2017 IEEE International Conference on Multimedia and Expo (ICME)最新文献_第10页

3D action recognition using data visualization and convolutional neural networks 使用数据可视化和卷积神经网络的三维动作识别

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-01 DOI: 10.1109/ICME.2017.8019438

Mengyuan Liu, Chen Chen, Hong Liu

引用次数: 16

Hybrid color attribute compression for point cloud data 点云数据的混合颜色属性压缩

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-01 DOI: 10.1109/ICME.2017.8019426

Li Cui, Haiyan Xu, E. Jang

引用次数: 10

Strummer: An interactive guitar chord practice system Strummer:一个互动的吉他和弦练习系统

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-01 DOI: 10.1109/ICME.2017.8019338

Shunya Ariga, Masataka Goto, K. Yatani

引用次数: 6

End-to-end learning for dimensional emotion recognition from physiological signals 基于生理信号的情感维度识别的端到端学习

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-01 DOI: 10.1109/ICME.2017.8019533

Gil Keren, Tobias Kirschstein, E. Marchi, F. Ringeval, Björn Schuller

{"title":"End-to-end learning for dimensional emotion recognition from physiological signals","authors":"Gil Keren, Tobias Kirschstein, E. Marchi, F. Ringeval, Björn Schuller","doi":"10.1109/ICME.2017.8019533","DOIUrl":"https://doi.org/10.1109/ICME.2017.8019533","url":null,"abstract":"Dimensional emotion recognition from physiological signals is a highly challenging task. Common methods rely on hand-crafted features that do not yet provide the performance necessary for real-life application. In this work, we exploit a series of convolutional and recurrent neural networks to predict affect from physiological signals, such as electrocardiogram and electrodermal activity, directly from the raw time representation. The motivation behind this so-called end-to-end approach is that, ultimately, the network learns an intermediate representation of the physiological signals that better suits the task at hand. Experimental evaluations show that, this very first study on end-to-end learning of emotion based on physiology, yields significantly better performance in comparison to existing work on the challenging RECOLA database, which includes fully spontaneous affective behaviors displayed during naturalistic interactions. Furthermore, we gain better understanding of the models' inner representations, by demonstrating that some cells' activations in the convolutional network are correlated to a large extent with hand-crafted features.","PeriodicalId":330977,"journal":{"name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123274539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 38

Learning informative pairwise joints with energy-based temporal pyramid for 3D action recognition 基于能量的时间金字塔学习信息配对关节，用于三维动作识别

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-01 DOI: 10.1109/ICME.2017.8019313

Mengyuan Liu, Chen Chen, Hong Liu

{"title":"Learning informative pairwise joints with energy-based temporal pyramid for 3D action recognition","authors":"Mengyuan Liu, Chen Chen, Hong Liu","doi":"10.1109/ICME.2017.8019313","DOIUrl":"https://doi.org/10.1109/ICME.2017.8019313","url":null,"abstract":"This paper presents an effective local spatial-temporal descriptor for action recognition from skeleton sequences. The unique property of our descriptor is that it takes the spatial-temporal discrimination and action speed variations into account, intending to solve the problems of distinguishing similar actions and identifying actions with different speeds in one goal. The entire algorithm consists of two stages. First, a frame selection method is used to remove noisy skeletons for a given skeleton sequence. From the selected skeletons, skeleton joints are mapped to a high dimensional space, where each point refers to kinematics, time label and joint label of a skeleton joint. To encode relative relationships among joints, pairwise points from the space are then jointly mapped to a new space, where each point encodes the relative relationships of skeleton joints. Second, Fisher Vector (FV) is employed to encode all points from the new space as a compact feature representation. To cope with speed variations in actions, an energy-based temporal pyramid is applied to form a multi-temporal FV representation, which is fed into a kernel-based extreme learning machine classifier for recognition. Extensive experiments on benchmark datasets consistently show that our method outperforms state-of-the-art approaches for skeleton-based action recognition.","PeriodicalId":330977,"journal":{"name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113960075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

DenseTracker: A multi-task dense network for visual tracking DenseTracker:用于视觉跟踪的多任务密集网络

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-01 DOI: 10.1109/ICME.2017.8019506

Fei Zhao, Ming Tang, Yi Wu, Jinqiao Wang

引用次数: 4

Image quality assessment for free viewpoint video based on mid-level contours feature 基于中级轮廓特征的免费视点视频图像质量评估

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-01 DOI: 10.1109/ICME.2017.8019431

Suiyi Ling, P. Callet

引用次数: 19

Semantic-aware adaptation scheme for soccer video over MPEG-DASH 基于MPEG-DASH的足球视频语义感知自适应方案

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-01 DOI: 10.1109/ICME.2017.8019541

Shenghong Hu, Lingfen Sun, Chunxia Xiao, Chao Gui

{"title":"Semantic-aware adaptation scheme for soccer video over MPEG-DASH","authors":"Shenghong Hu, Lingfen Sun, Chunxia Xiao, Chao Gui","doi":"10.1109/ICME.2017.8019541","DOIUrl":"https://doi.org/10.1109/ICME.2017.8019541","url":null,"abstract":"In recent years, quality of experience (QoE) has been investigated and proved to have both influential factors on user's visual quality and perceptual quality, while the perceptual quality means user's requirement on personalized content should be acquired in optimized quality. That's to say, those segments holding user interested content such as highlights need to be allocated more network resource in a resource-limited streaming scenario. However, all the existing HTTP-based adaptive methods only focus the content-agnostic bitrate adaptation according to limited network resources or energy resource, since they ignored user perceived semantics on some important segments, which suffered less quality on the important segments than on those ordinary ones, so as to hurt the overall QoE. In this paper, we have proposed a new semantic-aware adaptation scheme for MPEG-DASH services, which decides how to preserve bandwidth and buffering time depending on content descriptors for the perceived important content to users. Further, a semantic-aware probe and adaptation (SMA-PANDA) algorithm has been implemented in a DASH client to compare with conventional bitrate adaptions. Preliminary results show that SMA-PANDA achieves better QoE and flexibility on streaming user's interested content on MPEG-DASH platform, and it also aggressively helps user interested content compete more resource to deliver high quality presentation.","PeriodicalId":330977,"journal":{"name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130028711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Multiscale dictionary learning for hierarchical sparse representation 分层稀疏表示的多尺度字典学习

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-01 DOI: 10.1109/ICME.2017.8019435

Yangmei Shen, H. Xiong, Wenrui Dai

{"title":"Multiscale dictionary learning for hierarchical sparse representation","authors":"Yangmei Shen, H. Xiong, Wenrui Dai","doi":"10.1109/ICME.2017.8019435","DOIUrl":"https://doi.org/10.1109/ICME.2017.8019435","url":null,"abstract":"In this paper, we propose a multiscale dictionary learning framework for hierarchical sparse representation of natural images. The proposed framework leverages an adaptive quadtree decomposition to represent structured sparsity in different scales. In dictionary learning, a tree-structured regularized optimization is formulated to distinguish and represent high-frequency details based on varying local statistics and group low-frequency components for local smoothness and structural consistency. In comparison to traditional proximal gradient method, block-coordinate descent is adopted to improve the efficiency of dictionary learning with a guarantee of recovery performance. The proposed framework enables hierarchical sparse representation by naturally organizing the trained dictionary atoms in a prespecified arborescent structure with descending scales from root to leaves. Consequently, the approximation of high-frequency details can be improved with progressive refinement from coarser to finer scales. Employed into image denoising, the proposed framework is demonstrated to be competitive with the state-of-the-art methods in terms of objective and visual restoration quality.","PeriodicalId":330977,"journal":{"name":"2017 IEEE International Conference on Multimedia and Expo (ICME)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129693453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

An interactive system for low-poly illustration generation from images using adaptive thinning 一个交互式系统，用于从使用自适应细化的图像生成低多边形插图

2017 IEEE International Conference on Multimedia and Expo (ICME) Pub Date : 2017-07-01 DOI: 10.1109/ICME.2017.8019369

Yiting Ma, X. Chen, Yueling Bai

引用次数: 2