This thesis is focused on the activity recognition and object localization, which are two important research topics in AmI.
本文的研究主要针对环境智能中的两个研究重点:行为识别和目标定位。
A solution to address this problem is to apply color segmentation, which allows both image-to-image matching and object localization.
解决这个问题的办法是采用色彩分割,它既考虑图像对图像的匹配,又考虑对象定位。
So in this method, Firstly, using accumulating frame difference, we obtain the exact moving object localization which makes up the incompletely of the edge gotten by the frame difference.
因此,本文算法首先利用累积帧差,弥补了两帧帧差所得边界的不完整性,得到准确的运动对象的定位;
A localization and object tracking approach based on statistical operators and graph searching algorithms is presented for a team of robots localized with heterogeneous sensors.
以统计的操作员和曲线图搜索运算法则为基础的一个局限和物体追踪方式为与异种的感应器一起本土化的一队机械手被呈现。
To resolve the problem that the background pixels in an object model induce localization errors in object tracking, a fuzzy kernel histogram was presented for object tracking.
针对目标模型内的背景像素造成目标跟踪定位偏差的问题,提出了一种适合于目标跟踪的模糊核直方图。
An object recognition and localization algorithm based on local feature-turning Angle between neighbouring tangent vectors, is presented.
提出了基于切矢转角局部特征的目标识别与定位算法。
A realtime dynamic object recognition and localization method is presented for mobile robot using binocular vision.
提出了一种双目移动机器人实时动态目标识别与定位方法。
The precise edge detection in range image was the base of 3-D object recognition and localization.
深度图像边缘提取是物体识别和定位的基础。
The result of this paper is to propose a new method based on CCD star image for space-object accurate optical localization, and provide a new technology for space-object surveillance.
本文的研究成果在于提出了一套基于CCD星图的空间目标精确光学定位方法,为进行空间目标监测提供了新的技术途径。
This paper aims to explore a new method which is based on CCD star image for space-object accurate optical localization.
本论文旨在探索研究一套新的基于CCD星图的空间目标精确光学定位方法。
This paper aims to explore a new method which is based on CCD star image for space-object accurate optical localization.
本论文旨在探索研究一套新的基于CCD星图的空间目标精确光学定位方法。
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