A vision-based detection and tracking algorithm for a child monitoring robot

Accidents have been found to be one of the leading causes of both fatal and non-fatal injuries to children. Though some accidents that occur are often unavoidable, more often than not these injuries can be prevented by giving the child proper attention. The researchers intend to address certain gaps...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Jose, John Anthony C., Basco, Justine Veronica, Jolo, Jomar Kenneth, Yambao, Patrick Kenneth, Cabatuan, Melvin K., Bandala, Argel A., Maningo, Jose Martin Z., Dadios, Elmer P.
التنسيق: text
منشور في: Animo Repository 2019
الموضوعات:
الوصول للمادة أونلاين:https://animorepository.dlsu.edu.ph/faculty_research/1712
https://animorepository.dlsu.edu.ph/context/faculty_research/article/2711/type/native/viewcontent
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المؤسسة: De La Salle University
الوصف
الملخص:Accidents have been found to be one of the leading causes of both fatal and non-fatal injuries to children. Though some accidents that occur are often unavoidable, more often than not these injuries can be prevented by giving the child proper attention. The researchers intend to address certain gaps in stationary monitoring solutions by adding abilities such as an insured way of continuously monitoring the test subject and a real time notification feature to a mobile spherical robot. This research presents the software division of a technological solution to child monitoring by developing a computer vision algorithm for following and monitoring children indoors utilizing an RGB-D camera. This algorithm will work hand in hand with a hardware design of a spherical robot that utilizes microcontrollers, RFID technology and GSM system. An Android application will also be created to provide the users the means of manually overriding the spherical robot, color calibration and location indicator as a part of the robot's notification system. The detection and tracking ability of the algorithm is tested by using objects with varying characteristics. The autonomous navigation testing of the robot is performed at two controlled test setups: living room and child's playroom. © 2019 IEEE.