Universal Range Data Acquisition for Educational Laboratories Using Microsoft Kinect

被引:0
|
作者
Zhang, Mingshao [1 ]
Zhang, Zhou [1 ]
Esche, Sven K. [1 ]
机构
[1] Stevens Inst Technol, Hoboken, NJ 07030 USA
关键词
RECOGNITION; SENSOR; SYSTEM;
D O I
暂无
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Many experiments conducted in engineering and science laboratories involve the acquisition of range data such as linear or angular position, velocity and acceleration, distance, displacement, etc. This type of data acquisition (DAQ) is accomplished by sensors, DAQ measurement hardware and a computer with programmable software. This approach to DAQ can cause a series of problems hampering its implementation in educational laboratories. For instance, many sophisticated sensors (e.g. laser scanners) and the DAQ hardware are expensive, often the sensors and DAQ hardware and peripheral devices require modifications for being reused in other applications and most experimental setups need to be calibrated before each measurement. These facts tend to increase the up-front cost of the experimental devices and add to the required operating time. Therefore, low-cost range sensors such as the Microsoft Kinect could become a cost-effective and versatile DAQ alternative. Furthermore, Kinect has acceptable performance regarding sensitivity, accuracy, stability and reliability as well as low error rates, cost and power consumption. In this paper, the concept of using Kinect as a substitute range DAQ is presented and a prototype implementation targeting educational experiments is introduced. This system has several attractive features besides low cost, including that it (in conjunction with appropriate software) can be trained to recognize and remember multiple objects, is able to track these objects simultaneously, does neither need to be customized nor modified for measurements in different applications, and uses all the surface data (as opposed to single-point tracking) to calculate the positions and deformations of objects, which results in low drifting error. Taking advantage of these desirable characteristics, Kinect is believed to have the potential for becoming an economical and versatile tool for adoption in a wide variety of educational laboratories.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] Arabic Sign Language Recognition Using the Microsoft Kinect
    Aliyu, S.
    Mohandes, M.
    Deriche, M.
    Badran, S.
    [J]. 2016 13TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS & DEVICES (SSD), 2016, : 301 - 306
  • [22] Prescription Software for Recovery and Rehabilitation Using Microsoft Kinect
    Simmons, Stephen
    McCrindle, Rachel
    Sperrin, Malcolm
    Smith, Andy
    [J]. PROCEEDINGS OF THE 2013 7TH INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING TECHNOLOGIES FOR HEALTHCARE AND WORKSHOPS (PERVASIVEHEALTH 2013), 2013, : 323 - 326
  • [23] Localization system using microsoft kinect for indoor structures
    Tamura, Yuichi
    Takabatake, Yuki
    Kashima, Naoya
    Umetani, Tomohiro
    [J]. Plasma and Fusion Research, 2012, 7 (SPL.ISS.1)
  • [24] Use of the Microsoft Kinect for applications of patient surface data to radiotherapy
    Guillet, Dominique
    Syme, Alasdair
    DeBlois, Francois
    [J]. MEDICAL PHYSICS, 2014, 41 (08) : 3 - 3
  • [25] Development of a Compact Radiographic Simulator Using Microsoft Kinect
    Ono, M.
    Kozono, K.
    Aoki, M.
    Mizoguchi, A.
    Kamikawa, Y.
    Umezu, Y.
    Arimura, H.
    Toyofuku, F.
    [J]. MEDICAL PHYSICS, 2012, 39 (06) : 3646 - 3646
  • [26] A Platform for Mechanical Assembly Education Using the Microsoft Kinect
    Chang, Yizhe
    Aziz, El-Sayed
    Zhang, Zhou
    Zhang, Mingshao
    Esche, Sven
    Chassapis, Constantin
    [J]. ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2014, VOL 5, 2015,
  • [27] Metrology and Visualization of Potholes using the Microsoft Kinect Sensor
    Moazzam, I.
    Kamal, K.
    Mathavan, S.
    Usman, S.
    Rahman, M.
    [J]. 2013 16TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS - (ITSC), 2013, : 1284 - 1291
  • [28] A musculoskeletal model driven by dual Microsoft Kinect Sensor data
    Skals, Sebastian
    Rasmussen, Kasper P.
    Bendtsen, Kaare M.
    Yang, Jian
    Andersen, Michael S.
    [J]. MULTIBODY SYSTEM DYNAMICS, 2017, 41 (04) : 297 - 316
  • [29] Validity and sensitivity of the longitudinal asymmetry index to detect gait asymmetry using Microsoft Kinect data
    Auvinet, E.
    Multon, F.
    Manning, V.
    Meunier, J.
    Cobb, J. P.
    [J]. GAIT & POSTURE, 2017, 51 : 162 - 168
  • [30] Using Data From the Microsoft Kinect 2 to Quantify Upper Limb Behavior: A Feasibility Study
    Dehbandi, Behdad
    Barachant, Alexandre
    Harary, David
    Long, John Davis
    Tsagaris, K. Zoe
    Bumanlag, Silverio Joseph
    He, Victor
    Putrino, David
    [J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2017, 21 (05) : 1386 - 1392