Robust Action Recognition using Depth-cameras for Rehabilitation and Bio-feedback Applications

随着廉价的消费级混合相机（深度+颜色）的出现，如Kinect设备 （已经是第二代，销量超过2000万台）和英特尔实感摄像头， 在几款笔记本电脑和平板电脑型号中标配，为消费者应用的全新领域打开了大门 以及家庭电脑和游戏的新时代。因为它们既可以获得几何信息， 颜色信息这种混合相机的好处之一是，它们可以，第一次， 实时无标记动作捕捉和动作识别。事实上，这些设备已经与内置的 基本的动作捕捉和动作识别不幸的是，虽然价格便宜，这些设备缺乏 医疗应用中所需的精度和鲁棒性，如康复软件。在这个项目中，我们将 与Jintronix合作开发新的准确和强大的动作识别和动作捕捉 基于消费级深度相机的方法。

With the emergence of inexpensive consumer level hybrid cameras (depth+color) such as the Kinect device (already at the second generation and that sold over 20 million units) and the Intel RealSense camera now standard in several laptop and tablet models opened the door to a whole new universe of consumer applications and a new era of home computing and gaming. Since they can acquire both geometric information as well as color information one of the benefits of such hybrid cameras is that they can, for the first time, facilitate real-time marker-less motion capture and action recognition. In fact these devices already are shipped with built in rudimentary motion capture and action recognition. Unfortunately, while inexpensive, these devices lack the accuracy and robustness required in medical applications such as rehabilitation software. In this project we will develop in partnership with Jintronix, new accurate as well as robust action recognition and motion capture methods based on consumer level depth-cameras.