Proceedings of the 21st ACM international conference on Multimedia最新文献_第2页

Learning articulated body models for people re-identification 学习铰接式人体模型，重新识别人

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502147

Davide Baltieri, R. Vezzani, R. Cucchiara

{"title":"Learning articulated body models for people re-identification","authors":"Davide Baltieri, R. Vezzani, R. Cucchiara","doi":"10.1145/2502081.2502147","DOIUrl":"https://doi.org/10.1145/2502081.2502147","url":null,"abstract":"People re-identification is a challenging problem in surveillance and forensics and it aims at associating multiple instances of the same person which have been acquired from different points of view and after a temporal gap. Image-based appearance features are usually adopted but, in addition to their intrinsically low discriminability, they are subject to perspective and view-point issues. We propose to completely change the approach by mapping local descriptors extracted from RGB-D sensors on a 3D body model for creating a view-independent signature. An original bone-wise color descriptor is generated and reduced with PCA to compute the person signature. The virtual bone set used to map appearance features is learned using a recursive splitting approach. Finally, people matching for re-identification is performed using the Relaxed Pairwise Metric Learning, which simultaneously provides feature reduction and weighting. Experiments on a specific dataset created with the Microsoft Kinect sensor and the OpenNi libraries prove the advantages of the proposed technique with respect to state of the art methods based on 2D or non-articulated 3D body models.","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":"82066897","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: 21

Session details: Keynote address 会议详情:主题演讲

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/3245284

David A. Shamma

引用次数: 0

Picture tags and world knowledge: learning tag relations from visual semantic sources 图片标签与世界知识:从视觉语义源学习标签关系

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502113

Lexing Xie, Xuming He

{"title":"Picture tags and world knowledge: learning tag relations from visual semantic sources","authors":"Lexing Xie, Xuming He","doi":"10.1145/2502081.2502113","DOIUrl":"https://doi.org/10.1145/2502081.2502113","url":null,"abstract":"This paper studies the use of everyday words to describe images. The common saying has it that 'a picture is worth a thousand words', here we ask which thousand? The proliferation of tagged social multimedia data presents a challenge to understanding collective tag-use at large scale -- one can ask if patterns from photo tags help understand tag-tag relations, and how it can be leveraged to improve visual search and recognition. We propose a new method to jointly analyze three distinct visual knowledge resources: Flickr, ImageNet/WordNet, and ConceptNet. This allows us to quantify the visual relevance of both tags learn their relationships. We propose a novel network estimation algorithm, Inverse Concept Rank, to infer incomplete tag relationships. We then design an algorithm for image annotation that takes into account both image and tag features. We analyze over 5 million photos with over 20,000 visual tags. The statistics from this collection leads to good results for image tagging, relationship estimation, and generalizing to unseen tags. This is a first step in analyzing picture tags and everyday semantic knowledge. Potential other applications include generating natural language descriptions of pictures, as well as validating and supplementing knowledge databases.","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":"88380513","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: 29

Design, development and evaluation of an adaptive and standardized RTP/RTCP-based IDMS solution 设计、开发和评估自适应和标准化的基于RTP/ rtcp的IDMS解决方案

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502219

M. Montagud

引用次数: 7

Robust facial expressions recognition using 3D average face and ameliorated adaboost 基于三维平均脸和改进adaboost的鲁棒面部表情识别

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502173

Jinhui Chen, Y. Ariki, T. Takiguchi

引用次数: 18

Pl@ntNet mobile app Pl@ntNet移动应用

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502251

H. Goëau, P. Bonnet, A. Joly, V. Bakic, Julien Barbe, Itheri Yahiaoui, Souheil Selmi, Jennifer Carré, D. Barthélémy, N. Boujemaa, J. Molino, Grégoire Duché, Aurélien Péronnet

引用次数: 56

Efficient image and tag co-ranking: a bregman divergence optimization method 高效图像和标签联合排序:一种bregman散度优化方法

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502156

Lin Wu, Yang Wang, J. Shepherd

{"title":"Efficient image and tag co-ranking: a bregman divergence optimization method","authors":"Lin Wu, Yang Wang, J. Shepherd","doi":"10.1145/2502081.2502156","DOIUrl":"https://doi.org/10.1145/2502081.2502156","url":null,"abstract":"Ranking on image search has attracted considerable attentions. Many graph-based algorithms have been proposed to solve this problem. Despite their remarkable success, these approaches are restricted to their separated image networks. To improve the ranking performance, one effective strategy is to work beyond the separated image graph by leveraging fruitful information from manual semantic labeling (i.e., tags) associated with images, which leads to the technique of co-ranking images and tags, a representative method that aims to explore the reinforcing relationship between image and tag graphs. The idea of co-ranking is implemented by adopting the paradigm of random walks. However, there are two problems hidden in co-ranking remained to be open: the high computational complexity and the problem of out-of-sample. To address the challenges above, in this paper, we cast the co-ranking process into a Bregman divergence optimization framework under which we transform the original random walk into an equivalent optimal kernel matrix learning problem. Enhanced by this new formulation, we derive a novel extension to achieve a better performance for both in-sample and out-of-sample cases. Extensive experiments are conducted to demonstrate the effectiveness and efficiency of our approach.","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":"89160786","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: 43

Efficient video quality assessment based on spacetime texture representation 基于时空纹理表示的高效视频质量评估

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502168

Peng Peng, Kevin J. Cannons, Ze-Nian Li

引用次数: 4

What are the distance metrics for local features? 局部特征的距离度量是什么?

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502134

Zhendong Mao, Yongdong Zhang, Q. Tian

{"title":"What are the distance metrics for local features?","authors":"Zhendong Mao, Yongdong Zhang, Q. Tian","doi":"10.1145/2502081.2502134","DOIUrl":"https://doi.org/10.1145/2502081.2502134","url":null,"abstract":"Previous research has found that the distance metric for similarity estimation is determined by the underlying data noise distribution. The well known Euclidean(L2) and Manhattan (L1) metrics are then justified when the additive noise are Gaussian and Exponential, respectively. However, finding a suitable distance metric for local features is still a challenge when the underlying noise distribution is unknown and could be neither Gaussian nor Exponential. To address this issue, we introduce a modeling framework for arbitrary noise distributions and propose a generalized distance metric for local features based on this framework. We prove that the proposed distance is equivalent to the L1 or the L2 distance when the noise is Gaussian or Exponential. Furthermore, we justify the Hamming metric when the noise meets the given conditions. In that case, the proposed distance is a linear mapping of the Hamming distance. The proposed metric has been extensively tested on a benchmark data set with five state-of-the-art local features: SIFT, SURF, BRIEF, ORB and BRISK. Experiments show that our framework better models the real noise distributions and that more robust results can be obtained by using the proposed distance metric.","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":"87439925","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: 3

Joserlin: joint request and service scheduling for peer-to-peer non-linear media access 点对点非线性媒体访问的联合请求和服务调度

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502090

Z. Zhao, Wei Tsang Ooi

引用次数: 4