预测点 meaning in Chinese
future position
predicted position
Examples
- Finally , the prediction it gives is an estimated range , rather than a specific point estimate , and more accurately reflects forecasting errors
此外，这个模型给出的是一个预测范围而不是一个特定的预测点，因而能更准确的反映预测误差。 - But during predicting , both cbp and icbp neglected structural changes and correlation in time series themselves . they did not consider how the distance from the observation point to the current predicting point would influence the resulting performance
但在预测时cbp和icbp都忽视了时间序列本身的结构性变化及相关性，即没有考虑观察点与预测点的远近对预测性能的影响。 - The results show that the wayside noise increases 8db - 12db , if the train ' s velocity increase two times ; and increases 3 db , if the number of axles increase tow times ; and decreases 3db , if the distance far away from the track increase tow times damping loss factor increases , the wayside noise decreases ; coupling loss factor increase , the wayside noise increase
预测结果表明：列车通过时，在其他条件不变的情况下，列车速度增加一倍，轮轨辐射噪声大约增加8db 12db ；列车轴数增加一倍，轮轨辐射噪声大约增加3db ；预测点距轨道距离增加一倍，轮轨辐射噪声大约降低3db 。 - Block motion estimation using full search is computationally intensive , many fast algorithm have proposed to reduce the computation at the expense of less accuracy of motion estimation . in this paper , we present a new fast and efficient search algorithm for block motion estimation . the proposed algorithm is based on the ideas of predicted starting search point , subsampled block distortion measure , center - biased distribution of motion vector , multiple - candidate diamond search . from the experimental results , the proposed algorithm is superior to many other well - known fast algorithms in both quality performance and computational complexity
算法采用多步搜索方法，利用相邻块之间的运动相关性，选择反映当前块运动趋势的预测点作为初始搜索点用子采样块匹配失真度量来减少计算量利用运动矢量的中心倾向的分布特性，用多侯选点钻石形状搜索方法来提高运动估计的速度和准确性。 - Visual analysis of human motion has been receiving increasing attention from researchers in the fields of image processing and computer vision during the past few years . it has a lot of applications in virtual reality , smart surveillance system , advanced user interface , motion analysis and video compressing , etc . this paper focuses on the technology of human motion tracking based on video , first , we make a summarization of the domestic and overseas status of the research in this field . on the basis of this , we analyse the technical difficulties of human motion tracking . as most of the existing model - based methods of human motion tracking perform not so good in some situation as they need mannual intervention , and also the precision of tracking is not so satisfying during the research of tracking of walking people because of the self - occlusion of legs , this paper proposes an algorithm of automatic detection and tracking of legs of the walking people based on monocular image sequences , in which we analyse the features of walking people , track the five joints of lower limbs , get various parameters , and then re - construct the walking process . the main research achievement is as follows : 1 ) we propose an algorithm of markerless automatic extraction of leg skeleton . first we divide the video into continuous image sequences , after background subtraction , the satisfying human region could be extracted , then we get a single - connected region by converting the rgb image to binary image and median filtering . afterwards , the contour of lower limbs in the frame with a widest boundingbox is detected , using sobel operator , to find the ankle joint of leg behind according to the features and rules of walking , then , the joint of knee of leg behind , hip , ankle of leg in front , knee of leg in front could be got in turn . so , model of leg skeleton is constructed
首先将视频分解成许多连续的静态图像帧,经过背景去除,把感兴趣的人体区域提取出来,通过二值化,中值滤波等预处理方法得到只有人体的一个单连通区域,然后用sobel算子检测出boundingbox最宽帧中人体下半身的轮廓,根据运动规律及特征找到后腿踝关节点,结合从boundingbox最窄帧中所获取的腿长依次得到后腿膝关节,跨部关节,前腿踝关节,前腿膝关节四点,从而构建出腿部骨架模型。 2 )实现了人体步行腿部骨架的跟踪算法。在完成对腿部骨架模型的自动初始化之后,本文对跨关节、膝关节及踝关节分别采用运动建模、圆周相交定点算法、运动预测及预测点周围搜索rgb相似矩形块三种方法确定每一帧中其实际坐标,从而重构出腿部骨架的运动过程。