technology:computer vision algorithms

Gauging urban change with Google Street View | Harvard Gazette
►http://news.harvard.edu/gazette/story/2017/07/gauging-urban-change-with-google-street-view

https://harvardgazette.files.wordpress.com/2017/07/streetchange_77_seaport_blvd_boston_ma_6052.jpg

Nikhil Naik, Scott Duke Kominers, and their collaborators are hoping to transform the way scientists study urban environments, with an assist from Google.

In joint work with Edward L. Glaeser, the Fred and Eleanor Glimp Professor of Economics at Harvard, and César A. Hidalgo and Ramesh Raskar, associate professors at the MIT Media Lab, Kominers, an associate professor in the entrepreneurial management unit at Harvard Business School (HBS) and the department of economics, and Naik, a Prize Fellow in economics, history, and politics, authored a study that uses computer vision algorithms to examine millions of Google Street View images to measure how urban areas are changing.

#urban_matter via Renaud Epstein sur Twitter

Project Naptha - #OCR in the browser
►http://projectnaptha.com

Project Naptha automatically applies state-of-the-art computer vision algorithms on every image you see while browsing the web. The result is a seamless and intuitive experience, where you can highlight as well as copy and paste and even edit and translate the text formerly trapped within an image.

#chrome via @francoisbriatte

Le camouflage open-source contre les détections de visages automatiques
►http://www.cvdazzle.com

Introduction

CV Dazzle is camouflage from computer vision (CV). It is a form of expressive interference that combines makeup and hair styling (or other modifications) with face-detection thwarting designs. The name is derived from a type of camouflage used during WWI, called Dazzle, which was used to break apart the gestalt-image of warships, making it hard to discern their directionality, size, and orientation. Likewise, the goal of CV Dazzle is to break apart the gestalt of a face, or object, and make it undetectable to computer vision algorithms, in particular face detection.

And because face detection is the first step in automated facial recognition, CV Dazzle can be used in any environment where automated face recognition systems are in use, such as Google’s Picasa, Flickr, or Facebook (see CV Dazzle vs PhotoTagger by Face.com).

Article en français sur ►http://www.ufunk.net/techno/le-camouflage-open-source-contre-les-d%C3%A9tections-de-visages-automatiques
►http://www.cvdazzle.com/assets/images/comparison_sm.jpg