基于Android 2.3.1设计并实现了实时视频流传输系统。视频数据压缩算法采用H264,数据传输使用点对点P2P(Peer to Peer)。系统分两个层次,底层使用C++实现RTP封装与解包、P2P网络传输、视频采集与编解码等;上层使用Java实现对界面的控制...基于Android 2.3.1设计并实现了实时视频流传输系统。视频数据压缩算法采用H264,数据传输使用点对点P2P(Peer to Peer)。系统分两个层次,底层使用C++实现RTP封装与解包、P2P网络传输、视频采集与编解码等;上层使用Java实现对界面的控制。Java界面层通过JNI(Java native interface)调用C++接口,上下层之间无视频数据的拷贝操作,提高了系统性能。同时,设计实现解码错误弹回策略,根据解码错误反馈信息,了解当前网络拥塞情况,灵活调整帧率和压缩图像分辨率。系统在4台三星S5PV210开发板上的运行效果良好。该系统可以作为视频会议、监控系统等的参考或组成部分。展开更多
视频流传输是无线多媒体传感器网络的研究热点.本文提出一种基于蚁群优化的实时视频流分发策略AVSD(ACO based video streaming dissemination),分路由建立,节点内部视频数据分发两个阶段.在现有视频编码技术基础上,利用蚁群优化寻找具...视频流传输是无线多媒体传感器网络的研究热点.本文提出一种基于蚁群优化的实时视频流分发策略AVSD(ACO based video streaming dissemination),分路由建立,节点内部视频数据分发两个阶段.在现有视频编码技术基础上,利用蚁群优化寻找具有不同QoS保障的路径,进行区分优先级的数据分发.仿真结果表明,AVSD策略可有效降低端到端时延,合理利用全网资源,提高网络性能并能够为无线多媒体传感器网络提供较好的视频传输性能.展开更多
A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow ...A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.展开更多
文摘视频流传输是无线多媒体传感器网络的研究热点.本文提出一种基于蚁群优化的实时视频流分发策略AVSD(ACO based video streaming dissemination),分路由建立,节点内部视频数据分发两个阶段.在现有视频编码技术基础上,利用蚁群优化寻找具有不同QoS保障的路径,进行区分优先级的数据分发.仿真结果表明,AVSD策略可有效降低端到端时延,合理利用全网资源,提高网络性能并能够为无线多媒体传感器网络提供较好的视频传输性能.
基金Project(50778015)supported by the National Natural Science Foundation of ChinaProject(2012CB725403)supported by the Major State Basic Research Development Program of China
文摘A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.
