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A novel approach for gesture control video games based on perceptual features: modelling, tracking and recognition

机译:一种基于感知功能的手势控制视频游戏的新颖方法:建模,跟踪和识别

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Gesture recognition has been an attractive research area for decades. Recently, the video game industry has become the major driving force for the development of advanced gesture control technologies. Conventional video games are controlled via physical devices. In contrast, the emerging trend is using camera-based human computer interface (HCI) to capture human gestures and control game playing directly.rnThis paper presents a novel approach for facilitating the development of gesture control-based video games. A time-of-flight (TOF) camera is adopted to provide both depth and greyscale image sequences. 3D perceptual gesture features are extracted and grouped into a generic gesture representation for target gesture recognition. The game control parameters are derived from the recognised gestures on the fly. This framework includes five key modules:rn1. perceptual feature extractionrn2. object tracking by perceptual groupingrn3. representation and modellingrn4. gesture recognitionrn5. game control parameter generation.rnA proof-of-concept dart game is implemented for demonstration and evaluation.
机译:几十年来,手势识别一直是有吸引力的研究领域。最近,视频游戏产业已成为高级手势控制技术发展的主要驱动力。常规的视频游戏是通过物理设备控制的。相比之下,新兴的趋势是使用基于相机的人机界面(HCI)来捕获人的手势并直接玩控制游戏。本文提出了一种新颖的方法来促进基于手势控制的视频游戏的开发。飞行时间(TOF)摄像机用于提供深度和灰度图像序列。提取3D感知手势特征并将其分组为用于目标手势识别的通用手势表示。游戏控制参数是从飞行中识别出的手势中得出的。该框架包括五个关键模块:rn1。感知特征提取通过感知分组跟踪对象3。表示和建模4。手势识别游戏控制参数生成。实现了概念验证飞镖游戏的演示和评估。

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