基于动作图像特征的人体运动行为挖掘算法

研究人体行为图像特征识别问题,在人体动作图像中存在大量的和真实行为无关的掩饰动作特征,掩饰动作的存在会大大干扰人体真实行为特征,造成行为真实特征关联的减弱,形成干扰.传统的关联特征挖掘方法在关联干扰的情况下,很难建立准确的行为特征对应空间,使得关联性发生混乱,造成行为特征挖掘错误.提出了一种采用动作特征人体运行行为挖掘算法.利用黄金分割方法,计算动作特征的权值比重,从而删除冗余特征,为人体行为挖掘提供准确的数据基础.利用非线性分类函数,对人体行为特征进行分类,从而实现人体运动行为的挖掘.实验结果表明,利用改进算法能够有效提高人体运动行为识别的准确性,从而有效地对人体运动行为进行有效识别.     

基于运动矢量交点密集度的人群恐慌行为检测

为了更准确有效的识别人群恐慌行为,本文提出了一种利用视频中人群运动矢量的交点密集度来判断人群恐慌异常的新算法.该算法以LK光流法为基础来提取运动人群的运动矢量信息,接着通过获得的信息求取运动矢量间的两两交叉点,然后运用分块法求得区域交叉点密集度,并以此来识别人群异常.对多个视频进行测试,测试结果表明:该算法能够以较高正确率识别视频中人群的恐慌行为.     

监控视频中的车辆异常行为检测

针对人工监测道路上车辆超速、违规变道和闯红灯等车辆异常行为各种弊端,提出了一种基于监控视频的车辆异常行为检测方法. 首先使用ViBe（Visual Background Extractor）算法得到车辆的前景图像,利用金字塔Lucas-Kanada光流法跟踪前景图像中的强角点并计算出该点的速度和角度,再利用均值漂移算法对速度和角度两个运动特征标量聚类,经统计得到聚类后的统计直方图. 最后,分别通过运动特征熵和运动特征标量到聚类中心的欧式距离2种方法判断车辆有无异常行为. 实验结果表明,2种方法能够准确、实时地检测出道路中的车辆异常行为.     

基于光流特征与序列比对的实时行为识别*

提出一种基于光流特征与序列比对的行为识别算法.首先利用分层光流提取视频序列中的运动信息;然后用光流场的方向直方图构造相应行为的模板库和索引序列库;最后用序列比对方法实现行为识别.实验结果表明,该算法可在线进行人的典型行为识别,对目标尺度变化、小角度倾斜和旋转具有一定程度的鲁棒性.目前以该算法为核心的行为识别实验系统对图像尺寸为320×240的序列平均处理速度达到10 fps.     

基于图像处理的中心煤气流分布识别方法

研究中心煤气流分布准确识别的问题.利用传统算法进行中心煤气流识别,在数据采集的过程中容易受到高炉内复杂环境因素的干扰,导致原料运动规律发生改变,从而无法准确描述料层中物质的运动状态,难以建立准确的机理模型,最终降低了中心煤气流分布识别的准确性.为了避免上述缺陷,提出了一种基于模糊聚类算法的中心煤气流分布识别方法.利用小波空域变换方法,对采集的图像进行滤波处理,从而提高了中心煤气流分布识别的准确性.利用模糊聚类方法,对中心煤气流分布情况进行准确的识别.实验结果表明,利用本文算法进行中心煤气流分布识别,可以极大地提高识别的准确性,从而满足实际冶金生产的需求.     

基于光流法运动配准的覆冰图像超分辨率重建

针对电力监控系统中输电线路易晃动造成覆冰图像模糊,提出基于光流法运动配准的覆冰图像超分辨率重建算法。该算法首先利用基于光流法的图像配准算法估计图像间的亚像素级运动矢量,得到前向和后向配准图像;然后,利用迭代反投影(IBP)算法对估计出的图像分别进行超分辨率重建;最后,根据配准误差加权得到最终的输出图像。实验结果表明,相对于传统算法,该算法的重建结果无论是在峰值信噪比和标准差还是基于对比敏感度的无参考图像清晰度上,均有明显提高,具有较好的客观指标和视觉效果。     

基于光流的ATM机异常行为实时检测

异常行为检测在自助银行智能监控系统领域中有广泛的应用前景.本文针对此应用领域,提出了基于区域光流特征的异常行为检测方法.首先利用混合高斯模型来表示背景像素的变化并自适应更新背景模型,用背景差法从视频序列中提取运动前景;采用lucas-kanade光流法计算出运动区域内的光流信息.采用基于幅值的加权方向直方图描述行为,计算区域内直方图的运动熵发现候选异常区域,再利用支持向量机进行分类.从实验结果可以看出,能够较好的识别出异常事件,并且实时性较好,能够满足实际应用需求.     

基于深度学习与稀疏光流的人群异常行为识别

目前公共场所人群异常行为检测的异常种类检测准确率较低,且多数对突然奔跑等部分异常行为无法识别.为此,提出一种基于YOLO_v3与稀疏光流的人群异常行为识别算法,通过检测小团体异常为群体异常预警与采取相应的应急措施提供充足的时间.为方便定位异常发生区域,将视频分割为多个子区域,通过获取子区域的图像样本进行诱发群体异常的小团体异常检测,利用改进YOLO_v3神经网络对传统算法较难检测行人持棍、持枪、持刀与面部遮挡等异常进行检测,在未检测到上述异常诱因时,使用稀疏光流法获取人群平均动能与运动方向熵,将得到的特征数据通过PSO-ELM进行分类,区分正常行为与同向突散或无规则突散.实验结果表明,与现有同类算法相比,该算法能有效检测行人持械与面部遮挡等小团体异常,并且定位异常发生区域的准确率达到98.227%.     

一种新型的嵌入式智能图像传感器设计

提出并设计一种新型的嵌入式智能图像传感器,该传感器具备一定的室外场景(主要为道路和公共场所)状态感知能力,适用于分布式智能视频监控系统.本文采用基于统计学习的方法实现了运动前景图像检测和阴影消除,并在此基础上完成运动目标行为分析,实现了关键区域保护、监控目标移动检测以及镜头遮挡保护等智能视频监控功能.本文所设计的视觉分析算法适用于复杂的室外环境,适合于实时计算.在算法的实现中充分利用了该嵌入式智能图像传感器硬件设计的优点,在实验中取得了良好的效果.     

基于动态帧间间隔更新的人群异常行为检测

针对视频监控中人群异常行为检测方面存在的实时性和准确性问题,本文基于金字塔LK光流法提出一种动态帧间间隔更新的人群异常行为检测的方法. 该算法通过提取的人群运动信息来动态更新帧间间隔,接着以该帧间间隔来检测人群运动信息. 这样,算法不仅保留了原算法在检测人群运动信息方面优点,且有效提高了算法的运行效率. 最后,该算法通过获取的人群运动矢量交点密集度及能量信息来识别人群异常行为. 对多个视频进行测试,测试结果表明,该算法能够以较高正确率识别视频中人群的异常行为,同时还有效提高了算法的运行速度.     

基于运动的摄像机定标方法的综述

该文从运动方式角度将摄像机定标方式分为非限定运动方式和限定运动方式两大类,分别对摄像机各种运动方式对定标技术的影响进行了系统的研究,在应用中应该根据具体情况选择合适的摄像机的运动方式,以满足实际问题的需要。     

Robocup小型足球机器人的运动分析与控制--Robocup系列研究之三

足球机器人运动控制要求灵活、快速、准确。通过对足球机器人的结构及车轮分析，对足球机器人的轨迹控制进行运动学分析，在运动学分析的基础上提出一种比较好的控制方法，从而实现足球机器人的轨迹控制。试验结果表明足球机器人轨迹控制达到设计要求。     

Discriminative functional analysis of human movements

This paper investigates the use of statistical dimensionality reduction (DR) techniques for discriminative low dimensional embedding to enable affective movement recognition. Human movements are defined by a collection of sequential observations (time-series features) representing body joint angle or joint Cartesian trajectories. In this work, these sequential observations are modelled as temporal functions using B-spline basis function expansion, and dimensionality reduction techniques are adapted to enable application to the functional observations. The DR techniques adapted here are: Fischer discriminant analysis (FDA), supervised principal component analysis (PCA), and Isomap. These functional DR techniques along with functional PCA are applied on affective human movement datasets and their performance is evaluated using leave-one-out cross validation with a one-nearest neighbour classifier in the corresponding low-dimensional subspaces. The results show that functional supervised PCA outperforms the other DR techniques examined in terms of classification accuracy and time resource requirements.     

卸载过程的物料运动研究

在物料输送中卸载过程的物料运动是非常复杂的。利用运动学原理分析了物料的受力情况,解析了水平输送、倾斜向上输送和倾斜向下输送3种情况时临界状态发生的条件,确定了输送带以不同角度趋入滚筒时物料被抛出的始点位置和切线角,研究了物料在输送带上的运动状况并得出结论,最后建立卸料轨迹方程,用计算机实现了轨迹线的绘制。     

The influence of combined visual and tactile information on finger and eye movements during shape tracing

Abstract

Adaptation experiments in shape tracing were conducted to investigate finger and eye movements in various conditions of visual and tactile information. Maximum velocity, mean velocity, maximum acceleration and reacceleration point were calculated from finger movements. Number of eye fixations and lead time of eye fixation to finger position were calculated from eye movements. The results showed that for the finger movement the values of the indices studied were higher in the combined visual and tactile condition than in the visual only condition. The number of eye fixations decreased when subjects repeated the tracing and was more marked in the combined visual and tactile condition than in the visual only condition. The results suggest that finger movements become faster and use of vision is reduced when both visual and tactile information are given.     

Jyotish: Constructive approach for context predictions of people movement from joint Wifi/Bluetooth trace

It is well known that people movement exhibits a high degree of repetition since people visit regular places and make regular contacts for their daily activities. This paper¹ presents a novel framework named Jyotish,² which constructs a predictive model by exploiting the regularity of people movement found in the real joint Wifi/Bluetooth trace. The constructed model is able to answer three fundamental questions: (1) where the person will stay, (2) how long she will stay at the location, and (3) who she will meet.In order to construct the predictive model, Jyotish includes an efficient clustering algorithm to cluster Wifi access point information in the Wifi trace into locations. Then, we construct a Naive Bayesian classifier to assign these locations to records in the Bluetooth trace and obtain a fine granularity of people movement. Next, the fine grain movement trace is used to construct the predictive model including location predictor, stay duration predictor, and contact predictor to provide answers for three questions above. Finally, we evaluate the constructed predictive model over the real Wifi/Bluetooth trace collected by 50 participants in University of Illinois campus from March to August 2010. Evaluation results show that Jyotish successfully constructs a predictive model, which provides a considerably high prediction accuracy of people movement.     

Evaluation of eye,head and trunk coordination during target tracking tasks

This study tested the feasibility of a method to synchronise and to evaluate eye, head and trunk movement patterns during target tracking tasks performed by 10 subjects. A projected central target was randomly repositioned at 40° and 70° of rotation to the left and right. Subjects were instructed to change gaze as quickly as possible. Head and trunk motion was measured using a motion analysis system, and eye movement was measured using an eye-tracker; all data were synchronised. For healthy subjects, the eye moved faster than the head, there was no trunk movement and the head moved more than the eye to reach further displaced targets. The method tested was feasible, and it could be used to evaluate eye, head and trunk movement patterns of subjects with injuries such as whiplash and concussions.

Practitioner Summary: Studies of eye, head and trunk movements using synchronised methods are needed. We tested the feasibility of a method to synchronise and evaluate eye, head and trunk movement patterns. The method tested was feasible, and it could be used to evaluate movement patterns of subjects with injuries such as whiplash.     

GPS位置历史挖掘和移动轨迹异常检测系统的设计与实现

为了发现候鸟的公共移动模式和异常迁徙行为, 通过对候鸟位置历史数据建模, 设计与实现了位置历史挖掘和异常检测系统, 分析并可视化展示候鸟迁徙过程中经停地和移动序列的分布状况及其重要性。通过计算候鸟移动序列相符度并可视化展示结果, 发现候鸟迁徙的公共模式和异常行为。使用青海湖斑头雁的卫星遥测数据验证了这一系统, 结果发现了斑头雁的三个公共移动模式和三个异常迁徙行为, 验证了该系统的有效性。     

Communication Interface with Eye-Gaze and Head Gesture Using Successive DP Matching and Fuzzy Inference

This paper proposes a communication interface with eye-gaze and head gesture. Visual sensorimotor integration with eye-head cooperation is considered, especially head gesture accompanied with vestibulo-ocular reflex is used for selecting object in the screen. Eye-mark recorder and motion tracking system were used to tracking eye movement and head movement, respectively. Nonverbal response animation with eye contact was introduced in the interaction system. In identifying the head gesture, we adopted a modified dynamic programming matching method and fuzzy inference.     

附加质量的强迫振动测试系统总体框架

介绍了附加质量的强迫振动机构实验系统的总体方案设计.振荡机构能使实验模型产生所谓的"纯横荡"运动和"纯摇首"运动.测力系统和数据处理系统将测得的流体动力进行处理,最终求得附加质量及旋转导数.该机构同平面运动机构相比,结构紧凑,可靠性好,具有突出的优点.