基于时空上下文的手势跟踪与识别

针对复杂背景下手势运动过程中出现的手势形态变化、遮挡、光照变化等问题,提出了一种基于时空上下文的手势跟踪与识别方法。使用机器学习方法离线训练手势样本分类器,实现对手势的检测和定位;利用时空上下文跟踪算法对动态手势进行跟踪,同时为了避免跟踪过程中出现的漂移、目标丢失等情况,使用手势检测算法对手势位置信息进行实时校准;根据手势运动轨迹对手势运动进行跟踪与识别。实验表明,提出的方法可以实现对手势运动快速、准确、连续识别,满足人机交互的要求。     

基于手势识别的工业机器人操作控制方法

针对目前操作工人与工业机器人之间的交互还是采用比较机械化的交互方式,设计使用Kinect传感器作为手势采集设备,并使用人的手势来对工业机器人进行控制的方法。首先,使用深度阈值法与手部骨骼点相结合的方法,从Kinect传感器获取的数据中准确地提取出手部图像。在提取过程中,操作员无需佩戴任何设备,对操作员所站位置没有要求,对背景环境也没要求。然后,用稀疏自编码网络与Softmax分类器结合的方法对手势图像进行识别,手势识别过程包含预训练和微调,预训练是用逐层贪婪训练法依次训练网络的每一层,微调是将整个神经网络看成一个整体微调整个网络的参数,手势识别的准确率达到99.846%。最后,在自主研发的工业机器人仿真平台上进行实验,在单手和双手手势下都取得了不错的效果,实验结果验证了手势控制工业机器人的可行性和可用性。     

一种基于改进DTW算法的动态手势识别方法

结合Kinect传感器提出了一种基于改进的DTW算法的动态手势识别方法。首先,通过SDK对Kinect传感器获得的深度信息进行分析,获得人体骨骼点3D位置,选取其中4个点作为手部运动特征;然后,用加权距离和全局路径限制的方法对传统的DTW算法进行改进;最后,用改进的DTW算法进行模板训练和实现动态手势的识别。实验表明：该方法能很好地实现动态手势的识别,实时性好,在背景干扰和光照方面有较强的鲁棒性,较传统的DTW算法在识别速度和识别正确率方面有所提高。     

A Framework for Recognizing the Simultaneous Aspects of American Sign Language

The major challenge that faces American Sign Language (ASL) recognition now is developing methods that will scale well with increasing vocabulary size. Unlike in spoken languages, phonemes can occur simultaneously in ASL. The number of possible combinations of phonemes is approximately 1.5×10⁹, which cannot be tackled by conventional hidden Markov model-based methods. Gesture recognition, which is less constrained than ASL recognition, suffers from the same problem. In this paper we present a novel framework to ASL recognition that aspires to being a solution to the scalability problems. It is based on breaking down the signs into their phonemes and modeling them with parallel hidden Markov models. These model the simultaneous aspects of ASL independently. Thus, they can be trained independently, and do not require consideration of the different combinations at training time. We show in experiments with a 22-sign-vocabulary how to apply this framework in practice. We also show that parallel hidden Markov models outperform conventional hidden Markov models.     

彩色图像中基于Hu矩的手势识别方法研究

手势识别是图像处理中一个主要研究方向,Hu矩由于其良好的不变性被广泛地应用在二值图像中进行图像识别.文中将传统的Hu矩引入到彩色图像中,经过大量的实验,得出了Hu矩在彩色图像中的特性,提出了基于Hu矩的图像旋转识别法,应用在彩色图像的手势识别中.     

Motion-sensor fusion-based gesture recognition and its VLSI architecture design for mobile devices

With the rapid proliferation of smartphones and tablets, various embedded sensors are incorporated into these platforms to enable multimodal human–computer interfaces. Gesture recognition, as an intuitive interaction approach, has been extensively explored in the mobile computing community. However, most gesture recognition implementations by now are all user-dependent and only rely on accelerometer. In order to achieve competitive accuracy, users are required to hold the devices in predefined manner during the operation. In this paper, a high-accuracy human gesture recognition system is proposed based on multiple motion sensor fusion. Furthermore, to reduce the energy overhead resulted from frequent sensor sampling and data processing, a high energy-efficient VLSI architecture implemented on a Xilinx Virtex-5 FPGA board is also proposed. Compared with the pure software implementation, approximately 45 times speed-up is achieved while operating at 20 MHz. The experiments show that the average accuracy for 10 gestures achieves 93.98% for user-independent case and 96.14% for user-dependent case when subjects hold the device randomly during completing the specified gestures. Although a few percent lower than the conventional best result, it still provides competitive accuracy acceptable for practical usage. Most importantly, the proposed system allows users to hold the device randomly during operating the predefined gestures, which substantially enhances the user experience.     

基于手势输入构造三维概念模型的研究进展

综述了国内外基于手势输入构造三维概念模型的最新研究进展,讨论分析了手势交互过程及其关键技术：手势设计、手势识别、手势交互的层次结构以及手势交互的三维实现．最后对今后的发展方向进行了展望．     

人手的运动学仿真及基于知识的控制方法

在对手部结构进行分析的基础上,给出了受约束的人手运动学模型,并重点研究了基于虚拟现实的人手运动仿真,建立了虚拟手遥控操作仿真实验系统,通过它进行单指、成组和整手控制,并实现了基于知识的抓取操作。     

马萨诸塞州诉环保署案对我国环境诉讼的借鉴

马萨诸塞州诉环保署一案,是美国近年来备受关注的一个新型的环境诉讼即气候变化诉讼的经典判决,也是联邦最高法院受理的第一个气候变化诉讼。美国联邦最高法院于2007年4月就马萨诸塞州等诉环保署案做出判决后,在美国国内产生广泛影响[1],对我国行政型环境公益诉讼在起诉资格审查、裁判请求权保障、裁判理由充分公开等方面均有可借鉴之处[2]。     

一种基于连续波雷达的手势识别方法

为了解决依靠光学传感器进行手势识别对外部环境依赖较大的问题,提出了一种基于连续波(Continuous Wave,CW)雷达的手势识别方法,并建立了4种手势动作的回波数据库.首先,对CW雷达回波进行短时傅里叶变换(Short-Time Fourier Transform,STFT)获取手势动作的时频谱;然后,通过设立阈值将时频谱中的背景杂波去除;接下来,对处理后的时频谱提取方向梯度直方图(Histogram of Oriented Gradient,HOG)特征;最后,采用支持向量机(Support Vector Machine,SVM)作为分类器,以HOG特征作为输入进行手势识别.实验结果表明,所提方法在普通室内环境下的识别精度超过95％,能够对典型的手势动作进行有效识别.