Proceedings of the 21st ACM international conference on Multimedia最新文献_第9页

Robust evaluation for quality of experience in crowdsourcing 对众包经验质量的稳健评估

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502083

Qianqian Xu, Jiechao Xiong, Qingming Huang, Y. Yao

引用次数: 25

ImproveMyCity: an open source platform for direct citizen-government communication improemycity:公民与政府直接沟通的开源平台

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502225

I. Tsampoulatidis, D. Ververidis, P. Tsarchopoulos, S. Nikolopoulos, Y. Kompatsiaris, N. Komninos

{"title":"ImproveMyCity: an open source platform for direct citizen-government communication","authors":"I. Tsampoulatidis, D. Ververidis, P. Tsarchopoulos, S. Nikolopoulos, Y. Kompatsiaris, N. Komninos","doi":"10.1145/2502081.2502225","DOIUrl":"https://doi.org/10.1145/2502081.2502225","url":null,"abstract":"ImproveMyCity is an open source platform that enables residents to directly report to their public administration local issues about their neighborhood such as discarded trash bins, faulty street lights, broken tiles on sidewalks, illegal advertising boards, etc. The reported issues are automatically transmitted to the appropriate office in public administration so as to schedule their settlement. Reporting is feasible both through a web- and a smartphone-based front-end that adopt a map-based visualization, which makes reporting a user-friendly and intriguing process. The management and routing of incoming issues is performed through a back-end infrastructure that serves as an integrated management system with easy to use interfaces. Apart from reporting a new issue, both front-ends allow the citizens to add comments or vote on existing issues, which adds a social dimension on the collected content. Finally, the platform makes also provision for informing the citizens about the progress status of the reported issue and in this way facilitate the establishment of a two-way dialogue between the citizen and public administration.","PeriodicalId":20448,"journal":{"name":"Proceedings of the 21st ACM international conference on Multimedia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86104429","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: 35

Understanding and classifying image tweets 理解和分类图片推文

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502203

Tao Chen, Dongyuan Lu, Min-Yen Kan, Peng Cui

引用次数: 81

Object coding on the semantic graph for scene classification 基于语义图的对象编码用于场景分类

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502131

Jingjing Chen, Yahong Han, Xiaochun Cao, Q. Tian

引用次数: 3

Segmental multi-way local pooling for video recognition 视频识别的分段多路局部池化

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502167

Ilseo Kim, Sangmin Oh, Arash Vahdat, Kevin J. Cannons, A. Perera, Greg Mori

引用次数: 7

Learning latent spatio-temporal compositional model for human action recognition 学习潜在时空组成模型的人体动作识别

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502089

Xiaodan Liang, Liang Lin, Liangliang Cao

{"title":"Learning latent spatio-temporal compositional model for human action recognition","authors":"Xiaodan Liang, Liang Lin, Liangliang Cao","doi":"10.1145/2502081.2502089","DOIUrl":"https://doi.org/10.1145/2502081.2502089","url":null,"abstract":"Action recognition is an important problem in multimedia understanding. This paper addresses this problem by building an expressive compositional action model. We model one action instance in the video with an ensemble of spatio-temporal compositions: a number of discrete temporal anchor frames, each of which is further decomposed to a layout of deformable parts. In this way, our model can identify a Spatio-Temporal And-Or Graph (STAOG) to represent the latent structure of actions emph{e.g.} triple jumping, swinging and high jumping. The STAOG model comprises four layers: (i) a batch of leaf-nodes in bottom for detecting various action parts within video patches; (ii) the or-nodes over bottom, i.e. switch variables to activate their children leaf-nodes for structural variability; (iii) the and-nodes within an anchor frame for verifying spatial composition; and (iv) the root-node at top for aggregating scores over temporal anchor frames. Moreover, the contextual interactions are defined between leaf-nodes in both spatial and temporal domains. For model training, we develop a novel weakly supervised learning algorithm which iteratively determines the structural configuration (e.g. the production of leaf-nodes associated with the or-nodes) along with the optimization of multi-layer parameters. By fully exploiting spatio-temporal compositions and interactions, our approach handles well large intra-class action variance (emph{e.g.} different views, individual appearances, spatio-temporal structures). The experimental results on the challenging databases demonstrate superior performance of our approach over other methods.","PeriodicalId":20448,"journal":{"name":"Proceedings of the 21st ACM international conference on Multimedia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79389863","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: 40

Semantic technologies for multimedia content: foundations and applications 多媒体内容的语义技术:基础和应用

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502232

A. Scherp

引用次数: 1

Time matters!: capturing variation in time in video using fisher kernels 时间很重要!:利用fisher核捕获视频中的时间变化

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502183

Ionut Mironica, J. Uijlings, Negar Rostamzadeh, B. Ionescu, N. Sebe

{"title":"Time matters!: capturing variation in time in video using fisher kernels","authors":"Ionut Mironica, J. Uijlings, Negar Rostamzadeh, B. Ionescu, N. Sebe","doi":"10.1145/2502081.2502183","DOIUrl":"https://doi.org/10.1145/2502081.2502183","url":null,"abstract":"In video global features are often used for reasons of computational efficiency, where each global feature captures information of a single video frame. But frames in video change over time, so an important question is: how can we meaningfully aggregate frame-based features in order to preserve the variation in time? In this paper we propose to use the Fisher Kernel to capture variation in time in video. While in this approach the temporal order is lost, it captures both subtle variation in time such as the ones caused by a moving bicycle and drastic variations in time such as the changing of shots in a documentary. Our work should not be confused with a Bag of Local Visual Features approach, where one captures the visual variation of local features in both time and space indiscriminately. Instead, each feature measures a complete frame hence we capture variation in time only. We show that our framework is highly general, reporting improvements using frame-based visual features, body-part features, and audio features on three diverse datasets: We obtain state-of-the-art results on the UCF50 human action dataset and improve the state-of-the-art on the MediaEval 2012 video-genre benchmark and on the ADL daily activity recognition dataset.","PeriodicalId":20448,"journal":{"name":"Proceedings of the 21st ACM international conference on Multimedia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75145252","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: 24

The space between the images 图像之间的空间

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2509857

L. Guibas

{"title":"The space between the images","authors":"L. Guibas","doi":"10.1145/2502081.2509857","DOIUrl":"https://doi.org/10.1145/2502081.2509857","url":null,"abstract":"Multimedia content has become a ubiquitous presence on all our computing devices, spanning the gamut from live content captured by device sensors such as smartphone cameras to immense databases of images, audio and video stored in the cloud. As we try to maximize the utility and value of all these petabytes of content, we often do so by analyzing each piece of data individually and foregoing a deeper analysis of the relationships between the media. Yet with more and more data, there will be more and more connections and correlations, because the data captured comes from the same or similar objects, or because of particular repetitions, symmetries or other relations and self-relations that the data sources satisfy. This is particularly true for media of a geometric character, such as GPS traces, images, videos, 3D scans, 3D models, etc. In this talk we focus on the \"space between the images\", that is on expressing the relationships between different mutlimedia data items. We aim to make such relationships explicit, tangible, first-class objects that themselves can be analyzed, stored, and queried -- irrespective of the media they originate from. We discuss mathematical and algorithmic issues on how to represent and compute relationships or mappings between media data sets at multiple levels of detail. We also show how to analyze and leverage networks of maps and relationships, small and large, between inter-related data. The network can act as a regularizer, allowing us to to benefit from the \"wisdom of the collection\" in performing operations on individual data sets or in map inference between them. We will illustrate these ideas using examples from the realm of 2D images and 3D scans/shapes -- but these notions are more generally applicable to the analysis of videos, graphs, acoustic data, biological data such as microarrays, homeworks in MOOCs, etc. This is an overview of joint work with multiple collaborators, as will be discussed in the talk.","PeriodicalId":20448,"journal":{"name":"Proceedings of the 21st ACM international conference on Multimedia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76174741","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: 0

Semantic pooling for complex event detection 用于复杂事件检测的语义池

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502191

Qian Yu, Jingen Liu, Hui Cheng, Ajay Divakaran, H. Sawhney

引用次数: 8