Synergic movement of finger's joints provides human hand tremendous dexterities,and the detection of kinematics parameters is critical to describe and evaluate the kinesiology functions of the fingers.The present ...Synergic movement of finger's joints provides human hand tremendous dexterities,and the detection of kinematics parameters is critical to describe and evaluate the kinesiology functions of the fingers.The present work is the attempt to investigate how the angular velocity and angular acceleration of the joints of index finger vary with respect to time during conducting a motor task.A high-speed video camera has been employed to visually record the movement of index finger,and miniaturized(5-mm diameter) reflective markers have affixed to the subject's index finger on the side close to thumb and dorsum of thumb at different joint landmarks.Captured images have been reviewed frame by frame to get the coordinate values of each joint,and the angular displacements,angular velocities and angular acceleration can be obtained with triangle function.The experiment results show that the methods here can detect the kinematics parameters of index finger joints during moving,and can be a valid route to study the motor function of index finger.展开更多
It is difficult to detect dissolve accurately in video segmentation. Two new parameters AEI and IDM are computed to describe dissolve. An improved method based on the change curves of AEI and IDM is proposed to detect...It is difficult to detect dissolve accurately in video segmentation. Two new parameters AEI and IDM are computed to describe dissolve. An improved method based on the change curves of AEI and IDM is proposed to detect dissolve accurately. The experiments show that this method can detect dissolve accurately.展开更多
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 spatialdomain 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
为了实时识别快速路交织区拥堵瓶颈的形成及其诱发因素,基于无人机航拍视频构建车辆轨迹数据,提出一种融合交通流不稳定性分析的交织区拥堵识别方法。识别方法由车辆轨迹提取、扰动感知模型和拥堵风险指数构建3个阶段构成。首先,通过YOL...为了实时识别快速路交织区拥堵瓶颈的形成及其诱发因素,基于无人机航拍视频构建车辆轨迹数据,提出一种融合交通流不稳定性分析的交织区拥堵识别方法。识别方法由车辆轨迹提取、扰动感知模型和拥堵风险指数构建3个阶段构成。首先,通过YOLOv4(You Only Look Once,Version 4)网络训练航拍小目标权重检测俯拍车辆,关联外观与运动特征以跟踪车辆轨迹,从而提取无人机航拍视频中的精细车辆轨迹。然后,通过提取车辆微观速度、变道、冲突信息建立车速扰动和变道交织扰动感知模型。最后,采用熵值法结合扰动信息与平均车速构建归一化的拥堵风险指数,根据交织流的拥堵风险指数识别拥堵。本文采集广州大桥数据进行案例分析与测试验证。研究结果表明:学习了小目标特征的网络在航拍场景测试的误检率和少检率均低于5%,所提取的车辆轨迹连续稳定;在交织区拥堵识别评价中,本文方法的F1值达到97.85%,明显优于基本参数识别方法,在各路段中具有较高的识别准确度和算法鲁棒性;相比平均速度指标,所提出的拥堵风险指数能够更精细灵敏地反映短时和局部的拥堵,并能够从平均车速、个体车速差异和变道交织3个维度中识别多种因素引起的交织区交通瓶颈。研究结果可为城市重点路段交通诱导与优化提供技术基础。展开更多
基金Supported by the National Natural Science Foundation of China (30770546 )Natural Science Foundation of Chongqing(2006BB2043,2007BB5148)
文摘Synergic movement of finger's joints provides human hand tremendous dexterities,and the detection of kinematics parameters is critical to describe and evaluate the kinesiology functions of the fingers.The present work is the attempt to investigate how the angular velocity and angular acceleration of the joints of index finger vary with respect to time during conducting a motor task.A high-speed video camera has been employed to visually record the movement of index finger,and miniaturized(5-mm diameter) reflective markers have affixed to the subject's index finger on the side close to thumb and dorsum of thumb at different joint landmarks.Captured images have been reviewed frame by frame to get the coordinate values of each joint,and the angular displacements,angular velocities and angular acceleration can be obtained with triangle function.The experiment results show that the methods here can detect the kinematics parameters of index finger joints during moving,and can be a valid route to study the motor function of index finger.
文摘It is difficult to detect dissolve accurately in video segmentation. Two new parameters AEI and IDM are computed to describe dissolve. An improved method based on the change curves of AEI and IDM is proposed to detect dissolve accurately. The experiments show that this method can detect dissolve accurately.
基金Supported by the National Natural Science Foundation of China （ No. 60872123 ） and the Guangdong Provincial Natural Science Foundation （No. U0835001 ）.
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 spatialdomain 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).
文摘为了实时识别快速路交织区拥堵瓶颈的形成及其诱发因素,基于无人机航拍视频构建车辆轨迹数据,提出一种融合交通流不稳定性分析的交织区拥堵识别方法。识别方法由车辆轨迹提取、扰动感知模型和拥堵风险指数构建3个阶段构成。首先,通过YOLOv4(You Only Look Once,Version 4)网络训练航拍小目标权重检测俯拍车辆,关联外观与运动特征以跟踪车辆轨迹,从而提取无人机航拍视频中的精细车辆轨迹。然后,通过提取车辆微观速度、变道、冲突信息建立车速扰动和变道交织扰动感知模型。最后,采用熵值法结合扰动信息与平均车速构建归一化的拥堵风险指数,根据交织流的拥堵风险指数识别拥堵。本文采集广州大桥数据进行案例分析与测试验证。研究结果表明:学习了小目标特征的网络在航拍场景测试的误检率和少检率均低于5%,所提取的车辆轨迹连续稳定;在交织区拥堵识别评价中,本文方法的F1值达到97.85%,明显优于基本参数识别方法,在各路段中具有较高的识别准确度和算法鲁棒性;相比平均速度指标,所提出的拥堵风险指数能够更精细灵敏地反映短时和局部的拥堵,并能够从平均车速、个体车速差异和变道交织3个维度中识别多种因素引起的交织区交通瓶颈。研究结果可为城市重点路段交通诱导与优化提供技术基础。
