Kim Kwangtaek, Kim Joongrock, Choi Jaesung, Kim Junghyun, Lee Sangyoun
Department of Electrical and Electronic Engineering, Institute of BioMed-IT, Energy-IT and Smart-IT Technology (Best), Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Korea.
Future IT Convergence Lab, LGE Advanced Research Institute, 38 Baumoe-ro, Seocho-gu, Seoul 137-724, Korea.
Sensors (Basel). 2015 Jan 8;15(1):1022-46. doi: 10.3390/s150101022.
Vision-based hand gesture interactions are natural and intuitive when interacting with computers, since we naturally exploit gestures to communicate with other people. However, it is agreed that users suffer from discomfort and fatigue when using gesture-controlled interfaces, due to the lack of physical feedback. To solve the problem, we propose a novel complete solution of a hand gesture control system employing immersive tactile feedback to the user's hand. For this goal, we first developed a fast and accurate hand-tracking algorithm with a Kinect sensor using the proposed MLBP (modified local binary pattern) that can efficiently analyze 3D shapes in depth images. The superiority of our tracking method was verified in terms of tracking accuracy and speed by comparing with existing methods, Natural Interaction Technology for End-user (NITE), 3D Hand Tracker and CamShift. As the second step, a new tactile feedback technology with a piezoelectric actuator has been developed and integrated into the developed hand tracking algorithm, including the DTW (dynamic time warping) gesture recognition algorithm for a complete solution of an immersive gesture control system. The quantitative and qualitative evaluations of the integrated system were conducted with human subjects, and the results demonstrate that our gesture control with tactile feedback is a promising technology compared to a vision-based gesture control system that has typically no feedback for the user's gesture inputs. Our study provides researchers and designers with informative guidelines to develop more natural gesture control systems or immersive user interfaces with haptic feedback.
基于视觉的手部手势交互在与计算机交互时自然且直观,因为我们在与他人交流时会自然地运用手势。然而,由于缺乏物理反馈,人们一致认为用户在使用手势控制界面时会感到不适和疲劳。为了解决这个问题,我们提出了一种新颖的完整解决方案,即采用沉浸式触觉反馈到用户手部的手势控制系统。为了实现这一目标,我们首先使用所提出的MLBP(改进的局部二值模式)开发了一种利用Kinect传感器的快速准确的手部跟踪算法,该算法可以有效地分析深度图像中的3D形状。通过与现有方法、最终用户自然交互技术(NITE)、3D手部跟踪器和CamShift进行比较,从跟踪精度和速度方面验证了我们跟踪方法的优越性。作为第二步,开发了一种带有压电致动器的新型触觉反馈技术,并将其集成到所开发的手部跟踪算法中,包括用于沉浸式手势控制系统完整解决方案的DTW(动态时间规整)手势识别算法。对该集成系统进行了人体受试者的定量和定性评估,结果表明,与通常对用户手势输入没有反馈的基于视觉的手势控制系统相比,我们的带有触觉反馈的手势控制是一项有前途的技术。我们的研究为研究人员和设计师提供了信息丰富的指导方针,以开发更自然的手势控制系统或带有触觉反馈的沉浸式用户界面。