非穿戴指势手指三维定位

Three Dimension Localization of Non-wearable Pointing Arm

根据小波变换在时域和空域均具有优异的局部化特征,基于背景差分,利用小波多尺度特性进行小波多尺度变换,提取视频运动对象并抑制阴影.根据手指在图像中的空间位置关系,基于阈值分割与色彩信息融合方法,提取手指区域.融合手指指尖特征点、指势手指的手臂中心轴线及其外极线的多几何约束的立体匹配策略,采用求解反对应方法,确保手指特征匹配的正确性.实验验证了文中所提方法能有效定位指势手指的三维信息.

As the wavelet transform has outstanding local characteristics both in temporal and spatial domains, moving objects are extracted based on background subtraction using wavelet multi-scale transform. According to the relative spatial position of pointing arm finger in a 2D image, a method for the extraction of pointing arm region is developed based on fusion of threshold segmentation and color information. In processing the correspondence problem of finger tip pointing, a stereo matching technique is used based on geometric constraints among the pointing arm finger tip, central axis of the pointing arm, and the corresponding epipolar line. Reverse correspondence is adopted to ensure validity of the processed correspondence. Experimental results show that the described algorithm is robust and 3D information of the pointing arm can be determined efficiently.