The wireless visual sensor network(WVSN)as a new emerged intelligent visual system,has been applied in many video monitoring sites.However,there is still great challenge because of the limited wireless network bandwid...The wireless visual sensor network(WVSN)as a new emerged intelligent visual system,has been applied in many video monitoring sites.However,there is still great challenge because of the limited wireless network bandwidth.To resolve the problem,we propose a real-time dynamic texture approach which can detect and reduce the temporal redundancy during many successive image frames.Firstly,an adaptively learning background model is improved to discover successive similar image frames from the inputting video sequence.Then,the dynamic texture model based on the singular value decomposition is adopted to distinguish foreground and background element dynamics.Furthermore,a background discarding strategy based on visual motion coherence is proposed to determine whether each image frame is streamed or not.To evaluate the trade-off performance of the proposed method,it is tested on the CDW-2014 dataset,which can accurately detect the first foreground frame when the moving objects of interest appear in the field of view in the most tested dynamic scenes,and the misdetection rate of the undetected foreground frames is near to zero.Compared to the original stream,it can reduce the occupied bandwidth a lot and its computational cost is relatively lower than the state-of-the-art methods.展开更多
针对无线视频传感器网络(Wireless video sensor networks,WVSN)对视频编码算法的具体需求,提出一种基于运动检测的低复杂度视频编码算法。该算法只对当前编码帧中的运动对象进行编码,并且以面向对象的结构输出码流。实验结果表明,与H....针对无线视频传感器网络(Wireless video sensor networks,WVSN)对视频编码算法的具体需求,提出一种基于运动检测的低复杂度视频编码算法。该算法只对当前编码帧中的运动对象进行编码,并且以面向对象的结构输出码流。实验结果表明,与H.264全I帧编码相比,本文提出的算法编码速度提高了约3倍,编码性能提高了约2 dB。与H.264基本档次相比,虽然编码性能略有下降,但是编码速度平均提高了8倍左右。本文提出的算法可以在编码效率和编码速度之间获得很好的折衷,在一定程度上可以满足WVSN的需求。展开更多
基金the Science and Technology Research Program of Hubei Provincial Department of Education(No.T201805)the PhD Research Startup Foundation of Hubei University of Technology(No.BSQD13032)。
文摘The wireless visual sensor network(WVSN)as a new emerged intelligent visual system,has been applied in many video monitoring sites.However,there is still great challenge because of the limited wireless network bandwidth.To resolve the problem,we propose a real-time dynamic texture approach which can detect and reduce the temporal redundancy during many successive image frames.Firstly,an adaptively learning background model is improved to discover successive similar image frames from the inputting video sequence.Then,the dynamic texture model based on the singular value decomposition is adopted to distinguish foreground and background element dynamics.Furthermore,a background discarding strategy based on visual motion coherence is proposed to determine whether each image frame is streamed or not.To evaluate the trade-off performance of the proposed method,it is tested on the CDW-2014 dataset,which can accurately detect the first foreground frame when the moving objects of interest appear in the field of view in the most tested dynamic scenes,and the misdetection rate of the undetected foreground frames is near to zero.Compared to the original stream,it can reduce the occupied bandwidth a lot and its computational cost is relatively lower than the state-of-the-art methods.
文摘针对无线视频传感器网络(Wireless video sensor networks,WVSN)对视频编码算法的具体需求,提出一种基于运动检测的低复杂度视频编码算法。该算法只对当前编码帧中的运动对象进行编码,并且以面向对象的结构输出码流。实验结果表明,与H.264全I帧编码相比,本文提出的算法编码速度提高了约3倍,编码性能提高了约2 dB。与H.264基本档次相比,虽然编码性能略有下降,但是编码速度平均提高了8倍左右。本文提出的算法可以在编码效率和编码速度之间获得很好的折衷,在一定程度上可以满足WVSN的需求。
