はじめまして、リサーチャーの中村と申します。 私は本年4月に新卒としてモルフォに入社しました。
今年の新人研修（OJT）において、私達のチームは2ヶ月にわたってVieurekaカメラというエッジデバイスを用いたアプリケーション開発を行いました。 私達のチームでは、Vieurekaカメラ上で得られた顔認識結果をPCやクラウド上で共有することで遠隔でも玄関の状況や来訪者を知ることが出来るスマートインターホンを開発しました。 アプリケーションの構造を下の図に示します。
そこで本記事では、顔認証機能付きスマートインターホンの要素技術であるリアルタイム顔検出について紹介します。 特に、ここではアルゴリズムの詳細に踏み込むのではなく、エッジデバイス上での実行速度と検出精度のバランスに着目していきます。
続きを読むHi everyone! I am Chamin, a boffin researcher from Morpho's CTO Office. As members of Morpho's main R&D division, we regularly attend conferences on Computer Vision and Machine Learning. This helps us to keep in touch with the state of the art, and also gain insights to new research topics. So, one (sometimes a few) of us would attend a conference, summarize the interesting stuff, and share them with the colleagues.
ICIP 2020 - The 2020 International Conference on Computational Photography - was supposed to be held in St. Louis, USA. However, due to COVID-19 concerns, it was conducted as an online event. In this post, I will summarize a few interesting papers from this conference.
In Computational Photography, we investigate digital processing techniques that can replace or supplement optical processes that are used in taking pictures. Admittedly, that sounds more like rocket science than photography, so let me give you an example. Suppose you want to have a good bokeh effect in photos that you take with your smartphone. If you rely solely on optics to do this, you will end up with a thick phone that has a HUGE lens (expensive, hard to carry and maintain, etc.). Instead, the present-day smartphones use a couple of tiny cameras, other sensors, and computational photography techniques to provide a similar effect. Figure 0 is an example for such a photo, taken with an iPhone 11 Pro.
OK, so much for the introduction. The following are four of about a dozen ICCP 2020 papers that I summarized and shared with my colleagues. I hope you'll find them interesting.
続きを読む