2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras最新文献_第2页

Smart camera design for realtime high dynamic range imaging 智能相机设计，实时高动态范围成像

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras Pub Date : 2011-10-13 DOI: 10.1109/ICDSC.2011.6042918

Pierre-Jean Lapray, B. Heyrman, M. Rossé, D. Ginhac

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引用次数: 12

Demo: Real-time depth extraction and viewpoint interpolation on FPGA 演示:基于FPGA的实时深度提取和视点插值

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras Pub Date : 2011-10-13 DOI: 10.1109/ICDSC.2011.6042943

Guanyu Yi, H. Yeh, G. Vanmeerbeeck, Ke Zhang, G. Lafruit

{"title":"Demo: Real-time depth extraction and viewpoint interpolation on FPGA","authors":"Guanyu Yi, H. Yeh, G. Vanmeerbeeck, Ke Zhang, G. Lafruit","doi":"10.1109/ICDSC.2011.6042943","DOIUrl":"https://doi.org/10.1109/ICDSC.2011.6042943","url":null,"abstract":"In this demo, we demonstrate a real-time viewpoint interpolation application on FPGA. Viewpoint interpolation is the process of synthesizing plausible in-between views — so-called virtual camera views — from a couple of surrounding fixed camera views. Stereo matching is used to extract depth information, by computing a disparity map from a pair of input images. With the depth information, virtual views at any points between the two cameras are computed through view interpolation. To make viewpoint interpolation possible for low/moderate-power consumer applications, a further quality/complexity tradeoff study is required to conciliate algorithmic quality to architectural performance. In essence, the inter-dependencies between the different algorithmic steps in the processing chain are thoroughly analyzed, aiming at an overall quality-performance model that pinpoints which algorithmic functionalities can be simplified with minor (preferably no) global input-output quality degradation, while maximally reducing their implementation complexity w.r.t. arithmetic and line buffer requirements. Compared to state-of-the-art CPU and GPU platforms running at several GHz clock speed, our low-power 65 MHz FPGA implementation achieves speedups with one order of magnitude over state-of-the-art, without impeding on the visual quality, reaching over 60 frames per second high-definition (1024×768) high-quality, 64-disparity search range stereo matching and enabling viewpoint interpolation in low-power, embedded applications.","PeriodicalId":385052,"journal":{"name":"2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128819822","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

A socio-economic approach to online vision graph generation and handover in distributed smart camera networks 分布式智能摄像机网络中在线视觉图生成与切换的社会经济方法

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras Pub Date : 2011-10-13 DOI: 10.1109/ICDSC.2011.6042902

Lukas Esterle, Peter R. Lewis, Marcin Bogdański, B. Rinner, X. Yao

引用次数: 38

PhD forum: BiSeeMos: A fast embedded stereo smart camera 博士论坛:BiSeeMos:一个快速嵌入式立体智能相机

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras Pub Date : 2011-10-13 DOI: 10.1109/ICDSC.2011.6042960

Frantz Pelissier, F. Berry

引用次数: 1

Demo: Real-time 3D visualization of multi-camera room occupancy monitoring for immersive communication systems 演示:用于沉浸式通信系统的多摄像头房间占用监控的实时3D可视化

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras Pub Date : 2011-10-13 DOI: 10.1109/ICDSC.2011.6042956

Aljosha Demeulemeester, Charles-Frederik Hollemeersch, P. Lambert, R. Walle, Vedran Jelaca, Sebastian Gruenwedel, Jorge Oswaldo Niño Castañeda, Dimitri Van Cauwelaert, P. Veelaert, P. V. Hese, W. Philips

引用次数: 0

Local image quality metric for a distributed smart camera network with overlapping FOVs 具有重叠视场的分布式智能摄像机网络的局部图像质量度量

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras Pub Date : 2011-10-13 DOI: 10.1109/ICDSC.2011.6042920

E. Shen, R. Hornsey

引用次数: 7

Fusion of multiple trackers in video networks 视频网络中多跟踪器的融合

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras Pub Date : 2011-10-13 DOI: 10.1109/ICDSC.2011.6042927

Yiming Li, B. Bhanu

引用次数: 4

Distributed smart cameras for hard real-time obstacle detection in control applications 用于控制应用中硬实时障碍物检测的分布式智能摄像机

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras Pub Date : 2011-10-13 DOI: 10.1109/ICDSC.2011.6042935

Herwig Guggi, B. Rinner

引用次数: 4

PhD forum: A cyber-physical system approach to embedded visual servoing 博士论坛:嵌入式视觉伺服的网络物理系统方法

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras Pub Date : 2011-10-13 DOI: 10.1109/ICDSC.2011.6042950

Zhenyu Ye, H. Corporaal, P. Jonker

引用次数: 2

Real-time multi-view human action recognition using a wireless camera network 利用无线摄像机网络进行实时多视角人体动作识别

2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras Pub Date : 2011-10-13 DOI: 10.1109/ICDSC.2011.6042901

Sricharan Ramagiri, R. Kavi, V. Kulathumani

{"title":"Real-time multi-view human action recognition using a wireless camera network","authors":"Sricharan Ramagiri, R. Kavi, V. Kulathumani","doi":"10.1109/ICDSC.2011.6042901","DOIUrl":"https://doi.org/10.1109/ICDSC.2011.6042901","url":null,"abstract":"In this paper, we describe how information obtained from multiple views using a network of cameras can be effectively combined to yield a reliable and fast human action recognition system. We describe a score-based fusion technique for combining information from multiple cameras that can handle arbitrary orientation of the subject with respect to the cameras. Our fusion technique does not rely on a symmetric deployment of the cameras and does not require that camera network deployment configuration be preserved between training and testing phases. To classify human actions, we use motion information characterized by the spatio-temporal shape of a human silhouette over time. By relying on feature vectors that are relatively easy to compute, our technique lends itself to an efficient distributed implementation while maintaining a high frame capture rate. We evaluate the performance of our system under different camera densities and view availabilities. Finally, we demonstrate the performance of our system in an online setting where the camera network is used to identify human actions as they are being performed.","PeriodicalId":385052,"journal":{"name":"2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122396490","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: 50