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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>IPCV Research Group</title>
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<body>
<header>
<nav>
<ul class="navBar">
<li class="navBar"><a href="index.html">Home</a></li>
<li class="navBar"><a href="page1.html">Comparing Techniques</a></li>
<li class="navBar"><a href="page2.html">FusionLoc</a></li>
<li class="navBar"><a href="page3.html">Sensor Fusion & IMU</a></li>
</ul>
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</header>
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<h1>Indoor Positioning & Computer Vision (IPCV) Research Group</h1>
<div style="text-align: center;">
<img src="images/logo_2.PNG" width="358">
</div>
<a id="About_Us">
<h2>About Us</h2>
<div class="container-1400">
<div class="paragraph">
<p> We are a research group from the University of Toronto, Mississauga Mathematical and Computational Sciences department. Our current research interests lie in indoor and outdoor positioning, localization and navigation that can be applied to mobile robots, drones, and AR/VR systems. In the past we have compared and evaluated multiple current indoor positioning techniques and further developed and improved specific methods, including computer vision and AI/ML techniques. We are also currently researching and exploring sensor fusion and IMU-based positioning. </p>
<p><strong>Research Interests:</strong></p>
<ul>
<li>Sensor Fusion and filtering</li>
<li>Deep Learning for Computer Vision</li>
<li>Inertial Navigation Systems</li>
<li>Simultaneous Localization and Mapping</li>
<li>Object and Camera Pose Estimation</li>
<li>Perception for Autonomous Vehicles</li>
</ul>
<a href="https://github.com/indoorpositioning">GitHub Page</a>
</div>
</div>
</a>
<br>
<a id="Team">
<h2>Team</h2>
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<table>
<tr>
<td colspan="4"><h3>Current Members</h3></td>
</tr>
<tr>
<td><img src="images/ali.jpg" width="200" height="200"></td>
<td>
<strong>Ali Raza</strong> <br>
Undergraduate Researcher <br>
Computer Science Specialist <br>
alisyed[dot]raza[at]mail.utoronto.ca <br>
<a href="https://www.linkedin.com/in/ali-raza-6410ba161/"><img src="images/icons8-linkedin-48.png" width="30" height="30"></a>
</td>
<td><img src="images/shahmir.jpg" width="200" height="200"></td>
<td>
<strong>Shahmir Akhter</strong> <br>
Undergraduate Researcher <br>
Computer Science & CCIT Double Major <br>
shahmir[dot]akhter[at]mail.utoronto.ca <br>
<a href="https://www.linkedin.com/in/shahmir-akhter-80b553194/"><img src="images/icons8-linkedin-48.png" width="30" height="30"></a>
</td>
</tr>
<tr>
<td><img src="images/michael.jpeg" width="200" height="200"></td>
<td>
<strong>Michael Liut</strong> <br>
Principal Investigator <br>
Assistant Professor, Teaching Stream <br>
Computer Science <br>
michael[dot]liut[at]utoronto.ca <br>
<a href="https://www.linkedin.com/in/mliut/"><img src="images/icons8-linkedin-48.png" width="30" height="30"></a>
<a href="https://www.michaelliut.ca/"><img src="images/icons8-website-48.png" width="30" height="30"></a>
</td>
<td></td>
<td></td>
</tr>
<tr>
<td colspan="4"><h3>Past Members</h3></td>
</tr>
<tr>
<td><img src="images/lazar.jpg" width="200" height="200"></td>
<td>
<strong>Lazar Lolic</strong> <br>
Undergraduate Researcher <br>
Computer Science Specialist <br>
lazar[dot]lolic[at]utoronto.ca <br>
<a href="https://www.linkedin.com/in/lazar-lolic/"><img src="images/icons8-linkedin-48.png" width="30" height="30"></a>
</td>
<td><img src="images/alfonso.jpg" width="200" height="200"></td>
<td>
<strong>Alfonso Dela Cruz</strong> <br>
Undergraduate Researcher <br>
Computer Science Specialist <br>
alfonso[dot]delacruz[at]mail.utoronto.ca <br>
<a href="https://www.linkedin.com/in/alfonso-dela-cruz-751710199/"><img src="images/icons8-linkedin-48.png" width="30" height="30"></a>
</td>
</tr>
</table>
</div>
</a>
<br>
<a id="Publications">
<div class="container-1400">
<h2>Publications</h2>
<div class="publication">
<p><a href="https://ieeexplore.ieee.org/document/9662632">Comparing and Evaluating Indoor Positioning Techniques.</a></p>
<p>Ali Raza, Lazar Lolic, Shahmir Akhter, Michael Liut.</p>
<p>2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN 2021), Lloret de Mar, Spain, November 2021.</p>
<p> ---- </p>
<p><a href="https://arxiv.org/abs/2203.00080">Deep Camera Pose Regression Using Pseudo-LiDAR</a> (Pre-print)</p>
<p>Ali Raza, Lazar Lolic, Shahmir Akhter, Alfonso Dela Cruz, Michael Liut.</p>
</div>
</div>
</a>
<br>
<a id="Funding">
<h2>Funding</h2>
<div class="container-1400">
<div class="paragraph">
<p> This research was supported by the National Sciences and Research Council of Canada (NSERC) grant USRA/567510-2021, the University of Toronto Mississauga's (UTM) Office of the Vice-Principal Research (OVPR) Fund, Dean's Office Research Opportunity Project (ROP) Fund, and UTM's Department of Mathematical and Computational Sciences </p>
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