a hands-on laboratory in schools. There are several basic experiments in physics which help the students understand the basics of classical physics. However, the rising cost of laboratory infrastructure and costly equipment to conduct these experiments make it difficult for schools, in developing countries like India to build laboratories. This paper presents innovative web-based laboratory for physics to study equations of motion. One such experiment in equations of motion is the determination of acceleration due to gravity of a free falling object. However, measuring the distance traveled and time taken by a free-falling object is a tedious process. To overcome this challenge, a computer vision based system is presented which can measure the distance traveled and time taken by the object during free fall. By the technique of object detection in computer vision, the free-falling object is detected and tracked. The system is implemented using OpenCV libraries. The result of the analysis of free falling object is provided to the students through the web page.

关键词： OpenCV Object Detection Acceleration Due to Gravity Dynamics Experiment

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Preface

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Journal of computer Science & Technology 2016年第3期31卷 437-438页

作者： Shi-Min Hu (1) Li-Gang Liu (2) Ralph R. Martin (3) 1. Department of Computer Science and Technology Tsinghua University Beijing China 2. School of Mathematical Sciences University of Science and Technology of China Hefei China 3. School of Computer Science and Informatics Cardiff University Cardiff China

The Computational Visual Media （CVM） conference series is intended to provide a major international forum for exchanging novel research ideas and significant practical computational methods which either underpin or apply visual media. The primary rationale is to target cross-disciplinary research which amalgamates aspects of computer graphics, computer vision, machine learning, image processing, video processing, visualization and geometric computing. The main topics of interest to CVM include classification, composition, retrieval, synthesis, and understanding of visual media.

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Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 10481 LNCS卷 V页

作者： Mukherjee, Snehasis Mukherjee, Suvadip Mukherjee, Dipti Prasad Sivaswamy, Jayanthi Awate, Suyash Setlur, Srirangaraj Namboodiri, Anoop M. Chaudhury, Santanu Indian Institute of Information Technology SriCity India Indian Institute of Technology Bombay Mumbai India GE Global Research Bangalore India CEDAR BuffaloNY United States Indian Statistical Institute Kolkata India International Institute of Information Technology Hyderabad India CSIR-CEERI Pilani Rajasthan India

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