LabelMe-iPhone: Hand-held Visual Object Tagging and Recognition

Large databases of labeled images are a key ingredient in building
large-scale object recognition systems and for this purpose MIT’s
computer vision group has produced LabelMe, a web-based image
annotation tool and online repository. LabelMe has helped shape the
frontier of object recognition research and we feel it is time to
start thinking about annotation and recognition beyond the desktop.
We are primarily seeking a highly motivated UROP candidate to help us
extend the LabelMe web-based interface to the iPhone, which will let
users capture interesting photos as well as label them using their
iPhones. We believe LabelMe-iPhone will let our labeled image dataset
grow to unprecedented size as well as provide a great starting point
for other research projects in our lab. The ideal candidate should
have experience in iPhone and web-based development development.
Knowledge of computer vision and/or machine learning is a plus, but
not necessary.

Prerequisite: iPhone and web-based programming experience
Supervisors: Dr. Tomasz Malisiewicz (Postdoc) and Prof. Antonio Torralba

Contact: Interested candidates should send a resume along with a brief
description of research interests and experience to and