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
为了使带宽不同的用户能通过互联网观看数字电视节目,提出了一种将卫星数字电视网络直播的IP(in ternetprotoco l)电视应用方案,采用运动矢量重估计技术来实现M PEG(m ov ing p icture experts group)-2视频到低码率的M PEG-4视频的实...为了使带宽不同的用户能通过互联网观看数字电视节目,提出了一种将卫星数字电视网络直播的IP(in ternetprotoco l)电视应用方案,采用运动矢量重估计技术来实现M PEG(m ov ing p icture experts group)-2视频到低码率的M PEG-4视频的实时转换,从而避免用户带宽的限制。提出了一种运动重估计算法,通过建立运动矢量反向查找表,利用相似宏块重叠面积来优化候选运动矢量的搜索过程,用帧内相邻宏块运动矢量进行估计等方法,显著提高视频转码效率并保证质量。实验结果表明:在视频转码过程中,与采用PM V fast(pred ictive m otion vector fie ld adaptive searchtechn ique)搜索算法相比,该算法能节省40%左右的编码时间,而峰值信噪比降低不足0.3 dB,显著提高了转码效率。展开更多
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）.
文摘为了使带宽不同的用户能通过互联网观看数字电视节目,提出了一种将卫星数字电视网络直播的IP(in ternetprotoco l)电视应用方案,采用运动矢量重估计技术来实现M PEG(m ov ing p icture experts group)-2视频到低码率的M PEG-4视频的实时转换,从而避免用户带宽的限制。提出了一种运动重估计算法,通过建立运动矢量反向查找表,利用相似宏块重叠面积来优化候选运动矢量的搜索过程,用帧内相邻宏块运动矢量进行估计等方法,显著提高视频转码效率并保证质量。实验结果表明:在视频转码过程中,与采用PM V fast(pred ictive m otion vector fie ld adaptive searchtechn ique)搜索算法相比,该算法能节省40%左右的编码时间,而峰值信噪比降低不足0.3 dB,显著提高了转码效率。
