2012 IEEE International Symposium on Multimedia最新文献_第7页

Quantifying the Makeup Effect in Female Faces and Its Applications for Age Estimation 女性面部化妆效果的量化及其在年龄估计中的应用

2012 IEEE International Symposium on Multimedia Pub Date : 2012-12-10 DOI: 10.1109/ISM.2012.29

Ranran Feng, B. Prabhakaran

引用次数: 10

Detection and Identification of Chimpanzee Faces in the Wild 野生黑猩猩面孔的检测与识别

2012 IEEE International Symposium on Multimedia Pub Date : 2012-12-10 DOI: 10.1109/ISM.2012.30

A. Loos, Andreas Ernst

引用次数: 13

Energy Consumption Reduction via Context-Aware Mobile Video Pre-fetching 通过上下文感知移动视频预取降低能耗

2012 IEEE International Symposium on Multimedia Pub Date : 2012-12-10 DOI: 10.1109/ISM.2012.56

A. Devlic, P. Lungaro, P. Kamaraju, Z. Segall, Konrad Tollmar

{"title":"Energy Consumption Reduction via Context-Aware Mobile Video Pre-fetching","authors":"A. Devlic, P. Lungaro, P. Kamaraju, Z. Segall, Konrad Tollmar","doi":"10.1109/ISM.2012.56","DOIUrl":"https://doi.org/10.1109/ISM.2012.56","url":null,"abstract":"The arrival of smart phones and tablets, along with a flat rate mobile Internet pricing model have caused increasing adoption of mobile data services. According to recent studies, video has been the main driver of mobile data consumption, having a higher growth rate than any other mobile application. However, streaming a medium/high quality video files can be an issue in a mobile environment where available capacity needs to be shared among a large number of users. Additionally, the energy consumption in mobile devices increases proportionally with the duration of data transfers, which depend on the download data rates achievable by the device. In this respect, adoption of opportunistic content pre-fetching schemes that exploit times and locations with high data rates to deliver content before a user requests it, has the potential to reduce the energy consumption associated with content delivery and improve the user's quality of experience, by allowing playback of pre-stored content with virtually no perceived interruptions or delays. This paper presents a family of opportunistic content pre-fetching schemes and compares their performance to standard on-demand access to content. By adopting a simulation approach on experimental data, collected with monitoring software installed in mobile terminals, we show that content pre-fetching can reduce energy consumption of the mobile devices by up to 30% when compared to the on demand download of the same file, with a time window of 1 hour needed to complete the content prepositioning.","PeriodicalId":282528,"journal":{"name":"2012 IEEE International Symposium on Multimedia","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127519656","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: 13

DLH/CLLS: An Open, Extensible System Design for Prosuming Lecture Recordings and Integrating Multimedia Learning Ecosystems DLH/CLLS:一个开放的，可扩展的系统设计，用于生产讲座录音和集成多媒体学习生态系统

2012 IEEE International Symposium on Multimedia Pub Date : 2012-12-10 DOI: 10.1109/ISM.2012.97

Kai Michael Höver, Gundolf von Bachhaus, M. Hartle, M. Mühlhäuser

引用次数: 12

Using Low Level Gradient Channels for Computationally Efficient Object Detection and Its Application in Logo Detection 基于低梯度通道的高效目标检测及其在Logo检测中的应用

2012 IEEE International Symposium on Multimedia Pub Date : 2012-12-10 DOI: 10.1109/ISM.2012.51

Yu Chen, V. Thing

引用次数: 0

Effective Moving Object Detection and Retrieval via Integrating Spatial-Temporal Multimedia Information

2012 IEEE International Symposium on Multimedia Pub Date : 2012-12-10 DOI: 10.1109/ISM.2012.74

Dianting Liu, M. Shyu

{"title":"Effective Moving Object Detection and Retrieval via Integrating Spatial-Temporal Multimedia Information","authors":"Dianting Liu, M. Shyu","doi":"10.1109/ISM.2012.74","DOIUrl":"https://doi.org/10.1109/ISM.2012.74","url":null,"abstract":"In the area of multimedia semantic analysis and video retrieval, automatic object detection techniques play an important role. Without the analysis of the object-level features, it is hard to achieve high performance on semantic retrieval. As a branch of object detection study, moving object detection also becomes a hot research field and gets a great amount of progress recently. This paper proposes a moving object detection and retrieval model that integrates the spatial and temporal information in video sequences and uses the proposed integral density method (adopted from the idea of integral images) to quickly identify the motion regions in an unsupervised way. First, key information locations on video frames are achieved as maxima and minima of the result of Difference of Gaussian (DoG) function. On the other hand, a motion map of adjacent frames is obtained from the diversity of the outcomes from Simultaneous Partition and Class Parameter Estimation (SPCPE) framework. The motion map filters key information locations into key motion locations (KMLs) where the existence of moving objects is implied. Besides showing the motion zones, the motion map also indicates the motion direction which guides the proposed integral density approach to quickly and accurately locate the motion regions. The detection results are not only illustrated visually, but also verified by the promising experimental results which show the concept retrieval performance can be improved by integrating the global and local visual information.","PeriodicalId":282528,"journal":{"name":"2012 IEEE International Symposium on Multimedia","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129978763","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: 15

Spatio-temporal Gaussian Mixture Model for Background Modeling 背景建模的时空高斯混合模型

2012 IEEE International Symposium on Multimedia Pub Date : 2012-12-10 DOI: 10.1109/ISM.2012.73

Y. Soh, Y. Hae, Intaek Kim

引用次数: 12

Tag Cloud++ - Scalable Tag Clouds for Arbitrary Layouts 标签云++ -可扩展的标签云任意布局

2012 IEEE International Symposium on Multimedia Pub Date : 2012-12-10 DOI: 10.1109/ISM.2012.66

Minwoo Park, D. Joshi, A. Loui

引用次数: 2

A Variational Bayesian Inference Framework for Multiview Depth Image Enhancement 多视角深度图像增强的变分贝叶斯推理框架

2012 IEEE International Symposium on Multimedia Pub Date : 2012-12-10 DOI: 10.1109/ISM.2012.44

P. Rana, Jalil Taghia, M. Flierl

{"title":"A Variational Bayesian Inference Framework for Multiview Depth Image Enhancement","authors":"P. Rana, Jalil Taghia, M. Flierl","doi":"10.1109/ISM.2012.44","DOIUrl":"https://doi.org/10.1109/ISM.2012.44","url":null,"abstract":"In this paper, a general model-based framework for multiview depth image enhancement is proposed. Depth imagery plays a pivotal role in emerging free-viewpoint television. This technology requires high quality virtual view synthesis to enable viewers to move freely in a dynamic real world scene. Depth imagery of different viewpoints is used to synthesize an arbitrary number of novel views. Usually, the depth imagery is estimated individually by stereo-matching algorithms and, hence, shows lack of inter-view consistency. This inconsistency affects the quality of view synthesis negatively. This paper enhances the inter-view consistency of multiview depth imagery by using a variational Bayesian inference framework. First, our approach classifies the color information in the multiview color imagery. Second, using the resulting color clusters, we classify the corresponding depth values in the multiview depth imagery. Each clustered depth image is subject to further sub clustering. Finally, the resulting mean of the sub-clusters is used to enhance the depth imagery at multiple viewpoints. Experiments show that our approach improves the quality of virtual views by up to 0.25 dB.","PeriodicalId":282528,"journal":{"name":"2012 IEEE International Symposium on Multimedia","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133131722","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

Video-Based Lane Detection Using a Fast Vanishing Point Estimation Method 基于视频的车道检测快速消失点估计方法

2012 IEEE International Symposium on Multimedia Pub Date : 2012-12-10 DOI: 10.1109/ISM.2012.70

Burak Benligiray, C. Topal, C. Akinlar

{"title":"Video-Based Lane Detection Using a Fast Vanishing Point Estimation Method","authors":"Burak Benligiray, C. Topal, C. Akinlar","doi":"10.1109/ISM.2012.70","DOIUrl":"https://doi.org/10.1109/ISM.2012.70","url":null,"abstract":"Lane detection algorithms constitute a basis for intelligent vehicle systems such as lane tracking and involuntary lane departure detection. In this paper, we propose a simple and video-based lane detection algorithm that uses a fast vanishing point estimation method. The first step of the algorithm is to extract and validate the line segments from the image with a recently proposed line detection algorithm. In the next step, an angle based elimination of line segments is done according to the perspective characteristics of lane markings. This basic operation removes many line segments that belong to irrelevant details on the scene and greatly reduces the number of features to be processed afterwards. Remaining line segments are extrapolated and superimposed to detect the image location where majority of the linear edge features converge. The location found by this efficient operation is assumed to be the vanishing point. Subsequently, an orientation-based removal is done by eliminating the line segments whose extensions do not intersect the vanishing point. The final step is clustering the remaining line segments such that each cluster represents a lane marking or a boundary of the road (i.e. sidewalks, barriers or shoulders). The properties of the line segments that constitute the clusters are fused to represent each cluster with a single line. The nearest two clusters to the vehicle are chosen as the lines that bound the lane that is being driven on. The proposed algorithm works in an average of 12 milliseconds for each frame with 640×480 resolution on a 2.20 GHz Intel CPU. This performance metric shows that the algorithm can be deployed on minimal hardware and still provide real-time performance.","PeriodicalId":282528,"journal":{"name":"2012 IEEE International Symposium on Multimedia","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124620418","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