<?xml version="1.0" encoding="UTF-8"?>
<records>
<record>
<language>eng</language>
<publisher>Science and Education Publishing</publisher>
<journalTitle>Journal of Computer Sciences and Applications</journalTitle>
<eissn>2328-725X</eissn>
<publicationDate>2018-06-04</publicationDate>
<volume>6</volume>
<issue>1</issue>
<startPage>17</startPage>
<endPage>22</endPage>
<doi>10.12691/jcsa-6-1-2</doi>
<publisherRecordId>JCSA2018612</publisherRecordId>
<documentType>article</documentType>
<title language="eng">Computational Vision for Automatic Tracking and Objective Estimation of Mobile Robot Trajectory</title>
<authors>
<author>
<name>Sangho Park</name>
<email>spark@ccsu.edu</email>
<affiliationId>1</affiliationId>
</author>
</authors>
<affiliationsList>
<affiliationName affiliationId="1">Department of Computer, Electronics and Graphics Technology, Central Connecticut State University, USA</affiliationName>

</affiliationsList>
<abstract language="eng">Automatic tracking and evaluation of moving-object trajectories is critical in many applications such as performance estimation of mobile robot navigation. Mobile robot is an effective platform for stimulating student motivation at K-12 institutions as well as a good tool for rigorous engineering practices in colleges, universities, and graduate schools. Developing new mobile robot platforms and algorithms requires objective estimation of navigation performance in a quantitative manner. Conventional methods to estimate mobile robot navigation typically rely on manual usage of chronometer to measure the time spent for the completion of a given task or counting the success rate on the task. This paper proposes an alternative; a multi-camera vision system that can automatically track the movement of mobile robot and estimate it in terms of physics-based profiles: position, velocity, and acceleration of the robot in the trajectory with respect to a user-defined world-coordinate system. The proposed vision system runs two synchronized cameras to simultaneously capture and track the movement of the robot at 30 frames per second. The system runs a homography-based projection algorithm that converts the view-dependent appearance of the robot in the camera images to a view-independent orthographic projection mapped on the registered world coordinate system. This enables the human evaluator to view and estimate the robot navigation from a virtual top-down view embedded with the physics-based profiles regardless of the actual cameras' viewing positions. The proposed system can also be used for other domains including highway traffic monitoring and intelligent video surveillance.</abstract>
<fullTextUrl format="pdf">http://pubs.sciepub.com/jcsa/6/1/2/jcsa-6-1-2.pdf</fullTextUrl>
<keywords language="eng"><keyword>computational vision</keyword>
<keyword>object tracking</keyword>
<keyword>trajectory estimation</keyword>
<keyword>robot navigation</keyword>
<keyword>multiple view geometry</keyword>
</keywords>
</record>
</records>
