TY -的A2 -门,马可AU -马哈茂德,哈桑盟——哈桑。Kamrul盟——Abdullah-Al-Tariq盟——Kabir。Hasanul盟——Mottalib m . a . PY - 2018 DA - 2018/11/19 TI -识别的象征性姿态利用深度信息SP - 1069823六世- 2018 AB -象征性姿态是手的姿势与一些约定俗成的含义。他们是静态手势,一个可以执行非常复杂的环境中包含旋转和尺度变化不使用的声音。可能产生的手势在不同光照条件下或阻塞背景场景。任何手势识别系统应该找到足够的区别的特性,比如hand-finger上下文信息。然而,在现有的方法中,手的手指代表的手指形状的深度信息是用于区别的特征的提取能力有限的手指。然而,如果我们考虑手指弯曲(即信息。一根手指,手掌重叠),提取深度地图,并使用它们作为地方特色、静态手势有轻微的不同可以成为区分。我们的工作证实了这个想法,我们生成的深度轮廓变化与实现更有识别力的要点。反过来,这种方法提高了识别精度达到96.84%。我们应用尺度不变特征变换(筛选)算法生成的深度轮廓描述符作为输出作为输入,并生成健壮的特性。 These features (after converting into unified dimensional feature vectors) are fed into a multiclass Support Vector Machine (SVM) classifier to measure the accuracy. We have tested our results with a standard dataset containing 10 symbolic gesture representing 10 numeric symbols (0-9). After that we have verified and compared our results among depth images, binary images, and images consisting of the hand-finger edge information generated from the same dataset. Our results show higher accuracy while applying SIFT features on depth images. Recognizing numeric symbols accurately performed through hand gestures has a huge impact on different Human-Computer Interaction (HCI) applications including augmented reality, virtual reality, and other fields. SN - 1687-5893 UR - https://doi.org/10.1155/2018/1069823 DO - 10.1155/2018/1069823 JF - Advances in Human-Computer Interaction PB - Hindawi KW - ER -