A particle filter based face tracking algorithm under complex environment is provide.
提出一种基于粒子滤波的复杂环境下人脸检测与跟踪算法。
Incorporating color distribution and spatial layout, this paper proposes a sequential Monte Carlo filter tracking face algorithm using color and spatial information in HSV color space.
结合图像的色彩分布和空间布局，提出了一种基于HSV色彩和空间信息的序列蒙特卡罗滤波人脸跟踪算法。
To overcome the limitation of the traditional tracking algorithm, we use particle filter for face tracking.
为了克服传统跟踪算法的局限性，采用粒子滤波器进行人脸跟踪。
A automatic face detection and tracking algorithm is presented, which is of very low computational complexity and is rather robust to image content.
给出了一种运算量低、鲁棒性好的人脸自动识别和跟踪算法。
A new real-time eye tracking algorithm is presented that works well under variable and realistic lighting conditions and various face orientations.
提出了一种实时的眼睛跟踪算法，它能在各种照明条件和各种脸部姿势条件下很好地工作。
Secondly, we use the mean shift algorithm to track the faces. We realize automatic face tracking of image sequence eventually.
其次，在人脸跟踪方面采用基于均值平移的算法进行跟踪，最终实现图像序列的自动人脸跟踪。
Face tracking using KLT algorithm can reduce the impact caused by the tilt of the head, only the first detection of the human eye, after all detected feature points, computing speed.
人脸跟踪使用KLT算法。能够减少人头倾斜造成的影响，只有第一次检测人眼，以后都是检测特征点，运算速度快。- Use vision。
We realize an algorithm based on minimum features for rapid face modeling from video, by tracking feature points, calibrating exterior parameter, estimating 3D location of feature points.
通过跟踪视频中的特征点，标定相机外参，进而估计特征点的3D位置，实现了基于一段视频中小特征点集的人脸建模算法。
We realize an algorithm based on minimum features for rapid face modeling from video, by tracking feature points, calibrating exterior parameter, estimating 3D location of feature points.
通过跟踪视频中的特征点，标定相机外参，进而估计特征点的3D位置，实现了基于一段视频中小特征点集的人脸建模算法。
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