The object-based scalable coding in MPEG-4 is investigated, and a prioritized transmission scheme of MPEG-4 audio-visual objects （AVOs） over the DiffServ network with the QoS guarantee is proposed. MPEG-4 AVOs are e...The object-based scalable coding in MPEG-4 is investigated, and a prioritized transmission scheme of MPEG-4 audio-visual objects （AVOs） over the DiffServ network with the QoS guarantee is proposed. MPEG-4 AVOs are extracted and classified into different groups according to their priority values and scalable layers （visual importance）. These priority values are mapped to the 1P DiffServ per hop behaviors （PHB）. This scheme can selectively discard packets with low importance, in order to avoid the network congestion. Simulation results show that the quality of received video can gracefully adapt to network state, as compared with the ‘best-effort＇ manner. Also, by allowing the content provider to define prioritization of each audio-visual object, the adaptive transmission of object-based scalable video can be customized based on the content.展开更多
This paper proposes a mobile video surveillance system consisting of intelligent video analysis and mobile communication networking. This multilevel distillation approach helps mobile users monitor tremendous surveill...This paper proposes a mobile video surveillance system consisting of intelligent video analysis and mobile communication networking. This multilevel distillation approach helps mobile users monitor tremendous surveillance videos on demand through video streaming over mobile communication networks. The intelligent video analysis includes moving object detection/tracking and key frame selection which can browse useful video clips. The communication networking services, comprising video transcoding, multimedia messaging, and mobile video streaming, transmit surveillance information into mobile appliances. Moving object detection is achieved by background subtraction and particle filter tracking. Key frame selection, which aims to deliver an alarm to a mobile client using multimedia messaging service accompanied with an extracted clear frame, is reached by devising a weighted importance criterion considering object clarity and face appearance. Besides, a spatial- domain cascaded transcoder is developed to convert the filtered image sequence of detected objects into the mobile video streaming format. Experimental results show that the system can successfully detect all events of moving objects for a complex surveillance scene, choose very appropriate key frames for users, and transcode the images with a high power signal-to-noise ratio （PSNR）.展开更多
文章在"以用户为中心"的理念指导下,在分析用户需求和学习特性的基础上,以构建符合干部网络学习的模式为主线,选用Flash Media System为流媒体解决方案,构建干部网络教育平台。平台集中了多渠道的网络教育资源,进行资源编码、...文章在"以用户为中心"的理念指导下,在分析用户需求和学习特性的基础上,以构建符合干部网络学习的模式为主线,选用Flash Media System为流媒体解决方案,构建干部网络教育平台。平台集中了多渠道的网络教育资源,进行资源编码、Web内容管理等预处理后通过点播、直播提供给平台用户,并采用内容分发和负载均衡技术将平台继续延伸。分角色设计的网络学习流程以及在网络学习支持服务特别是资源检索、评价与推送机制上的初步应用都使用户获得良好的网络学习体验。今后平台还需在学习者与资源、与管理者的互动机制上做进一步研究。展开更多
针对现有多目标跟踪方法易受到遮挡、运动模糊等问题干扰的情况,提出基于轨迹掩膜的在线多目标跟踪方法(online multi-object tracking method based on trajectory mask,OMTMTM)。提出轨迹掩膜生成算法,利用前一帧跟踪轨迹结果生成轨...针对现有多目标跟踪方法易受到遮挡、运动模糊等问题干扰的情况,提出基于轨迹掩膜的在线多目标跟踪方法(online multi-object tracking method based on trajectory mask,OMTMTM)。提出轨迹掩膜生成算法,利用前一帧跟踪轨迹结果生成轨迹掩膜,设计轨迹掩膜网络对轨迹掩膜提取多维度特征,包含目标可见区域的估计值、大致位置及形状等信息;将该特征与基础骨干网络提取的原始图像特征融合后进行多目标检测跟踪。OMTMTM的目标跟踪器具备先验判断能力,可实现遮挡情况下的准确跟踪;OMTMTM利用目标跟踪轨迹的时空信息,恢复出部分漏检或低置信待检目标,使轨迹掩膜更加合理,有利于后续跟踪。对OMTMTM的性能进行多维度评估,并结合基线模型进行对比分析。试验结果表明,OMTMTM具有先进的多目标跟踪性能。展开更多
随着无线网络中视频流量的增长,内容分发网络和移动边缘计算技术被视为应对这一挑战的有效方案,其中缓存策略问题是研究的重要内容。面对不同的应用场景和需求,设计缓存策略时会考虑不同的优化目标。文中重点考虑了两个优化目标的公平...随着无线网络中视频流量的增长,内容分发网络和移动边缘计算技术被视为应对这一挑战的有效方案,其中缓存策略问题是研究的重要内容。面对不同的应用场景和需求,设计缓存策略时会考虑不同的优化目标。文中重点考虑了两个优化目标的公平性问题。对视频服务商而言,用户满意度(Quality of Experience,QoE)体现了服务的质量,而能量效率体现了成本效益和节能指标。在设计缓存策略时,由于无法明确哪个目标的优先级更高,因此需要对它们进行公平地优化。首先,对缓存策略问题的两个重要目标(QoE和能量效率)进行数学建模,并提出了公平性原则。然后,将这两个优化目标作为博弈对象,代入纳什议价博弈模型中。接着,提出了一种确保公平性的多回合议价算法,并证明了该算法的合理性和有效性。最后,仿真实验验证,该算法能够在优化缓存策略的QoE和能量效率的同时保证它们之间的公平性。展开更多
文摘The object-based scalable coding in MPEG-4 is investigated, and a prioritized transmission scheme of MPEG-4 audio-visual objects （AVOs） over the DiffServ network with the QoS guarantee is proposed. MPEG-4 AVOs are extracted and classified into different groups according to their priority values and scalable layers （visual importance）. These priority values are mapped to the 1P DiffServ per hop behaviors （PHB）. This scheme can selectively discard packets with low importance, in order to avoid the network congestion. Simulation results show that the quality of received video can gracefully adapt to network state, as compared with the ‘best-effort＇ manner. Also, by allowing the content provider to define prioritization of each audio-visual object, the adaptive transmission of object-based scalable video can be customized based on the content.
文摘This paper proposes a mobile video surveillance system consisting of intelligent video analysis and mobile communication networking. This multilevel distillation approach helps mobile users monitor tremendous surveillance videos on demand through video streaming over mobile communication networks. The intelligent video analysis includes moving object detection/tracking and key frame selection which can browse useful video clips. The communication networking services, comprising video transcoding, multimedia messaging, and mobile video streaming, transmit surveillance information into mobile appliances. Moving object detection is achieved by background subtraction and particle filter tracking. Key frame selection, which aims to deliver an alarm to a mobile client using multimedia messaging service accompanied with an extracted clear frame, is reached by devising a weighted importance criterion considering object clarity and face appearance. Besides, a spatial- domain cascaded transcoder is developed to convert the filtered image sequence of detected objects into the mobile video streaming format. Experimental results show that the system can successfully detect all events of moving objects for a complex surveillance scene, choose very appropriate key frames for users, and transcode the images with a high power signal-to-noise ratio （PSNR）.
文摘文章在"以用户为中心"的理念指导下,在分析用户需求和学习特性的基础上,以构建符合干部网络学习的模式为主线,选用Flash Media System为流媒体解决方案,构建干部网络教育平台。平台集中了多渠道的网络教育资源,进行资源编码、Web内容管理等预处理后通过点播、直播提供给平台用户,并采用内容分发和负载均衡技术将平台继续延伸。分角色设计的网络学习流程以及在网络学习支持服务特别是资源检索、评价与推送机制上的初步应用都使用户获得良好的网络学习体验。今后平台还需在学习者与资源、与管理者的互动机制上做进一步研究。
文摘针对现有多目标跟踪方法易受到遮挡、运动模糊等问题干扰的情况,提出基于轨迹掩膜的在线多目标跟踪方法(online multi-object tracking method based on trajectory mask,OMTMTM)。提出轨迹掩膜生成算法,利用前一帧跟踪轨迹结果生成轨迹掩膜,设计轨迹掩膜网络对轨迹掩膜提取多维度特征,包含目标可见区域的估计值、大致位置及形状等信息;将该特征与基础骨干网络提取的原始图像特征融合后进行多目标检测跟踪。OMTMTM的目标跟踪器具备先验判断能力,可实现遮挡情况下的准确跟踪;OMTMTM利用目标跟踪轨迹的时空信息,恢复出部分漏检或低置信待检目标,使轨迹掩膜更加合理,有利于后续跟踪。对OMTMTM的性能进行多维度评估,并结合基线模型进行对比分析。试验结果表明,OMTMTM具有先进的多目标跟踪性能。
文摘随着无线网络中视频流量的增长,内容分发网络和移动边缘计算技术被视为应对这一挑战的有效方案,其中缓存策略问题是研究的重要内容。面对不同的应用场景和需求,设计缓存策略时会考虑不同的优化目标。文中重点考虑了两个优化目标的公平性问题。对视频服务商而言,用户满意度(Quality of Experience,QoE)体现了服务的质量,而能量效率体现了成本效益和节能指标。在设计缓存策略时,由于无法明确哪个目标的优先级更高,因此需要对它们进行公平地优化。首先,对缓存策略问题的两个重要目标(QoE和能量效率)进行数学建模,并提出了公平性原则。然后,将这两个优化目标作为博弈对象,代入纳什议价博弈模型中。接着,提出了一种确保公平性的多回合议价算法,并证明了该算法的合理性和有效性。最后,仿真实验验证,该算法能够在优化缓存策略的QoE和能量效率的同时保证它们之间的公平性。
