中文摘要：

基于彩色图像中红、绿、蓝3分量强度在阴影区域存在差异,根据小波变换在时域和空域均具有优异的局部化特征,结合背景差分,进行小波多尺度变换,提取视频指势对象,所提方法不需场景学习与训练、手工校正及先验假设等信息,可克服动态场景变化、阴影、噪声干扰等影响,具有强的鲁棒性.基于人类生物结构特征,采用不易遮挡和不受人脸朝向、姿态、光照变化等影响的头顶特征代替人眼特征,保证了人机交互活动的自由性和自然性,且提高了人机交互的时效性.融合手指尖特征和手臂中心轴线及其外极线的多几何约束策略,采用求解反对应方法,确保手指特征匹配对应的正确性.通过实验验证,证实了上述方法有效、可行,可应用于实时、非穿戴的自然指势视觉3维人机交互中.

英文摘要：

Based on the differences between the color intensities of R, G and B components on a color image in shadow regions, we develop a novel approach to the pointing object segmentation across a clutter background. Because the wavelet transformation is with outstanding local characteristics both in temporal and spatial fields, we suggest extracting the video pointing objects based on the combination of background subtraction with the wavelet multi-scale transformation. The proposed algorithm does not require the information which is necessary for existing methods in literature, such as scene learning and training, manual calibration and a priori hypothesis. It is also robust to dynamic scene variation, shadow and noise disturbance. Based on the biological structure characteristics, we employ the position of the human head-top instead of that of the human eyes in the pointing object segmentation. This is because that the human head-top is not easily occluded by other parts of the body, and is free from the effects of the facial orientation, posture and illumination variation. This provides the flexibility and casualness for the human-computer interaction（HCI）, and ensures a high speed for the interaction. For the correct matching of finger tip characteristics, we present a stereo matching strategy based on the geometric constraints among the pointing arm finger tip, the central axis of the pointing arm and the corresponding epipolar line. A reverse matching criterion is employed to ensure the validity of the processed matching. Experiment results indicate that the developed approach is efficient for the recognition of the flexible and casual nonwearable pointing in the human-comouter interaction.