Posture recognition plays an important role in many applications,such as security system and monitoring system.Joint quaternion combined with support vector machine(SVM) can solve the problem of moving human posture r...Posture recognition plays an important role in many applications,such as security system and monitoring system.Joint quaternion combined with support vector machine(SVM) can solve the problem of moving human posture recognition.It is a simple and effective algorithm that only three joints are used as the feature points in the whole human skeleton.Using the quaternion of the three joints,a feature vector with five parameters in gait cycle is extracted.The efficiency of the proposed method is demonstrated through an experimental study,and walking and running postures can be distinguished accurately.展开更多
This paper proposes an integrated joint source-channel decoder （I-JSCD） using Max-Log-MAP method for sources encoded with exp-Golomb codes and convolutional codes, and proposes a system applying this method to decod...This paper proposes an integrated joint source-channel decoder （I-JSCD） using Max-Log-MAP method for sources encoded with exp-Golomb codes and convolutional codes, and proposes a system applying this method to decoding the VLC data, e.g. motion vector differences （MVDs）, of H.264 across an AWGN channel. This method combines the source code state-space and the channel code state-space together to construct a joint state-space, develops a 3-D trellis and a maximum a-posterior （MAP） algorithm to estimate the source sequence symbol by symbol, and then uses max-log approximation to simplify the algorithm. Experiments indicate that the proposed system gives significant improvements on peak signal-to-noise ratio （PSNR） （maximum about 15 dB） than a separate scheme. This also leads to a higher visual quality of video stream over a highly noisy channel.展开更多
针对复杂的室内环境下,传统的射频识别技术(radio frequency identification,RFID)室内定位技术获得的接收信号强度特征向量维数较低,不能充分描述环境信息,无法获得良好的定位效果的问题,基于联合指纹提出一种鲁棒性强的高精度室内定...针对复杂的室内环境下,传统的射频识别技术(radio frequency identification,RFID)室内定位技术获得的接收信号强度特征向量维数较低,不能充分描述环境信息,无法获得良好的定位效果的问题,基于联合指纹提出一种鲁棒性强的高精度室内定位算法。该算法首先从RFID阅读器接收到的信号中提取信号强度和相位差数据,建立指纹库。然后利用凹函数递减策略改进PSO算法,优化SVR模型训练样本数据,建立参考标签的指纹特征和其与阅读器距离的映射关系。最后利用改进PSO算法迭代寻优,从而提高室内定位精度和鲁棒性。在仿真中,将该算法与GA-SVR和PSO-SVR算法进行比较,分析了不同指纹数据集和噪声对定位性能的影响。仿真结果表明,在相同指纹数据集和环境下,该算法的定位精度和系统稳定性均优于其他两种算法。展开更多
基金the Key Project of the National Natural Science Foundation of China(No.61134009)National Natural Science Foundations of China(Nos.61473077,61473078,61503075)+6 种基金Cooperative Research Funds of the National Natural Science Funds Overseas and Hong Kong and Macao Scholars,China(No.61428302)Program for Changjiang Scholars from the Ministry of Education,ChinaSpecialized Research Fund for Shanghai Leading Talents,ChinaProject of the Shanghai Committee of Science and Technology,China(No.13JC1407500)Innovation Program of Shanghai Municipal Education Commission,China(No.14ZZ067)Shanghai Pujiang Program,China(No.15PJ1400100)the Fundamental Research Funds for the Central Universities,China(Nos.15D110423,2232015D3-32)
文摘Posture recognition plays an important role in many applications,such as security system and monitoring system.Joint quaternion combined with support vector machine(SVM) can solve the problem of moving human posture recognition.It is a simple and effective algorithm that only three joints are used as the feature points in the whole human skeleton.Using the quaternion of the three joints,a feature vector with five parameters in gait cycle is extracted.The efficiency of the proposed method is demonstrated through an experimental study,and walking and running postures can be distinguished accurately.
基金Supported by the Foundation of Ministry of Education of China (211CERS10)
文摘This paper proposes an integrated joint source-channel decoder （I-JSCD） using Max-Log-MAP method for sources encoded with exp-Golomb codes and convolutional codes, and proposes a system applying this method to decoding the VLC data, e.g. motion vector differences （MVDs）, of H.264 across an AWGN channel. This method combines the source code state-space and the channel code state-space together to construct a joint state-space, develops a 3-D trellis and a maximum a-posterior （MAP） algorithm to estimate the source sequence symbol by symbol, and then uses max-log approximation to simplify the algorithm. Experiments indicate that the proposed system gives significant improvements on peak signal-to-noise ratio （PSNR） （maximum about 15 dB） than a separate scheme. This also leads to a higher visual quality of video stream over a highly noisy channel.
文摘针对复杂的室内环境下,传统的射频识别技术(radio frequency identification,RFID)室内定位技术获得的接收信号强度特征向量维数较低,不能充分描述环境信息,无法获得良好的定位效果的问题,基于联合指纹提出一种鲁棒性强的高精度室内定位算法。该算法首先从RFID阅读器接收到的信号中提取信号强度和相位差数据,建立指纹库。然后利用凹函数递减策略改进PSO算法,优化SVR模型训练样本数据,建立参考标签的指纹特征和其与阅读器距离的映射关系。最后利用改进PSO算法迭代寻优,从而提高室内定位精度和鲁棒性。在仿真中,将该算法与GA-SVR和PSO-SVR算法进行比较,分析了不同指纹数据集和噪声对定位性能的影响。仿真结果表明,在相同指纹数据集和环境下,该算法的定位精度和系统稳定性均优于其他两种算法。
