Kinect-based Universal Range Sensor and its Application in Educational Laboratories
Keywords:Engineering Education, Laboratory Development, Microsoft Kinect, Data Acquisition, Object Recognition, Motion Tracking
Traditional data acquisition (DAQ) systems for obtaining 3-D range information consist of sensors, DAQ measurement hardware and a processor with software. This kind of DAQ system is adapted and calibrated for various applications, thus imposing significant up-front costs that hamper its broad usage in educational laboratories. The low-cost Microsoft Kinect has become a promising alternative solution that has already been widely adopted by consumers and offers a wide variety of opportunities for being used in many other areas. The Kinect’s cameras are capable of producing high quality synchronized video that consists of both color and depth data. This enables the Kinect to compete with other sophisticated 3-D sensor DAQ systems in terms of performance criteria such as accuracy, stability, reliability and error rates. One of the most noticeable Kinect-based applications is the skeleton-based tracking of humans, which is made possible by its built-in human skeleton recognition functions. Other common usages of the Kinect are 3-D surface/scene reconstruction and object classification/recognition. However, Kinect-based developments that focus on the tracking of arbitrary objects have rarely been reported, mainly due to a lack of mature algorithms. In the first part of this paper, a three-stage approach for capturing general motions of objects will be introduced. This approach consists of point cloud pre-processing with a focus on computational efficiency, object tracking employing recognition and post-processing including motion analysis. This approach can be tailored to special cases, namely the algorithms focus more on computation efficiency when the objects of interest have simple shapes or colors, and they focus more on reliability for objects with complex geometries or textures. The second part of this paper describes the integration of the proposed DAQ system into a multi-player game-based laboratory environment. In this implementation, a physical experiment is triggered by the game avatars and the experimental data acquired by the Kinect and analyzed by the proposed algorithms are then fed back into the game environment and used to animate the experimental device.
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