Pull-based P2P live streaming is a promising solution for the large scale streaming systems, like PPStream, PPlive, due to its high scalability, low cost and high resilience. However, they usually suffer from bad dela...Pull-based P2P live streaming is a promising solution for the large scale streaming systems, like PPStream, PPlive, due to its high scalability, low cost and high resilience. However, they usually suffer from bad delay performance. In this paper, we seek to improve the delay performance under ensuring video display quality stemming from chunk scheduling. And so we model Pull-based chunk scheduling problem as a multi-objective optimization problem to minimize the video delay and maximize video display quality in the environment of heterogeneous upload bandwidths, heterogeneous and dynamic propagation delays. Finally we put up with a greedy Pull-based scheduling approach(GPSA) to solve the optimization problem. The evaluation shows GPSA can outperform two classical chunk scheduling approaches and adapt to dynamic variance of propagation delays.展开更多
We present an algorithm which can realize mobile robot in unknown outdoor environments, which 3D stereo vision simultaneous localization and mapping （SLAM） for means the 6-DOF motion and a sparse but persistent map ...We present an algorithm which can realize mobile robot in unknown outdoor environments, which 3D stereo vision simultaneous localization and mapping （SLAM） for means the 6-DOF motion and a sparse but persistent map of natural landmarks be constructed online only with a stereo camera. In mobile robotics research, we extend FastSLAM 2.0 like stereo vision SLAM with ＂pure vision＂ domain to outdoor environments. Unlike popular stochastic motion model used in conventional monocular vision SLAM, we utilize the ideas of structure from motion （SFM） for initial motion estimation, which is more suitable for the robot moving in large-scale outdoor, and textured environments. SIFT features are used as natural landmarks, and its 3D positions are constructed directly through triangulation. Considering the computational complexity and memory consumption, Bkd-tree and Best-Bin-First （BBF） search strategy are utilized for SIFT feature descriptor matching. Results show high accuracy of our algorithm, even in the circumstance of large translation and large rotation movements.展开更多
基金supported by National Key Basic Research Program of China(973 Program)(2009CB320504)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 60821001)+1 种基金Beijing Municipal Commission of Education to build the project special,Research Fund for the Doctoral Program of Higher Education of China (20090005120012)National Natural Science Foundation (60672121)
文摘Pull-based P2P live streaming is a promising solution for the large scale streaming systems, like PPStream, PPlive, due to its high scalability, low cost and high resilience. However, they usually suffer from bad delay performance. In this paper, we seek to improve the delay performance under ensuring video display quality stemming from chunk scheduling. And so we model Pull-based chunk scheduling problem as a multi-objective optimization problem to minimize the video delay and maximize video display quality in the environment of heterogeneous upload bandwidths, heterogeneous and dynamic propagation delays. Finally we put up with a greedy Pull-based scheduling approach(GPSA) to solve the optimization problem. The evaluation shows GPSA can outperform two classical chunk scheduling approaches and adapt to dynamic variance of propagation delays.
基金Project supported by the National Natural Science Foundation of China (Nos. 60534070 and 60505017)the Science PlanningProject of Zhejiang Province (No. 2005C14008), China
文摘We present an algorithm which can realize mobile robot in unknown outdoor environments, which 3D stereo vision simultaneous localization and mapping （SLAM） for means the 6-DOF motion and a sparse but persistent map of natural landmarks be constructed online only with a stereo camera. In mobile robotics research, we extend FastSLAM 2.0 like stereo vision SLAM with ＂pure vision＂ domain to outdoor environments. Unlike popular stochastic motion model used in conventional monocular vision SLAM, we utilize the ideas of structure from motion （SFM） for initial motion estimation, which is more suitable for the robot moving in large-scale outdoor, and textured environments. SIFT features are used as natural landmarks, and its 3D positions are constructed directly through triangulation. Considering the computational complexity and memory consumption, Bkd-tree and Best-Bin-First （BBF） search strategy are utilized for SIFT feature descriptor matching. Results show high accuracy of our algorithm, even in the circumstance of large translation and large rotation movements.
