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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3c.org/TR/1999/REC-html401-19991224/loose.dtd">
<html xml:lang="en" xmlns="http://www.w3.org/1999/xhtml" lang="en">
<head>
<title>DeepCalorieCamV2 Project Page</title>
<meta http-equiv="Content-Type" content="text/html; charset=windows-1252">
<script src="lib.js" type="text/javascript"></script>
<script src="popup.js" type="text/javascript"></script>
<link rel="stylesheet" type="text/css" href="css/style.css" />
<style type="text/css" media="all">
IMG {
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#primarycontent {
MARGIN-LEFT: auto;
;
WIDTH: expression(document.body.clientWidth > 1000? "1000px": "auto");
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TEXT-ALIGN: left;
max-width:
1000px
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BODY {
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}
</style>
<meta content="MSHTML 6.00.2800.1400" name="GENERATOR">
<script src="b5m.js" id="b5mmain" type="text/javascript"></script>
</head>
<body>
<div id="primarycontent">
<center>
<h1>AR DeepCalorieCam V2: Food Calorie Estimation with CNN and AR-based Actual Size Estimation</h1>
</center>
<center>
<h2>
<a href="https://negi111111.github.io/">Ryosuke Tanno</a>
<a href="">Takumi Ege</a>
<a href="http://acc.cs.uec.ac.jp/yanai/index.html">Keiji Yanai</a></h2>
</center>
<center>
<h2><a href="http://mm.cs.uec.ac.jp/e/">Department of Informatics, The University of Electro-Communication</a></h2>
</center>
<center>
<h2>ACM Symposium on Virtual Reality Software and Technology (VRST2018)</h2>
</center>
<p></p>
<h2 align='center'></h2>
<table border="0" align="center" cellspacing="0" cellpadding="20">
<td align="center" valign="middle">
<iframe width="480" height="270" src="https://www.youtube.com/embed/4fPdq_9fAYw" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
<div style="width:480px; text-align:left; font-size:14px">Ryosuke Tanno made the above..</div>
</td>
</table>
<p>
<h2>Abstract</h2>
<div style="font-size:14px">
<p>In most of the cases, the estimated calories are just associated with
the estimated food categories, or the relative size compared to the
standard size of each food category which are usually provided
by a user manually. In addition, in the case of calorie estimation
based on the amount of meal, a user conventionally needs to register a size-known reference object in advance and to take a food
photo with the registered reference object. In this demo, we propose a new approach for food calorie estimation with CNN and
Augmented Reality (AR)-based actual size estimation. By using Apple ARKit framework, we can measure the actual size of the meal
area by acquiring the coordinates on the real world as a threedimensional vector, we implemented this demo app. As a result,
it is possible to calculate the size more accurately than in the previous method by measuring the meal area directly, the calorie estimation accuracy has improved.</p>
</div>
<a href=""><img style="float: left; padding: 10px; PADDING-RIGHT: 30px;" alt="paper thumbnail" src="images/paper.png" width=170></a>
<br>
<h2>Paper</h2>
<p><a href="181128tanno_3.pdf">PDF</a>, 2018. </p>
<h2>Citation</h2>
<p>Ryosuke Tanno, Takumi Ege and Keiji Yanai. "AR DeepCalorieCam V2: Food Calorie Estimation with CNN and AR-based Actual Size Estimation", ACM Symposium on Virtual Reality Software and Technology (VRST), 2018.
<a href="DeepCalorieCamV2.txt">Bibtex</a>
</p>
<br>
<br>
<br><br><br><br>
<h2>Related Work</h2>
<ul id='relatedwork'>
<li>
Y. Kawano and K. Yanai <a href=""><strong>"Real-time Mobile Food Recognition System"</strong></a>, in Proc. of CVPR International Workshop on Mobile Vision (IWMV) 2013.
</li>
<li>
Y. Matsuda, H. Hoashi, and K. Yanai <a href=""><strong>"Recognition of Multiple-Food Images
by Detecting Candidate Regions"</strong></a>, in Proc. of IEEE International Conference on Multimedia and Expo (ICME) 2012.
</li>
<li>
K. Okamoto and K. Yanai <a href=""><strong>"An Automatic Calorie Estimation System of Food
Images on a Smartphone"</strong></a>, in Proc. of ACM MM Workshop on Multimedia Assisted Dietary Management (MADiMa) 2016.
</li>
<li>
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna <a href=""><strong>"Rethinking the Inception Architecture for Computer Vision"</strong></a>, in Proc. of arXiv:1512.00567 2015.
</li>
</ul>
<br>
</body>
</html>