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2nd IEEE International Conference on computer and Communications, ICCC 2016

作者： Gang, Wang Yongfei, Zhang Fan, Rui Zhou, Mingliang Jinhui, Yang Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China

ISBN: (纸本)9781467390262

The just noticeable distortion(JND) model has the better feature that can represent the human visual system's characteristics. To improve the accuracy of the JND model in multi-channel space, this paper proposes a DCT-domain multi-channel JND model in the YCbCr space. Firstly, the proposed JND model can directly compute the JND thresholds in the YCbCr space to be applied effectively in the video coding standards using the YCbCr format. Secondly, four effects are jointly considered by the proposed JND thresholds in chroma channels for the first time. Finally, in two chroma channels, we measure the contrast masking effect by psychophysical tests with the 8×8 DCT block size to accurately estimate the HVS thresholds in DCT domain. In tests, we also find out that, as the texture complexity is invariant, the contrast masking effects of the chroma components show a low pass property in frequency, which differs from the luma component that has a bypass property in frequency. Based on this observation, we model a continuous function of DCT frequency, the texture complexity, and the contrast masking effect in Cb and Cr channels, respectively. Experimental results show that the proposed multi-channel JND yields more tolerance for distortions with similar perceptual quality, compared to the Luo's JND model in the YCbCr space. © 2016 IEEE.

关键词： Video signal processing

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VISNET: A Study Case for Visualize Sensor Ad-Hoc Networks Behavior

VISNET: A Study Case for Visualize Sensor Ad-Hoc Networks Be...

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International Conference on virtual reality and Visualization (ICVRV)

作者： Jorge Gonzalez Xun Luo Gustavo Alomia Claudia Zúñiga Yi Chen School of Computer Science and Engineering Tianjin University of Technology Tianjin China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Research Group COMBA RD University of Santiago de Cali Cali Colombia Beijing Key Laboratory of Big Data Technology for Food Safety School of Computer and Information Engineering Beijing Technology and Business University Beijing China

ISBN: (纸本)9781538626375;9781538626368

Ad-hoc sensor networks are difficult to maintain and follow, due to the facts that networks are autonomous, and nodes are usually located in a remote place. The need to monitor and keep records of the operation of these networks motivates us to develop and implement a tool that allows not only monitoring the network but also using the data circulating in it to provide useful information to a community, either about the conditions of the environment, climate or other type of information that can be captured through sensors. This paper proposes a way to implement a visualization tool and shows the experiments performed over a wireless Ad-hoc network using temperature and humidity sensors.

关键词： Data visualization Humidity Ad hoc networks Temperature sensors Temperature distribution virtual reality Monitoring

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Visual object tracking- classical and contemporary approaches

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Frontiers of computer Science 2016年第1期10卷 167-188页

作者： Ahmad ALI Abdul JALIL Jianwei NIU Xiaoke ZHAO Saima RATHORE Javed AHMED Muhammad AKSAM IFTIKHAR Department of Computer and Information Sciences Pakistan Institute of Engineering & Applied Sciences Islamabad 44000 Pakistan State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing 100191 China Department of Electrical (Telecom) Engineering NUST Military College of Signals Islamabad 44000 Pakistan COMSATS Institute of Information Technology Lahore 54000 Pakistan

Visual object tracking （VOT） is an important sub- field of computer vision. It has widespread application do- mains, and has been considered as an important part of surveillance and security system. VOA facilitates finding the position of target in image coordinates of video frames. While doing this, VOA also faces many challenges such as noise, clutter, occlusion, rapid change in object appearances, highly maneuvered （complex） object motion, illumination changes. In recent years, VOT has made significant progress due to availability of low-cost high-quality video cameras as well as fast computational resources, and many modern techniques have been proposed to handle the challenges faced by VOT. This article introduces the readers to 1） VOT and its applica- tions in other domains, 2） different issues which arise in it, 3） various classical as well as contemporary approaches for object tracking, 4） evaluation methodologies for VOT, and 5） online resources, i.e., annotated datasets and source code available for various tracking techniques.

关键词： visual object tracking computer vision imageprocessing point tracking kernel tracking silhouette track-ing

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A robust authentication protocol with privacy protection for wireless sensor networks

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) 2017年 10155 LNCS卷 30-44页

作者： Li, Xiong Niu, Jianwei Raymond Choo, Kim-Kwang School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China Department of Information Systems and Cyber Security University of Texas at San Antonio San AntonioTX78249-0631 United States

ISBN: (纸本)9783319620237

As a typical application of Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many fields, such as remote healthcare, to gather data of monitoring area. However, due to open nature of wireless channel and limited computing and storage resource of sensor node, how to guarantee the sensitive sensed data are only be accessed by valid user becomes an important issue. Many user authentication protocols for WSNs have been proposed to address this issue, however, previous work more or less have their own weaknesses. Recently, Gope and Hwang proposed a lightweight anonymity authentication for WSNs, and they claimed that their protocol is secure against most attacks. However, our analysis indicates that their protocol still has some design and security flaws. To address the security issue for WSNs, a user authentication protocol with privacy protection for WSNs has been proposed. The analysis and comparisons results show that the proposed protocol is a robust and security one for WSNs. © Springer International Publishing AG 2017.

关键词： Authentication

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4D-rasterization for Fast Soft Shadow Rendering

4D-rasterization for Fast Soft Shadow Rendering

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27th Eurographics Symposium on Rendering - Experimental Ideas and Implementations, EGSR 2016

作者： Wang, Lili Zhao, Qi Meng, Chunlei Popescu, Voicu China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Computer Science Purdue University West LafayetteIN United States

ISBN: (纸本)9783038680192

This paper describes an algorithm for rendering soft shadows efficiently by generalizing conventional triangle projection and rasterization from 2D to 4D. The rectangular area light source is modeled with a point light source that translates with two degrees of freedom. This generalizes the projection of triangles and of output image samples, as seen from the light, to the locus of projections as the light translates. The generalized projections are rasterized to determine a conservative set of sample/triangle pairs, which are then examined to derive light occlusion masks for each sample. The algorithm is exact in the sense that each element of the occlusion mask of a sample is computed accurately by considering all potentially blocking triangles. The algorithm does not require any type of precomputation so it supports fully dynamic scenes. We have tested our algorithm on several scenes to render complex soft shadows accurately at interactive rates. © 2016 The Author(s) Eurographics Proceedings © 2016 The Eurographics Association.

关键词： Rasterization

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Deep Face Attributes Recognition Using Spatial Transformer Network

Deep Face Attributes Recognition Using Spatial Transformer N...

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IEEE International Conference on Information and Automation

作者： Lianzhi Tan Zhifeng Li Qiao Yu Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781509041039

-Face alignment is very crucial to the task of face attributes recognition. The performance of face attributes recognition would notably degrade if the fiducial points of the original face images are not precisely detected due to large lighting, pose and occlusion variations. In order to alleviate this problem, we propose a spatial transform based deep CNNs to improve the performance of face attributes recognition. In this approach, we first learn appropriate transformation parameters by a carefully designed spatial transformer network called LoNet to align the original face images, and then recognize the face attributes based on the aligned face images using a deep network called CINet. To the best of our knowledge, this is the first attempt to use spatial transformer network in face attributes recognition task. Extensive experiments on two large and challenging databases (CelebA and LFWA) clearly demonstrate the effectiveness of the proposed approach over the current state-of-the-art.

关键词： Face Attribute Recognition Spatial Transformer Network Face Alignment

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Learning Semantic Concepts from Noisy Media Collection for Automatic Image Annotation

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Chinese Journal of Electronics 2015年第4期24卷 790-794页

作者： TIAN Feng SHEN Xukun School of Computer and Information Technology Northeast Petroleum University State Key Laboratory of Virtual Reality Technology and Systems Beihang University

Along with the explosive growth of images, automatic image annotation has attracted great interest of various research communities. However, despite the great progress achieved in the past two decades, automatic annotation is still an important open problem in computer vision, and can hardly achieve satisfactory performance in real-world environment. In this paper, we address the problem of annotation when noise is interfering with the dataset. A semantic neighborhood learning model on noisy media collection is proposed. Missing labels are replenished, and semantic balanced neighborhood is construct. The model allows the integration of multiple label metric learning and local nonnegative sparse *** construct semantic consistent neighborhood for each sample, thus corresponding neighbors have higher global similarity, partial correlation, conceptual similarity along with semantic balance. Meanwhile, an iterative denoising method is also proposed. The method proposed makes a marked improvement as compared to the current state-ofthe-art.

关键词： Image annotation Noisy media collection Semantic neighborhood

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Monocular Video Guided Garment Simulation

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Journal of computer Science & technology 2015年第3期30卷 528-539页

作者：李发明陈小武周彬卢飞翔郭侃符强 State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing 100191 China

We present a prototype to generate a garment-shape sequence guided by a monocular video sequence. It is a combination of a physically-based simulation and a boundary-based modification. Given a garment in the video worn on a mannequin, the simulation generates a garment initial shape by exploiting the mannequin shapes estimated from the video. The modification then deforms the simulated 3D shape into such a shape that matches the garment 2D boundary extracted from the video. According to the matching correspondences between the vertices on the shape and the points on the boundary, the modification is implemented by attracting the matched vertices and their neighboring vertices. For best-matching correspondences and efficient performance, three criteria are introduced to select the candidate vertices for matching. Since modifying each garment shape independently may cause inter-frame oscillations, changes by the modification are also propagated from one frame to the next frame. As a result, the generated garment 3D shape sequence is stable and similar to the garment video sequence. We demonstrate the effectiveness of our prototype with a number of examples.

关键词： garment simulation monocular video shape correspondence

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Uniform remeshing of 3D meshes of arbitrary topology using discrete constrained centroid voronoi clustering 31

Uniform remeshing of 3D meshes of arbitrary topology using d...

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31st International Conference on computers and Their Applications, CATA 2016

作者： Lai, Shuhua He, Gaoqi School of Science and Technology Georgia Gwinnett College LawrencevilleGA30043 United States Department of Computer Science and Engineering East China University of Science and Technology Shanghai200237 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China

ISBN: (纸本)9781943436026

In this paper we propose a remeshing algorithm for altering the mesh geometry and connectivity of a 3D model to improve its uniformality. The new remeshing algorithm replaces an arbitrarily structured 3D mesh with a uniformly structured one, which has a given number of vertices, while approximates the original input mesh well. This is done through an elegant and efficient mesh clustering algorithm, which divides the faces of an input mesh into a given number of clusters for remeshing purpose by approximating the Centroidal Voronoi Tessellation of the mesh. With proliferation of 3D scanners, this remeshing algorithm is particularly useful for reverse engineering applications of 3D models, which in many cases are dense, nonuniform, irregular and arbitrary topology. Examples demonstrating effectiveness of the new algorithm are also included in the paper. Copyright ISCA.

关键词： Clustering algorithms

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Structure-adaptive shape editing for man-made objects

Structure-adaptive shape editing for man-made objects

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作者： Fu, Qiang Chen, Xiaowu Su, Xiaoyu Li, Jia Fu, Hongbo State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China International Research Institute for Multidisciplinary Science Beihang University China School of Creative Media City University of Hong Kong Hong Kong

One of the challenging problems for shape editing is to adapt shapes with diversified structures for various editing needs. In this paper we introduce a shape editing approach that automatically adapts the structure of a shape being edited with respect to user inputs. Given a category of shapes, our approach first classifies them into groups based on the constituent parts. The group-sensitive priors, including both inter-group and intra-group priors, are then learned through statistical structure analysis and multivariate regression. By using these priors, the inherent characteristics and typical variations of shape structures can be well captured. Based on such group-sensitive priors, we propose a framework for real-time shape editing, which adapts the structure of shape to continuous user editing operations. Experimental results show that the proposed approach is capable of both structure-preserving and structure-varying shape editing. © 2016 The Author(s) computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd.

关键词： Multivariant analysis

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