Proceedings of the 23rd ACM international conference on Multimedia最新文献_第2页

RECfusion: Automatic Video Curation Driven by Visual Content Popularity RECfusion:由视觉内容流行驱动的自动视频管理

Proceedings of the 23rd ACM international conference on Multimedia Pub Date : 2015-10-13 DOI: 10.1145/2733373.2806311

A. Ortis, G. Farinella, V. D'Amico, Luca Addesso, Giovanni Torrisi, S. Battiato

引用次数: 19

Filter-Invariant Image Classification on Social Media Photos 社交媒体照片的滤波不变图像分类

Proceedings of the 23rd ACM international conference on Multimedia Pub Date : 2015-10-13 DOI: 10.1145/2733373.2806348

Yu-Hsiu Chen, T. Chao, Sheng-Yi Bai, Yen-Liang Lin, Wen-Chin Chen, Winston H. Hsu

引用次数: 15

Beyond Doctors: Future Health Prediction from Multimedia and Multimodal Observations 超越医生:来自多媒体和多模式观察的未来健康预测

Proceedings of the 23rd ACM international conference on Multimedia Pub Date : 2015-10-13 DOI: 10.1145/2733373.2806217

Liqiang Nie, Luming Zhang, Yi Yang, Meng Wang, Richang Hong, Tat-Seng Chua

{"title":"Beyond Doctors: Future Health Prediction from Multimedia and Multimodal Observations","authors":"Liqiang Nie, Luming Zhang, Yi Yang, Meng Wang, Richang Hong, Tat-Seng Chua","doi":"10.1145/2733373.2806217","DOIUrl":"https://doi.org/10.1145/2733373.2806217","url":null,"abstract":"Although chronic diseases cannot be cured, they can be effectively controlled as long as we understand their progressions based on the current observational health records, which is often in the form of multimedia data. A large and growing body of literature has investigated the disease progression problem. However, far too little attention to date has been paid to jointly consider the following three observations of the chronic disease progression: 1) the health statuses at different time points are chronologically similar; 2) the future health statuses of each patient can be comprehensively revealed from the current multimedia and multimodal observations, such as visual scans, digital measurements and textual medical histories; and 3) the discriminative capabilities of different modalities vary significantly in accordance to specific diseases. In the light of these, we propose an adaptive multimodal multi-task learning model to co-regularize the modality agreement, temporal progression and discriminative capabilities of different modalities. We theoretically show that our proposed model is a linear system. Before training our model, we address the data missing problem via the matrix factorization approach. Extensive evaluations on a real-world Alzheimer's disease dataset well verify our proposed model. It should be noted that our model is also applicable to other chronic diseases.","PeriodicalId":427170,"journal":{"name":"Proceedings of the 23rd ACM international conference on Multimedia","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116379853","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: 112

A Semantic Geo-Tagged Multimedia-Based Routing in a Crowdsourced Big Data Environment 众包大数据环境下基于语义地理标记的多媒体路由

Proceedings of the 23rd ACM international conference on Multimedia Pub Date : 2015-10-13 DOI: 10.1145/2733373.2807985

F. Rehman, A. Lbath, Abdullah Murad, Mohamed Abdur Rahman, Bilal Sadiq, Akhlaq Ahmad, A. Qamar, Saleh M. Basalamah

{"title":"A Semantic Geo-Tagged Multimedia-Based Routing in a Crowdsourced Big Data Environment","authors":"F. Rehman, A. Lbath, Abdullah Murad, Mohamed Abdur Rahman, Bilal Sadiq, Akhlaq Ahmad, A. Qamar, Saleh M. Basalamah","doi":"10.1145/2733373.2807985","DOIUrl":"https://doi.org/10.1145/2733373.2807985","url":null,"abstract":"Traditional routing algorithms for calculating the fastest or shortest path become ineffective or difficult to use when both source and destination are dynamic or unknown. To solve the problem, we propose a novel semantic routing system that leverages geo-tagged rich crowdsourced multimedia information such as images, audio, video and text to add semantics to the conventional routing. Our proposed system includes a Semantic Multimedia Routing Algorithm (SMRA) that uses an indexed spatial big data environment to answer multimedia spatio-temporal queries in real-time. The results are customized to the users' smartphone bandwidth and resolution requirements. The system has been designed to be able to handle a very large number of multimedia spatio-temporal requests at any given moment. A proof of concept of the system will be demonstrated through two scenarios. These are 1) multimedia enhanced routing and 2) finding lost individuals in a large crowd using multimedia. We plan to test the system's performance and usability during Hajj 2015, where over four million pilgrims from all over the world gather to perform their rituals.","PeriodicalId":427170,"journal":{"name":"Proceedings of the 23rd ACM international conference on Multimedia","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114402739","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: 5

Unsupervised Cosegmentation based on Global Graph Matching 基于全局图匹配的无监督共分割

Proceedings of the 23rd ACM international conference on Multimedia Pub Date : 2015-10-13 DOI: 10.1145/2733373.2806317

Takanori Tamanaha, Hideki Nakayama

引用次数: 2

Dive into Remote Events: Omnidirectional Video Streaming with Acoustic Immersion 潜入远程事件:全向视频流与声沉浸

Proceedings of the 23rd ACM international conference on Multimedia Pub Date : 2015-10-13 DOI: 10.1145/2733373.2807963

D. Ochi, K. Niwa, A. Kameda, Y. Kunita, Akira Kojima

引用次数: 6

Color Photo Makeover via Crowd Sourcing and Recoloring 彩色照片改造通过众包和重新上色

Proceedings of the 23rd ACM international conference on Multimedia Pub Date : 2015-10-13 DOI: 10.1145/2733373.2806370

Wengang Cheng, Ruru Jiang, Chang Wen Chen

引用次数: 4

Joint Modeling of Users' Interests and Mobility Patterns for Point-of-Interest Recommendation 兴趣点推荐中用户兴趣和移动模式的联合建模

Proceedings of the 23rd ACM international conference on Multimedia Pub Date : 2015-10-13 DOI: 10.1145/2733373.2806339

Hongzhi Yin, B. Cui, Zi Huang, Weiqing Wang, X. Wu, Xiaofang Zhou

引用次数: 62

Human Action Recognition With Trajectory Based Covariance Descriptor In Unconstrained Videos 基于轨迹协方差描述符的无约束视频人体动作识别

Proceedings of the 23rd ACM international conference on Multimedia Pub Date : 2015-10-13 DOI: 10.1145/2733373.2806310

Hanli Wang, Yun Yi, Jun Wu

引用次数: 11

Predicting and Understanding Urban Perception with Convolutional Neural Networks 用卷积神经网络预测和理解城市感知

Proceedings of the 23rd ACM international conference on Multimedia Pub Date : 2015-10-13 DOI: 10.1145/2733373.2806273

L. Porzi, S. R. Bulò, B. Lepri, E. Ricci

{"title":"Predicting and Understanding Urban Perception with Convolutional Neural Networks","authors":"L. Porzi, S. R. Bulò, B. Lepri, E. Ricci","doi":"10.1145/2733373.2806273","DOIUrl":"https://doi.org/10.1145/2733373.2806273","url":null,"abstract":"Cities' visual appearance plays a central role in shaping human perception and response to the surrounding urban environment. For example, the visual qualities of urban spaces affect the psychological states of their inhabitants and can induce negative social outcomes. Hence, it becomes critically important to understand people's perceptions and evaluations of urban spaces. Previous works have demonstrated that algorithms can be used to predict high level attributes of urban scenes (e.g. safety, attractiveness, uniqueness), accurately emulating human perception. In this paper we propose a novel approach for predicting the perceived safety of a scene from Google Street View Images. Opposite to previous works, we formulate the problem of learning to predict high level judgments as a ranking task and we employ a Convolutional Neural Network (CNN), significantly improving the accuracy of predictions over previous methods. Interestingly, the proposed CNN architecture relies on a novel pooling layer, which permits to automatically discover the most important areas of the images for predicting the concept of perceived safety. An extensive experimental evaluation, conducted on the publicly available Place Pulse dataset, demonstrates the advantages of the proposed approach over state-of-the-art methods.","PeriodicalId":427170,"journal":{"name":"Proceedings of the 23rd ACM international conference on Multimedia","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121420782","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: 110