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IEEE Global Communications Conference

作者： Enzhong Yang Yongyi Ran Shuangwu Chen Jian Yang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (纸本)9781479935130

In video streaming service, multicast mode is a promising way to complement unicast delivery of content, since it deliveries the video content to a broad range of receivers. It is considered as an efficient scheme to reduce redundant traffic in the networks. In this paper, we propose an OpenFlow based architecture for implementing Scalable Video Coding (SVC) multicast streaming. It enables in-network identifying, processing and manipulating the media streams, which makes prompt bitrate adaptation possible in response to network fluctuations. The heterogeneous video quality demand from the heterogeneous device also can be satisfied by customizing the multicast traffic through a centralized OpenFlow controller. We implement a testbed following the proposed architecture in our campus. With OpenFlow, we deploy IP multicast in a new way without Internet Group Management Protocol (IGMP) or any multicast addresses. Experiments implemented on the testbed show that our approach can provide a flexible and controllable video multicast streaming service and improve the usage of bandwidth resource in the condition of guaranteeing multicast receivers' Quality of Experience (QoE).

关键词： IP networks multicast communication telecommunication traffic video coding video streaming IP multicast OpenFlow networks bandwidth resource usage improvement bitrate adaptation centralized OpenFlow controller controllable video multicast streaming service heterogeneous device heterogeneous video quality demand media streams multicast SVC streaming architecture multicast receivers quality-of-experience multicast traffic network fluctuations redundant traffic reduction scalable video coding multicast streaming unicast content delivery Control systems Ports (Computers) Receivers Servers Static VAr compensators Streaming media

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Action recognition with novel high-level pose features

Action recognition with novel high-level pose features

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Jiayi Fan Zhengjun Zha Xinmei Tian University of Science and Technology of China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System

ISBN: (纸本)9781509015535

Recently high-level pose features (HLPF) have been shown to be efficient for action recognition in joint-annotated tasks. However, the relative positions between pairs of joints in actual situations and the spatio-temporal information are not considered in constructing HLPF. To tackle their problems, we propose a set of novel high-level pose features (NHLPF). Specifically, considering that the distances between adjacent pairs of joints usually remain unchanged, we propose a horizontally relative position feature and a vertically relative position feature. In addition, a joint inner product feature is proposed to code the spatial information among each triplet of joints. To code temporal information, we calculate the trajectories of the above-mentioned three types of features as corresponding trajectory features. Furthermore, to combine the spatial and temporal information, we present a joint energy change feature, which is designed using observations of the magnitude and direction of the force between joints. We evaluate our NHLPF on a benchmark dataset. The results show that NHPLF are superior features for action recognition.

关键词： Trajectory Pose estimation Detectors Joining processes Hip Force Three-dimensional displays

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3-D Context Entropy Model for Improved Practical Image Compression

3-D Context Entropy Model for Improved Practical Image Compr...

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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Zongyu Guo Yaojun Wu Runsen Feng Zhizheng Zhang Zhibo Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (数字)9781728193601

ISBN: (纸本)9781728193618

In this paper, we present our image compression framework designed for CLIC 2020 competition. Our method is based on Variational AutoEncoder (VAE) architecture which is strengthened with residual structures. In short, we make three noteworthy improvements here. First, we propose a 3-D context entropy model which can take advantage of known latent representation in current spatial locations for better entropy estimation. Second, a light-weighted residual structure is adopted for feature learning during entropy estimation. Finally, an effective training strategy is introduced for practical adaptation with different resolutions. Experiment results indicate our image compression method achieves 0.9775 MS-SSIM on CLIC validation set and 0.9809 MS-SSIM on test set.

关键词： Context modeling Solid modeling Image coding Entropy Training Transforms Image resolution

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Accelerate Neural Image Compression with Channel-Adaptive Arithmetic Coding

Accelerate Neural Image Compression with Channel-Adaptive Ar...

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IEEE International Symposium on Circuits and Systems

作者： Zongyu Guo Jun Fu Runsen Feng Zhibo Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

We have witnessed the revolutionary progress of learned image compression despite a short history of this field. Some challenges still remain such as computational complexity that prevent the practical application of learning-based codecs. In this paper, we address the issue of heavy time complexity from the view of arithmetic coding. Prevalent learning-based image compression scheme first maps the natural image into latent representations and then conduct arithmetic coding on quantized latent maps. Previous arithmetic coding schemes define the start and end value of the arithmetic codebook as the minimum and maximum of the whole latent maps, ignoring the fact that the value ranges in most channels are shorter. Hence, we propose to use a channel-adaptive codebook to accelerate arithmetic coding. We find that the latent channels have different frequency-related characteristics, which are verified by experiments of neural frequency filtering. Further, the value ranges of latent maps are different across channels which are relatively image-independent. The channel-adaptive characteristics allow us to establish efficient prior codebooks that cover more appropriate ranges to reduce the runtime. Experimental results demonstrate that both the arithmetic encoding and decoding can be accelerated while preserving the rate-distortion performance of compression model.

关键词： Image coding Runtime Filtering Rate-distortion Acceleration Integrated circuit modeling Time complexity

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3-D context entropy model for improved practical image compression

arXiv

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arXiv 2020年

作者： Guo, Zongyu Wu, Yaojun Feng, Runsen Zhang, Zhizheng Chen, Zhibo CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

关键词： Image compression

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Learned video compression with feature-level residuals

arXiv

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arXiv 2020年

作者： Feng, Runsen Wu, Yaojun Guo, Zongyu Zhang, Zhizheng Jin, Xin Chen, Zhibo CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

In this paper, we present an end-to-end video compression network for P-frame challenge on CLIC. We focus on deep neural network (DNN) based video compression, and improve the current frameworks from three aspects. First, we notice that pixel space residuals is sensitive to the prediction errors of optical flow based motion compensation. To suppress the relative influence, we propose to compress the residuals of image feature rather than the residuals of image pixels. Furthermore, we combine the advantages of both pixel-level and feature-level residual compression methods by model ensembling. Finally, we propose a step-by-step training strategy to improve the training efficiency of the whole framework. Experiment results indicate that our proposed method achieves 0.9968 MS-SSIM on CLIC validation set and 0.9967 MS-SSIM on test set. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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An automatic method on detecting image control points from SAR imagery based on optical image patches

An automatic method on detecting image control points from S...

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2009 Joint Urban Remote Sensing Event

作者： Hui, Long Kun, Fu Chuanzhao, Han Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China Beijing Remote Sensing Institute Beijing China

ISBN: (纸本)9781424434619

In this paper, we propose a novel procedure of detecting control points from SAR image based on Optical Image Patches procedure. The method presented here is a three-step procedure. In the first stage, a local image patch from the SAR image is estimated from the geo-information of the SAR image and the GCP geo-coordinate, and the local patch is performed an affine transformation by using the four geo-coordinates of the SAR image in advance. In the second stage, the NCC procedure is performed on the GCP and the preprocessed local SAR image patch to find the candidate image control point(ICP). In the third stage, the pairs of ICP and GCP are refined, and the false pairs are discarded by the RANSAC algorithm. Experiments on SAR-Optical satellite images demonstrate the reliability and effectiveness of the presented method. ©2009 IEEE.

关键词： Synthetic aperture radar

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An interactive system for low-poly illustration generation from images using adaptive thinning

An interactive system for low-poly illustration generation f...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Yiting Ma Xuejin Chen Yu Bai University of Science and Technology of China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System

ISBN: (纸本)9781509060689

Low-poly style illustrations, which have 3D abstract appearance, have become a popular stylish recently. Most previous methods require special knowledges in 3D modeling and need tedious interactions. We present an interactive system for non-expert users to easily manipulate the low-poly style illustration. Our system consists of two parts: vertex sampling and mesh rendering. In the vertex sampling stage, we extract a set of candidate points from the image and rank them according to their importance of structure preserving using adaptive thinning. Based on the pre-ranked point list, the user can select an arbitrary number of vertices for the triangle mesh construction. In the mesh rendering stage, we optimize triangle colors to create stereo-looking low-polys. We also provide three tools for exible modication of vertex numbers, color contrast, and local region emphasis. The experiment results demonstrate that our system outperforms state-of-the-art method via simple user interactions.

关键词： Image color analysis Rendering (computer graphics) Tools Approximation error Interactive systems Three-dimensional displays Image edge detection

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GUID-based mobile visual communication using NDN mechanism

GUID-based mobile visual communication using NDN mechanism

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IEEE Visual Communications and Image processing (VCIP)

作者： Yuanzun Zhang Xiaobin Tan Hao Liu Weiping Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (纸本)9781509053179

With the explosive growth in the number of mobile terminals, the demand for visual communication with mobility is increasing. However, traditional solutions for mobility over IP network cannot always meet the demand of satisfying visual communication. Named Data Networking (NDN) is a new communication model that aims to replace IP model brings a different background to mobile visual communication problems. In this paper, we take advantage of the NDN model to realize seamless mobile visual communication. We introduce a delegate with calculation functions and a globally unique identifier (GUID) which can provide native identity indication into the NDN mechanism. The use of GUID benefits real-time applications like visual communication and further works with the delegate to decrease unnecessary routing update. We also specify the naming rule and design a FIB+ to support seamless mobile visual communication. To test the performance of our solutions, we build a proof-of-concept prototype and run experiments on it. The experiments demonstrate that our solution can provide real-time video communication with seamless mobility experience.

关键词： Routing Mobile communication Visual communication IP networks Artificial neural networks Mobile computing Real-time systems

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Compressive tracking with adaptive color feature selection and foreground modeling

Compressive tracking with adaptive color feature selection a...

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IEEE Visual Communications and Image processing (VCIP)

作者： Tianqi Zheng Chao Xie Wengang Zhou Houqiang Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (纸本)9781509053179

Part-based trackers have achieved promising performance in many tracking tasks. However, most part-based trackers use the same feature representation for all parts and simply combine them together to form an integral representation for the tracking target. It may not guarantee that all parts of the tracking target can well distinguish the foreground from the background. Better performance is expected by exploring different feature representations on different parts of the tracking target. In this paper, following the framework of the classic Compressive Tracker (CT), we model each part of the target adaptively by using a multi-dimensional color representation. By using color name, we select the color feature presentation that best distinguishes the foreground from background. In order to better handle deformation and illumination change, we use multi-Gaussian to model different appearance changes of the tracking target. Both qualitative and quantitative evaluations demonstrate that the proposed method makes a consistent performance improvement compared with the conventional Compressive Tracker on tracking benchmark dataset. Besides, it also outperforms many state-of-the-art trackers while running at averagely 20 frames per second (FPS).

关键词： Target tracking Image color analysis Color Gaussian distribution Computed tomography Adaptation models

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